"keyword","repo_name","file_path","file_extension","file_size","line_count","content","language" "Conjugate","guochu/VQC.jl","src/densitymatrix.jl",".jl","4224","96","struct DensityMatrix{T <: Number} data::Vector{T} nqubits::Int function DensityMatrix{T}(data::AbstractVector{<:Number}, nqubits::Int) where {T <: Number} (length(data) == 2^(2*nqubits)) || throw(DimensionMismatch()) new{T}(convert(Vector{T}, data), nqubits) end end function DensityMatrix{T}(m::AbstractMatrix{<:Number}, nqubits::Int) where {T <: Number} (size(m, 1) == size(m, 2) == 2^nqubits) || throw(DimensionMismatch()) return DensityMatrix{T}(reshape(m, length(m)), nqubits) end function DensityMatrix{T}(m::AbstractVector{<:Number}) where {T <: Number} n = _nqubits(m) return DensityMatrix{T}(m, div(n, 2)) end DensityMatrix{T}(m::AbstractMatrix{<:Number}) where {T <: Number} = DensityMatrix{T}(reshape(m, length(m))) DensityMatrix(data::Union{AbstractVector, AbstractMatrix}, nqubits::Int) = DensityMatrix{eltype(data)}(data, nqubits) DensityMatrix(data::AbstractVector) = DensityMatrix(data, div(_nqubits(data), 2)) DensityMatrix(data::AbstractMatrix) = DensityMatrix(reshape(data, length(data))) function DensityMatrix{T}(nqubits::Int) where {T<:Number} v = zeros(T, 2^(2*nqubits)) v[1,1] = 1 return DensityMatrix{T}(v, nqubits) end DensityMatrix(::Type{T}, nqubits::Int) where {T<:Number} = DensityMatrix{T}(nqubits) DensityMatrix(nqubits::Int) = DensityMatrix(ComplexF64, nqubits) DensityMatrix(x::DensityMatrix) = DensityMatrix(x.data, nqubits(x)) DensityMatrix(x::StateVector) = (x_data = storage(x); DensityMatrix(kron(conj(x_data), x_data), nqubits(x))) storage(x::DensityMatrix) = (L = 2^(nqubits(x)); reshape(x.data, L, L)) QuantumCircuits.nqubits(x::DensityMatrix) = x.nqubits Base.eltype(::Type{DensityMatrix{T}}) where T = T Base.eltype(x::DensityMatrix) = eltype(typeof(x)) Base.getindex(x::DensityMatrix, j::Int...) = getindex(storage(x), j...) Base.setindex!(x::StateVector, v, j::Int...) = setindex!(storage(x), v, j...) Base.convert(::Type{DensityMatrix{T}}, x::DensityMatrix) where {T<:Number} = DensityMatrix(convert(Vector{T}, x.data), nqubits(x)) Base.copy(x::DensityMatrix) = DensityMatrix(copy(x.data), nqubits(x)) Base.cat(v::DensityMatrix) = v function Base.cat(v::DensityMatrix...) a, b = _qcat_util(storage.(v)...) return DensityMatrix(kron(a, b)) end Base.isapprox(x::DensityMatrix, y::DensityMatrix; kwargs...) = isapprox(x.data, y.data; kwargs...) Base.:(==)(x::DensityMatrix, y::DensityMatrix) = x.data == y.data Base.:+(x::DensityMatrix, y::DensityMatrix) = DensityMatrix(x.data + y.data, nqubits(x)) Base.:-(x::DensityMatrix, y::DensityMatrix) = DensityMatrix(x.data - y.data, nqubits(x)) Base.:*(x::DensityMatrix, y::Number) = DensityMatrix(x.data * y, nqubits(x)) Base.:*(x::Number, y::DensityMatrix) = y * x Base.:/(x::DensityMatrix, y::Number) = DensityMatrix(x.data / y, nqubits(x)) LinearAlgebra.tr(x::DensityMatrix) = tr(storage(x)) LinearAlgebra.dot(x::DensityMatrix, y::DensityMatrix) = dot(storage(x), storage(y)) LinearAlgebra.normalize!(x::DensityMatrix) = (x.data ./= tr(x); x) LinearAlgebra.normalize(x::DensityMatrix) = normalize!(copy(x)) LinearAlgebra.ishermitian(x::DensityMatrix) = ishermitian(storage(x)) LinearAlgebra.isposdef(x::DensityMatrix) = isposdef(storage(x)) fidelity(x::DensityMatrix, y::DensityMatrix) = real(tr(sqrt(storage(x)) * sqrt(storage(y)))) fidelity(x::DensityMatrix, y::StateVector) = real(dot(storage(y), storage(x), storage(y))) fidelity(x::StateVector, y::DensityMatrix) = fidelity(y, x) distance2(x::DensityMatrix, y::DensityMatrix) = _distance2(x, y) distance(x::DensityMatrix, y::DensityMatrix) = _distance(x, y) schmidt_numbers(x::DensityMatrix) = eigvals(Hermitian(storage(x))) renyi_entropy(x::DensityMatrix; kwargs...) = renyi_entropy(schmidt_numbers(x); kwargs...) function rand_densitymatrix(::Type{T}, n::Int) where {T <: Number} (n >= 1) || error(""number of qubits must be positive."") L = 2^n v = randn(T, L, L) v = v' * v return normalize!(DensityMatrix(v' * v, n)) end rand_densitymatrix(n::Int) = rand_densitymatrix(ComplexF64, n) function QuantumCircuits.permute(x::DensityMatrix, newindex::Vector{Int}) n = nqubits(x) L = length(x.data) return DensityMatrix(reshape(permute(reshape(x.data, ntuple(i->2, 2*n)), vcat(newindex, newindex .+ n)), L), n) end ","Julia" "Conjugate","guochu/VQC.jl","src/measure.jl",".jl","2569","90",""""""" apply!(x::QMeasure, qstate) """""" function apply!(x::QMeasure, qstate::Union{StateVector, DensityMatrix}) x.keep || error(""only keep mode is implemented."") probability, istate = _local_measure(storage(qstate), x.position) op = I₂ if x.auto_reset m = kron(op[:, istate], QuantumCircuits.Gates.ZERO)/sqrt(probability) else m = kron(op[:, istate], op[:, istate])/sqrt(probability) end m = reshape(m, (2, 2)) apply!(gate(x.position, m), qstate) return istate-1, probability end """""" measure!(qstate::StateVector, pos::Int; auto_reset::Bool=true) Measure the i-th qubit of the quantum state, and return a 2-tuple including the measurement outcome, \n and the probability with which we get the outcome. The quantum state is updated inplace. \n If auto_reset=true,the measured qubit is reset to 0, otherwise it will be the same as the measurement outcome. """""" measure!(qstate::Union{StateVector, DensityMatrix}, pos::Int; auto_reset::Bool=true) = apply!(QMeasure(pos, auto_reset=auto_reset), qstate) function apply(s::QMeasure, qstater::StateVector) qstate = storage(qstater) swap!(qstate, 1, s.position) probability, istate = _local_measure(qstate, 1) # println(""with probability $probability to get $(istate-1)"") ss = div(length(qstate), 2) r = (transpose(I₂[:, istate])*reshape(qstate, (2, ss)))/sqrt(probability) swap!(qstate, 1, s.position) return StateVector(reshape(r, length(r)), nqubits(qstater)-1), istate-1, probability end """""" measure(qstate::StateVector, i::Int) Measure the i-th qubit of the quantum state, and return a 3-tuple including the collapsed quantum state, \n the measurement outcome, and the probability with which we get the outcome. """""" measure(qstate::StateVector, pos::Int) = apply(QMeasure(pos), qstate) function compute_probability_zero(v::AbstractVector, key::Int) L = length(v) pos = 2^(key-1) stri = pos * 2 r = 0. for i in 0:stri:(L-1) @inbounds for j in 0:(pos-1) l = i + j + 1 r += abs2(v[l]) end end return r end function _local_measure(v::AbstractVector, key::Int) p0 = compute_probability_zero(v, key) l = [p0, 1-p0] i = discrete_sample(l) return l[i], i end # for density matrix function compute_probability_zero(v::AbstractMatrix, key::Int) L = size(v, 1) pos = 2^(key-1) stri = pos * 2 r = 0. for i in 0:stri:(L-1) @inbounds for j in 0:(pos-1) l = i + j + 1 r += real(v[l, l]) end end return r end function _local_measure(v::AbstractMatrix, key::Int) p0 = compute_probability_zero(v, key) l = [p0, 1-p0] i = discrete_sample(l) return l[i], i end ","Julia" "Conjugate","guochu/VQC.jl","src/postselect.jl",".jl","2515","72"," function apply!(x::QSelect, qstate::StateVector) x.state == 0 ? apply!(gate(x.position, QuantumCircuits.Gates.UP), qstate) : apply!(gate(x.position, QuantumCircuits.Gates.DOWN), qstate) s = norm(qstate) qstate.data ./= s return s end function apply(x::QSelect, qstate::StateVector; keep::Bool=false) r = _apply_impl(x, qstate, keep=keep) ns = cnorm(storage(r)) return r / ns, real(ns) end """""" post_select!(qstate::StateVector, key::Int, state::Int=0) Post-select the i-th qubit of the quantum state, and the quantum state is updated inplace, the probability is returned. """""" post_select!(qstate::StateVector, key::Int, state::Int=0) = apply!(QSelect(key, state), qstate) """""" post_select(qstate::StateVector, key::Int, state::Int=0; keep::Bool=false) Return the collapsed quantum state as well as the probability. """""" post_select(qstate::StateVector, key::Int, state::Int=0; keep::Bool=false) = apply(QSelect(key, state), qstate, keep=keep) function _apply_throw_impl(x::QSelect, qstate::StateVector) swap!(storage(qstate), 1, x.position) ss = div(length(storage(qstate)), 2) tmp = reshape(storage(qstate), (2, ss)) r = x.state==0 ? QuantumCircuits.Gates.ZERO'*tmp : QuantumCircuits.Gates.ONE'*tmp swap!(storage(qstate), 1, x.position) return StateVector(reshape(r, length(r)), nqubits(qstate)-1) end function _apply_keep_impl(x::QSelect, qstate::StateVector) tmp = copy(qstate) x.state == 0 ? apply!(gate(x.position, QuantumCircuits.Gates.UP), tmp) : apply!(gate(x.position, QuantumCircuits.Gates.DOWN), tmp) return StateVector(tmp, nqubits(qstate)-1) end function _apply_impl(x::QSelect, qstate::StateVector; keep::Bool=false) return keep ? _apply_keep_impl(x, qstate) : _apply_throw_impl(x, qstate) end cnorm(x::AbstractVector) = sqrt(dot(x, x)) @adjoint QSelect(key::Int, state::Int) = QSelect(key, state), z -> (nothing, nothing) @adjoint _apply_throw_impl(x::QSelect, qstate::StateVector) = _apply_throw_impl(x, qstate), z -> begin if x.state == 0 m = StateVector(kron(storage(z), ZERO)) else m = StateVector(kron(storage(z), ONE)) end swap!(storage(m), 1, x.position) return (nothing, m) end @adjoint _apply_keep_impl(x::QSelect, qstate::StateVector) = _apply_keep_impl(x, qstate), z -> (nothing, _apply_keep_impl(x, StateVector(z, nqubits(qstate))) ) @adjoint _apply_impl(x::QSelect, qstate::StateVector; keep::Bool) = begin return keep ? Zygote.pullback(_apply_keep_impl, x, qstate) : Zygote.pullback(_apply_throw_impl, x, qstate) end ","Julia" "Conjugate","guochu/VQC.jl","src/statevector.jl",".jl","7557","229","struct StateVector{T <: Number} data::Vector{T} nqubits::Int function StateVector{T}(data::AbstractVector{<:Number}, nqubits::Int) where {T <: Number} @assert length(data) == 2^nqubits new{T}(convert(Vector{T}, data), nqubits) end end StateVector(data::AbstractVector{T}, nqubits::Int) where {T <: Number} = StateVector{T}(data, nqubits) StateVector{T}(data::AbstractVector{<:Number}) where T = StateVector{T}(data, _nqubits(data)) StateVector(data::AbstractVector{T}) where {T <: Number} = StateVector{T}(data) function StateVector{T}(nqubits::Int) where {T<:Number} v = zeros(T, 2^nqubits) v[1] = 1 return StateVector{T}(v, nqubits) end StateVector(::Type{T}, nqubits::Int) where {T<:Number} = StateVector{T}(nqubits) StateVector(nqubits::Int) = StateVector(ComplexF64, nqubits) StateVector(x::StateVector) = StateVector(x.data, nqubits(x)) storage(x::StateVector) = x.data QuantumCircuits.nqubits(x::StateVector) = x.nqubits Base.eltype(::Type{StateVector{T}}) where T = T Base.eltype(x::StateVector) = eltype(typeof(x)) Base.getindex(x::StateVector, j::Int) = getindex(storage(x), j) Base.setindex!(x::StateVector, v, j::Int) = setindex!(storage(x), v, j) Base.convert(::Type{StateVector{T}}, x::StateVector) where {T<:Number} = StateVector(convert(Vector{T}, storage(x)), nqubits(x)) Base.copy(x::StateVector) = StateVector(copy(storage(x)), nqubits(x)) Base.cat(v::StateVector) = v function Base.cat(v::StateVector...) a, b = _qcat_util(storage.(v)...) return StateVector(kron(a, b)) end Base.isapprox(x::StateVector, y::StateVector; kwargs...) = isapprox(storage(x), storage(y); kwargs...) Base.:(==)(x::StateVector, y::StateVector) = storage(x) == storage(y) Base.:+(x::StateVector, y::StateVector) = StateVector(storage(x) + storage(y), nqubits(x)) Base.:-(x::StateVector, y::StateVector) = StateVector(storage(x) - storage(y), nqubits(x)) Base.:*(x::StateVector, y::Number) = StateVector(storage(x) * y, nqubits(x)) Base.:*(x::Number, y::StateVector) = y * x Base.:/(x::StateVector, y::Number) = StateVector(storage(x) / y, nqubits(x)) Base.:*(m::AbstractMatrix, x::StateVector) = StateVector( m * storage(x), nqubits(x) ) LinearAlgebra.norm(x::StateVector) = norm(storage(x)) LinearAlgebra.dot(x::StateVector, y::StateVector) = dot(storage(x), storage(y)) LinearAlgebra.dot(x::StateVector, m::AbstractVector, y::StateVector) = dot(storage(x), m, storage(y)) LinearAlgebra.normalize!(x::StateVector) = (normalize!(storage(x)); x) LinearAlgebra.normalize(x::StateVector) = StateVector(normalize(storage(x)), nqubits(x)) """""" fidelity(x, y) tr(√x * √y) if x and y are density matrices ⟨x|y⟩^2 if x and y are pure states """""" fidelity(x::StateVector, y::StateVector) = abs2(dot(x, y)) distance2(x::StateVector, y::StateVector) = _distance2(x, y) distance(x::StateVector, y::StateVector) = _distance(x, y) # encoding onehot_encoding(::Type{T}, n::Int) where {T <: Number} = StateVector(onehot(T, 2^n, 1), n) onehot_encoding(n::Int) = onehot_encoding(ComplexF64, n) onehot_encoding(::Type{T}, i::AbstractVector{Int}) where {T <: Number} = StateVector(onehot(T, 2^(length(i)), _sub2ind(i)+1), length(i)) onehot_encoding(i::AbstractVector{Int})= onehot_encoding(ComplexF64, i) function onehot(::Type{T}, L::Int, pos::Int) where T r = zeros(T, L) r[pos] = one(T) return r end """""" kernal_mapping(s::Real) = [cos(s*pi/2), sin(s*pi/2)] This maps 0 -> [1, 0] (|0>), and 1 -> [0, 1] (|1>) """""" kernal_mapping(s::Real) = [cos(s*pi/2), sin(s*pi/2)] """""" qstate(::Type{T}, thetas::AbstractVector{<:Real}) where {T <: Number} Return a product quantum state of [[cos(pi*theta/2), sin(pi*theta/2)]] for theta in thetas]\n Example: qstate(Complex{Float64}, [0.5, 0.7]) """""" function qubit_encoding(::Type{T}, i::AbstractVector{<:Real}) where {T <: Number} isempty(i) && throw(""empty input."") v = [convert(Vector{T}, item) for item in kernal_mapping.(i)] (length(v) == 1) && return StateVector{T}(v[1]) a, b = _qcat_util(v...) return StateVector(kron(a, b)) end qubit_encoding(mpsstr::AbstractVector{<:Real}) = qubit_encoding(ComplexF64, mpsstr) function amplitude_encoding(::Type{T}, v::AbstractVector{<:Number}; nqubits::Int=ceil(Int, log2(length(v)))) where {T<:Number} vn = norm(v) (vn ≈ 1.) || println(""input vector is not normalized, it will be renormalized as a quantum state."") vv = zeros(T, 2^nqubits) for i in 1:length(v) vv[i] = v[i] / vn end return StateVector(vv, nqubits) end amplitude_encoding(v::AbstractVector; kwargs...) = amplitude_encoding(ComplexF64, v; kwargs...) function reset!(x::StateVector) fill!(storage(x), zero(eltype(x))) x[1] = one(eltype(x)) return x end function reset_onehot!(x::StateVector, i::AbstractVector{Int}) @assert nqubits(x) == length(i) pos = _sub2ind(i) + 1 fill!(storage(x), zero(eltype(x))) x[pos] = one(eltype(x)) return x end function reset_qubit!(x::StateVector, i::AbstractVector{<:Real}) @assert nqubits(x) == length(i) if length(i) == 1 copyto!(storage(x), kernal_mapping(i[1])) return x end a, b = _qcat_util(kernal_mapping.(i)...) m = length(a) n = length(b) xs = storage(x) for j in 1:m n_start = (j-1) * n + 1 n_end = j * n tmp = a[j] @. xs[n_start:n_end] = tmp * b end return x end function amplitude(s::StateVector, i::AbstractVector{Int}; scaling::Real=sqrt(2)) @assert length(i)==nqubits(s) idx = _sub2ind(i) return scaling==1 ? s[idx] : s[idx] * scaling^(nqubits(s)) end amplitudes(s::StateVector) = storage(s) function rand_state(::Type{T}, n::Int) where {T <: Number} (n >= 1) || error(""number of qubits must be positive."") v = randn(T, 2^n) v ./= norm(v) return StateVector(v, n) end rand_state(n::Int) = rand_state(ComplexF64, n) function QuantumCircuits.permute(x::StateVector, newindex::Vector{Int}) n = nqubits(x) L = length(storage(x)) return StateVector(reshape(permute(reshape(storage(x), ntuple(i->2,n)), newindex), L), n) end function _sub2ind(v::AbstractVector{Int}) @assert _is_valid_indices(v) isempty(v) && error(""input index is empty."") L = length(v) r = v[1] for i in 2:L r |= v[i] << (i-1) end return r end function _qcat_util(vr::Union{AbstractVector, AbstractMatrix}...) v = reverse(vr) L = length(v) # println(""$(typeof(v)), $L"") (L >= 2) || error(""something wrong."") Lh = div(L, 2) a = v[1] for i in 2:Lh a = kron(a, v[i]) end b = v[Lh + 1] for i in Lh+2 : L b = kron(b, v[i]) end return a, b end function _is_valid_indices(i::AbstractVector{Int}) for s in i (s == 0 || s == 1) || return false end return true end _nqubits(s::AbstractVector) = begin n = round(Int, log2(length(s))) (2^n == length(s)) || error(""state can not be interpretted as a qubit state."") return n end # function reset!(x::AbstractVector, i::AbstractVector{<:AbstractFloat}) # (nqubits(x) == length(i)) || error(""input basis mismatch with number of qubits."") # mpsstr = kernal_mapping.(i) # for (pos, item) in enumerate(Iterators.product(mpsstr...)) # x[pos] = prod(item) # end # return x # end # function qrandn(::Type{T}, n::Int) where {T <: Number} # (n >= 1) || error(""number of qubits must be positive."") # v = randn(T, 2^n) # v ./= norm(v) # return v # end # qrandn(n::Int) = qrandn(Complex{Float64}, n) ","Julia" "Conjugate","guochu/VQC.jl","src/VQC.jl",".jl","1750","86","module VQC using Zygote using Zygote: @adjoint using LinearAlgebra, StaticArrays, QuantumCircuits, QuantumCircuits.Gates using QuantumCircuits: permute import LinearAlgebra, QuantumCircuits # using KrylovKit: exponentiate # using SparseArrays: spzeros, sparse, SparseMatrixCSC # using Logging: @warn # statevector export StateVector, DensityMatrix, distance, distance2, onehot_encoding, qubit_encoding, amplitude_encoding, reset!, amplitude, amplitudes export tr, dot, norm, normalize!, normalize, ishermitian export reset_qubit!, reset_onehot!, storage, fidelity, rand_state, rand_densitymatrix, permute export schmidt_numbers, renyi_entropy # gate operations export apply! # measurement export measure, measure! # hamiltonian export expectation # AD for post selection may be removed in the future export post_select, post_select! # partial trace export partial_tr # utility functions # auxiliary include(""auxiliary/distance.jl"") include(""auxiliary/parallel_for.jl"") include(""auxiliary/sampling.jl"") include(""auxiliary/tensorops.jl"") include(""auxiliary/indexop.jl"") # definitions of pure quantum gate include(""statevector.jl"") # density matrix representation include(""densitymatrix.jl"") # quantum gate operations include(""applygates/applygates.jl"") # measurement and postselection include(""measure.jl"") include(""postselect.jl"") # hamiltonian expectation include(""hamiltonian/util.jl"") include(""hamiltonian/apply_qterms/apply_qterms.jl"") include(""hamiltonian/expecs/expecs.jl"") include(""hamiltonian/expecs_dm/expecs_dm.jl"") # differentiation include(""circuitdiff.jl"") include(""expecdiff.jl"") include(""additional_adjoints.jl"") # partial trace include(""ptrace.jl"") # utility functions include(""utility/utility.jl"") end ","Julia" "Conjugate","guochu/VQC.jl","src/expecdiff.jl",".jl","2366","71","# gradient of expectation values function _qterm_expec_util(m::QubitsTerm, state::StateVector) if length(positions(m)) <= LARGEST_SUPPORTED_NTERMS return expectation(m, state), z -> (nothing, (conj(z) * m + z * m') * state ) else v = m * state return dot(state, v), z -> begin m1 = conj(z) * m m2 = z * m' _apply_qterm_util!(m1, storage(state), storage(v)) v2 = storage( m2 * state ) v2 .+= storage(v) return (nothing, StateVector(v2, nqubits(state))) end end end # this could be slow # _qterm_expec_util(m::QubitsTerm, state::DensityMatrix) = expectation(m, state), z -> ( # nothing, storage((conj(z) * m + z * m') * DensityMatrix(one(storage(state)), nqubits(state))) ) _qterm_expec_util(m::QubitsTerm, state::DensityMatrix) = expectation(m, state), z -> ( nothing, (z * m') * DensityMatrix(one(storage(state)), nqubits(state))) @adjoint expectation(m::QubitsTerm, state::Union{StateVector, DensityMatrix}) = _qterm_expec_util(m, state) function _qop_expec_util(m::QubitsOperator, state_in::StateVector) if _largest_nterm(m) <= LARGEST_SUPPORTED_NTERMS return expectation(m, state_in), z -> (nothing, (conj(z) * m + z * m') * state_in ) else state = storage(state_in) workspace = similar(state) state_2 = zeros(eltype(state), length(state)) for (k, v) in m.data for item in v _apply_qterm_util!(QubitsTerm(k, item[1], item[2]), state, workspace) state_2 .+= workspace end end r = dot(state, state_2) return r, z -> begin if ishermitian(m) state_2 .*= (conj(z) + z) else state_2 .*= conj(z) md = m' for (k, v) in md.data for item in v _apply_qterm_util!(QubitsTerm(k, item[1], item[2]), state, workspace) @. state_2 += z * workspace end end end return (nothing, StateVector(state_2, nqubits(state_in))) end end end # _qop_expec_util(m::QubitsOperator, state::DensityMatrix) = expectation(m, state), z -> ( # nothing, storage( (conj(z) * m + z * m') * DensityMatrix(one(storage(state)), nqubits(state)) ) ) _qop_expec_util(m::QubitsOperator, state::DensityMatrix) = expectation(m, state), z -> ( nothing, (z * m') * DensityMatrix(one(storage(state)), nqubits(state)) ) @adjoint expectation(m::QubitsOperator, state::Union{StateVector, DensityMatrix}) = _qop_expec_util(m, state) ","Julia" "Conjugate","guochu/VQC.jl","src/additional_adjoints.jl",".jl","968","21"," @adjoint storage(x::Union{StateVector, DensityMatrix}) = storage(x), z -> (typeof(x)(z),) @adjoint nqubits(x::Union{StateVector, DensityMatrix}) = nqubits(x), z -> (nothing,) @adjoint StateVector(data::AbstractVector{<:Number}, n::Int) = StateVector(data, n), z -> (storage(z), nothing) @adjoint StateVector(data::AbstractVector{<:Number}) = StateVector(data), z -> (storage(z),) @adjoint DensityMatrix(data::AbstractMatrix{<:Number}, n::Int) = DensityMatrix(data, n), z -> (storage(z), nothing) @adjoint DensityMatrix(data::AbstractMatrix{<:Number}) = DensityMatrix(data), z -> (storage(z),) # @adjoint dot(x::StateVector, y::StateVector) = begin # v, back = Zygote.pullback(dot, storage(x), storage(y)) # return v, z -> begin # a, b = back(z) # return StateVector(a, nqubits(x)), StateVector(b, nqubits(y)) # end # end # # this is stupid, why should I need it # @adjoint dot(x::StateVector, y::StateVector) = Zygote.pullback(dot, storage(x), storage(y)) ","Julia" "Conjugate","guochu/VQC.jl","src/ptrace.jl",".jl","1669","55","# partial trace function partial_tr(state::DensityMatrix, sites::Vector{Int}) isempty(sites) && return state # some checks check_partial_tr_inputs(sites, nqubits(state)) (length(sites) == nqubits(state)) && return tr(state) return DensityMatrix(_partial_tr_impl(storage(state), sites, nqubits(state)), nqubits(state) - length(sites) ) end function partial_tr(state::StateVector, sites::Vector{Int}) isempty(sites) && return DensityMatrix(state) n = nqubits(state) check_partial_tr_inputs(sites, n) (length(sites) == n) && return dot(state, state) axis = move_selected_index_backward(collect(1:n), sites) vt = permute(reshape(storage(state), ntuple(i->2, n)), axis) vt_shape = size(vt) s1 = prod(vt_shape[1:(n-length(sites))]) s2 = prod(vt_shape[(n-length(sites)+1):end]) vt = reshape(vt, s1, s2) # vt = vt * vt' return DensityMatrix(vt * vt', n - length(sites) ) end function check_partial_tr_inputs(sites::Vector{Int}, n::Int) tmp = Set(sites) (length(sites) == length(tmp)) || throw(ArgumentError(""duplicate sites not allowed."")) for item in tmp (item>=1 && item<=n) || throw(ArgumentError(""site out of range."")) end end function _partial_tr_impl(v::AbstractMatrix, sites::Vector{Int}, n::Int) axis = move_selected_index_backward(collect(1:n), sites) # rdim = reverse(dim) vt = reshape(v, ntuple(i->2, 2*n)) axis2 = axis .+ n vt = permute(vt, [axis..., axis2...]) vt_shape = size(vt)[1:n] s1 = prod(vt_shape[1:(n-length(sites))]) s2 = prod(vt_shape[(n-length(sites)+1):end]) vt = permute(reshape(vt, s1,s2,s1,s2), (1,3,2,4)) r = zeros(eltype(vt), s1, s1) for i in 1:s2 r .+= view(vt, :, :, i, i) end return r end ","Julia" "Conjugate","guochu/VQC.jl","src/circuitdiff.jl",".jl","2837","91"," @adjoint *(circuit::QCircuit, x::Union{StateVector, DensityMatrix}) = begin y = circuit * x return y, Δ -> begin Δ, grads, y = back_propagate(copy(Δ), circuit, copy(y)) return grads, Δ end end @adjoint qubit_encoding(::Type{T}, mpsstr::Vector{<:Real}) where {T<:Number} = begin y = qubit_encoding(T, mpsstr) return y, Δ -> begin circuit = QCircuit([RyGate(i, theta*pi, isparas=true) for (i, theta) in enumerate(mpsstr)]) Δ, grads, y = back_propagate(Δ, circuit, copy(y)) return nothing, grads .* pi end end # @adjoint amplitude_encoding(::Type{T}, v::AbstractVector{<:Number}; kwargs...) where {T <: Number} = amplitude_encoding( # T, v; kwargs...), z -> (nothing, z[1:length(v)]) function back_propagate(Δ::StateVector, m::Gate, y::StateVector) Δ = apply!(m', Δ) y = apply!(m', y) ∇θs = nothing if nparameters(m) > 0 ∇θs = [real(expectation(y, item, Δ)) for item in differentiate(m)] end return Δ, ∇θs, y end # a temporary solution, which requires an additional copy of the density matrix # we can not assume x or y to be positive or hermitian here, since they may not be physical density matrix function expectation(x::DensityMatrix, m::Gate, y::DensityMatrix) yc = copy(y) apply_threaded!(m, yc.data) return dot(storage(x)', storage(yc)) end function back_propagate(Δ::DensityMatrix, m::Gate, y::DensityMatrix) Δ = apply!(m', Δ) y = apply!(m', y) ∇θs = nothing if nparameters(m) > 0 ∇θs = [real(expectation(y, item, Δ) + expectation(Δ, item', y)) for item in differentiate(m)] end return Δ, ∇θs, y end function back_propagate(Δ::DensityMatrix, m::QuantumMap, y::DensityMatrix) Δ = apply_dagger!(m, Δ) y = apply_inverse!(m, y) ∇θs = nothing return Δ, ∇θs, y end function back_propagate_util(Δ, circuit::QCircuit, y) RT = real(eltype(y)) grads = Vector{RT}[] for item in reverse(circuit) Δ, ∇θs, y = back_propagate(Δ, item, y) !isnothing(∇θs) && push!(grads, ∇θs) end ∇θs_all = RT[] for item in Iterators.reverse(grads) append!(∇θs_all, item) end return Δ, ∇θs_all, y end back_propagate(Δ::StateVector, circuit::QCircuit, y::StateVector) = back_propagate_util(Δ, circuit, y) back_propagate(Δ::DensityMatrix, circuit::QCircuit, y::DensityMatrix) = back_propagate_util(Δ, circuit, y) # function back_propagate(Δ::AbstractMatrix, m::Gate, y::DensityMatrix) # Δ = StateVector(Δ, nqubits(y)) # Δ = apply!(m', Δ) # y = apply!(m', y) # ∇θs = nothing # if nparameters(m) > 0 # ∇θs = [real(expectation(y, item, Δ)) for item in differentiate(m)] # end # return storage(Δ), ∇θs, y # end ","Julia" "Conjugate","guochu/VQC.jl","src/utility/groundstate.jl",".jl","1071","25","using KrylovKit: eigsolve, exponentiate function ground_state(h::QubitsOperator; kwargs...) ishermitian(h) || throw(ArgumentError(""input operator is not hermitian."")) n = QuantumCircuits.get_largest_pos(h) T = eltype(h) init_state = rand_state(T, n) eigvalues, eigvectors, info = eigsolve(x -> storage(h(StateVector(x, n))), storage(init_state), 1, :SR; ishermitian=true, kwargs...) (info.converged>=1) || error(""eigsolve fails to converge."") return eigvalues[1], StateVector(eigvectors[1], n) end function time_evolution(h::QubitsOperator, t::Number, v::StateVector; kwargs...) ishermitian(h) || throw(ArgumentError(""input operator is not hermitian."")) (QuantumCircuits.get_largest_pos(h) <= nqubits(v)) || throw(ArgumentError(""number of qubits mismatch."")) n = nqubits(v) T = promote_type(eltype(h), typeof(t), eltype(v) ) v = convert(StateVector{T}, v) tmp, info = exponentiate(x -> storage(h(StateVector(x, n))), t, storage(v); ishermitian=true, kwargs...) (info.converged>=1) || error(""eigsolve fails to converge."") return StateVector(tmp, n) end","Julia" "Conjugate","guochu/VQC.jl","src/utility/variationalcircuit.jl",".jl","4239","149",""""""" variational_circuit_1d(L::Int, depth::Int; θs::Vector{<:Real}) Return a variational quantum circuit given L qubis and d depth """""" function variational_circuit_1d(L::Int, depth::Int; θs::Vector{<:Real}=rand(_nparas(ComplexF64, L, depth)) .* 2π) paras = θs (length(paras) == _nparas(ComplexF64, L, depth)) || throw(""wrong number of parameters."") circuit = QCircuit() ncount = 1 for i in 1:L push!(circuit, RzGate(i, paras[ncount], isparas=true)) ncount += 1 push!(circuit, RyGate(i, paras[ncount], isparas=true)) ncount += 1 push!(circuit, RzGate(i, paras[ncount], isparas=true)) ncount += 1 end for i in 1:depth if isodd(i) for j in 1:(L-1) push!(circuit, CNOTGate(j, j+1)) end else for j in (L-1):-1:1 push!(circuit, CNOTGate(j, j+1)) end end for j in 1:L push!(circuit, RzGate(j, paras[ncount], isparas=true)) ncount += 1 push!(circuit, RyGate(j, paras[ncount], isparas=true)) ncount += 1 push!(circuit, RzGate(j, paras[ncount], isparas=true)) ncount += 1 end end @assert ncount == length(paras)+1 return circuit end function real_variational_circuit_1d(L::Int, depth::Int; θs::Vector{<:Real}=rand(_nparas(Float64, L, depth)) .* 2π) paras = θs (length(paras) == _nparas(Float64, L, depth)) || throw(""wrong number of parameters."") circuit = QCircuit() ncount = 1 for i in 1:L push!(circuit, RyGate(i, paras[ncount], isparas=true)) ncount += 1 end for i in 1:depth if isodd(i) for j in 1:(L-1) push!(circuit, CNOTGate(j, j+1)) end else for j in (L-1):-1:1 push!(circuit, CNOTGate(j, j+1)) end end for j in 1:L push!(circuit, RyGate(j, paras[ncount], isparas=true)) ncount += 1 end end @assert ncount == length(paras)+1 return circuit end # function variational_circuit_2d(m::Int, n::Int, depth::Int; θs::Vector{<:Real}=rand(_nparas(ComplexF64, m*n, depth)) .* 2π) # paras = θs # L = m*n # (length(paras) == _nparas(ComplexF64, L, depth)) || throw(""wrong number of parameters."") # circuit = QCircuit() # ncount = 1 # for i in 1:L # push!(circuit, RzGate(i, paras[ncount], isparas=true)) # ncount += 1 # push!(circuit, RyGate(i, paras[ncount], isparas=true)) # ncount += 1 # push!(circuit, RzGate(i, paras[ncount], isparas=true)) # ncount += 1 # end # index = LinearIndices((m, n)) # for l in 1:depth # for i in 1:m # for j in 1:(n-1) # push!(circuit, CNOTGate(index[i, j], index[i, j+1])) # end # end # for i in 1:(m-1) # for j in 1:n # push!(circuit, CNOTGate(index[i, j], index[i+1, j])) # end # end # for i in 1:L # push!(circuit, RzGate(i, paras[ncount], isparas=true)) # ncount += 1 # push!(circuit, RyGate(i, paras[ncount], isparas=true)) # ncount += 1 # push!(circuit, RzGate(i, paras[ncount], isparas=true)) # ncount += 1 # end # end # @assert ncount == length(paras)+1 # return circuit # end # variational_circuit_2d(shapes::Tuple{Int, Int}, args...; kwargs...) = variational_circuit_2d(shapes[1], shapes[2], args...; kwargs...) # function real_variational_circuit_2d(m::Int, n::Int, depth::Int; θs::Vector{<:Real}=rand(_nparas(Float64, m*n, depth)) .* 2π) # paras = θs # L = m*n # (length(paras) == _nparas(Float64, L, depth)) || throw(""wrong number of parameters."") # circuit = QCircuit() # ncount = 1 # for i in 1:L # push!(circuit, RyGate(i, paras[ncount], isparas=true)) # ncount += 1 # end # index = LinearIndices((m, n)) # for l in 1:depth # for i in 1:m # for j in 1:(n-1) # push!(circuit, CNOTGate(index[i, j], index[i, j+1])) # end # end # for i in 1:(m-1) # for j in 1:n # push!(circuit, CNOTGate(index[i, j], index[i+1, j])) # end # end # for i in 1:L # push!(circuit, RyGate(i, paras[ncount], isparas=true)) # ncount += 1 # end # end # @assert ncount == length(paras)+1 # return circuit # end # real_variational_circuit_2d(shapes::Tuple{Int, Int}, args...; kwargs...) = real_variational_circuit_2d(shapes[1], shapes[2], args...; kwargs...) function _nparas(::Type{T}, L::Int, depth::Int) where {T <: Number} n = depth+1 return (T <: Real) ? n * L : n * L * 3 end ","Julia" "Conjugate","guochu/VQC.jl","src/utility/qft.jl",".jl","427","25","export QFT function _nnqft_one_block(L::Int) (L<=0) && error(""input size can not be 0"") r = QCircuit() if L==1 push!(r, (1, H)) return r else append!(r, _nnqft_one_block(L-1)) push!(r, (((L,L-1), CONTROL(R(L)) * SWAP))) return r end end """""" efficient QFT which only contains nearest neighbour gates. """""" function QFT(L::Int) r = QCircuit() for i = L:-1:1 append!(r, _nnqft_one_block(i)) end return r end","Julia" "Conjugate","guochu/VQC.jl","src/utility/utility.jl",".jl","391","19","module Utilities using VQC using QuantumCircuits, QuantumCircuits.Gates export heisenberg_1d, heisenberg_2d, ising_1d, ising_2d, ground_state, time_evolution export QFT export variational_circuit_1d, real_variational_circuit_1d export order_finding include(""spin_hamiltonians.jl"") include(""groundstate.jl"") include(""qft.jl"") include(""variationalcircuit.jl"") include(""shor/shor.jl"") end","Julia" "Conjugate","guochu/VQC.jl","src/utility/spin_hamiltonians.jl",".jl","2615","86"," """""" heisenberg xxz chain """""" function heisenberg_chain(L::Int; J::Real=1., Jzz::Real=J, hz::Real=0.) sp, sm, z = QuantumCircuits._get_op.([""+"", ""-"", ""Z""]) terms = [] # one site terms for i in 1:L push!(terms, QubitsTerm(i=>z, coeff=hz)) end # nearest-neighbour interactions for i in 1:L-1 t = QubitsTerm(i=>sp, i+1=>sm, coeff=2*J) push!(terms, t) push!(terms, t') push!(terms, QubitsTerm(i=>z, i+1=>z, coeff=Jzz)) end return simplify(QubitsOperator(terms...)) end heisenberg_1d(L::Int; kwargs...) = heisenberg_chain(L; kwargs...) function heisenberg_2d(m::Int, n::Int=m; J::Real=1., Jzz::Real=J, hz::Real=0.) sp, sm, z = QuantumCircuits._get_op.([""+"", ""-"", ""Z""]) terms = [] for i in 1:m*n push!(terms, QubitsTerm(i=>z, coeff=hz)) end index = LinearIndices((m, n)) for i in 1:m for j in 1:(n-1) t = QubitsTerm(index[i, j]=>sp, index[i, j+1]=>sm, coeff=2*J) push!(terms, t) push!(terms, t') push!(terms, QubitsTerm(index[i, j]=>z, index[i, j+1]=>z, coeff=Jzz) ) end end for i in 1:(m-1) for j in 1:n t = QubitsTerm(index[i, j]=>sp, index[i+1, j]=>sm, coeff=2*J) push!(terms, t) push!(terms, t') push!(terms, QubitsTerm(index[i, j]=>z, index[i+1, j]=>z, coeff=Jzz) ) end end return simplify(QubitsOperator(terms...)) end heisenberg_2d(shapes::Tuple{Int, Int}; kwargs...) = heisenberg_2d(shapes[1], shapes[2]; kwargs...) function ising_chain(L::Int; J::Real=1., hz::Real=1.) x, z = QuantumCircuits._get_op.([""X"", ""Z""]) terms = [] for i in 1:L push!(terms, QubitsTerm(i=>z, coeff=hz)) end for i in 1:L-1 push!(terms, QubitsTerm(i=>x, i+1=>x, coeff=J)) end return simplify(QubitsOperator(terms...)) end ising_1d(L::Int; kwargs...) = ising_chain(L; kwargs...) function ising_2d(m::Int, n::Int=m; J::Real=1., hz::Real=1.) x, z = QuantumCircuits._get_op.([""X"", ""Z""]) terms = [] for i in 1:m*n push!(terms, QubitsTerm(i=>z, coeff=hz)) end index = LinearIndices((m, n)) for i in 1:m for j in 1:(n-1) push!(terms, QubitsTerm(index[i, j]=>x, index[i, j+1]=>x, coeff=J) ) end end for i in 1:(m-1) for j in 1:n push!(terms, QubitsTerm(index[i, j]=>x, index[i+1, j]=>x, coeff=J) ) end end return simplify(QubitsOperator(terms...)) end ising_2d(shapes::Tuple{Int, Int}; kwargs...) = ising_2d(shapes[1], shapes[2]; kwargs...) ","Julia" "Conjugate","guochu/VQC.jl","src/utility/shor/shor.jl",".jl","125","8"," include(""util.jl"") include(""Beauregard.jl"") include(""Fowler.jl"") include(""orderfinding_sqc.jl"") include(""orderfinding.jl"") ","Julia" "Conjugate","guochu/VQC.jl","src/utility/shor/Fowler.jl",".jl","6596","284"," # using 2n+4 qubits const PLUS = [0.5+0.5*im 0.5-0.5*im; 0.5-0.5*im 0.5+0.5*im] const MINUS = [0.5-0.5*im 0.5+0.5*im; 0.5+0.5*im 0.5-0.5*im] const CONTROL_PLUS = CONTROL(PLUS) const CONTROL_MINUS = CONTROL(MINUS) """""" n = length(a) n qubits @ input output b[0] b[1] ... b[n-1] """""" LNNAdderCircuit(a::BinaryInteger) = QCircuit([PHASEGate(i, compute_phase(a, i)) for i in 0:(length(a)-1)]) """""" n = len(a) n+1 qubits @input c control qubit b[0] b[1] ... b[n-1] @output b[0] b[1] ... b[n-1] c control qubit """""" LNNCAdderCircuit(a::BinaryInteger; inverse::Bool=false) = inverse ? QCircuit( [gate((i+1, i), SWAP * CONTROL(PHASE(compute_phase(a, i)))) for i in (length(a)-1):-1:0]) : QCircuit( [gate((i, i+1), SWAP * CONTROL(PHASE(compute_phase(a, i)))) for i in 0:(length(a)-1)]) """""" this circuit contains n+6 qubits, where n+1 = len(a) = len(N) x1 MS addition (most significant) qubit in |0> out |0> x2 ki qubit in |0> out |0> kx qubit b[0] b[1] b[2] ... b[n] """""" function LNNModAdderCircuit(N::BinaryInteger, a::BinaryInteger) (length(N)==length(a)) || error(""binary integer a and N size mismatch."") L = length(a) n = L-1 total_circuit = QCircuit() push!(total_circuit, gate((3,4), CONTROL_PLUS)) push!(total_circuit, gate((2,3), CNOT)) push!(total_circuit, gate((3,4), CONTROL_MINUS)) push!(total_circuit, gate((2,3), SWAP*CNOT)) push!(total_circuit, gate((3,4), CONTROL_PLUS)) append!(total_circuit, shift(LNNCAdderCircuit(a, inverse=false), 4)) append!(total_circuit, shift(LNNAdderCircuit(N), 4)') append!(total_circuit, shift(_QFT(L)', 4) ) push!(total_circuit, gate((1,2), SWAP)) push!(total_circuit, gate((2,3), SWAP)) push!(total_circuit, gate((4,3), SWAP * CNOT)) append!(total_circuit, move_site(4, n+4)) append!(total_circuit, shift(_QFT(L), 3)) append!(total_circuit, shift(LNNCAdderCircuit(N, inverse=true), 3) ) append!(total_circuit, shift(LNNCAdderCircuit(a, inverse=false)', 4) ) append!(total_circuit, shift(_QFT(L)', 5) ) append!(total_circuit, move_site(4, n+5)) push!(total_circuit, gate(4, X)) push!(total_circuit, gate((4,3), CNOT)) push!(total_circuit, gate(4, X)) push!(total_circuit, gate((2,3), SWAP)) push!(total_circuit, gate((1,2), SWAP)) push!(total_circuit, gate((0,1), SWAP)) append!(total_circuit, shift(_QFT(L), 4) ) append!(total_circuit, shift(LNNCAdderCircuit(a, inverse=true), 4) ) push!(total_circuit, gate((3,4), CONTROL_MINUS)) push!(total_circuit, gate((2,3), CNOT * SWAP)) push!(total_circuit, gate((3,4), CONTROL_PLUS)) push!(total_circuit, gate((2,3), CNOT)) push!(total_circuit, gate((1,2), SWAP)) push!(total_circuit, gate((0,1), SWAP)) push!(total_circuit, gate((3,4), CONTROL_MINUS)) return total_circuit end """""" this circuit contains 2n+4 qubits, where n+1 = len(a) = len(N) x[0] x[1] ... x[n-2] MS x[n-1] ki kx b[0] n+3 b[1] ... b[n] """""" function LNNCModMultiplierCircuit(N::BinaryInteger, a::BinaryInteger) (length(N)==length(a)) || error(""binary integer a and N size mismatch."") L = length(a) n = L-1 total_circuit = QCircuit() # qft = shift(_QFT(L), n+3) # append!(total_circuit, qft) mv = move_site(n-2, 0) for i in 0:(n-1) apow = modular_multiply(a, 2^i, N) madder = LNNModAdderCircuit(N, apow) append!(total_circuit, shift(madder, n-2) ) append!(total_circuit, mv) end # append!(total_circuit, qft') return total_circuit end function _cswap() circuit = QCircuit() push!(circuit, gate((2,1), CNOT)) push!(circuit, gate((1,2), CONTROL_PLUS)) push!(circuit, gate((0,1), CNOT)) push!(circuit, gate((1,2), CONTROL_MINUS)) push!(circuit, gate((0,1), SWAP * CNOT)) push!(circuit, gate((1,2), SWAP * CONTROL_PLUS)) push!(circuit, gate((1,0), CNOT)) return circuit end function mesh(n::Int) circuit = QCircuit() for i in 0:(n-2) append!(circuit, move_site(n+i, 2*i+1)) end return circuit end """""" 2n+1 qubits c a[0] a[1] ... a[n-1] b[0] b[1] ... b[n-1] """""" function control_swap(n::Int) total_circuit = QCircuit() append!(total_circuit, shift(mesh(n), 1) ) for i in 0:2:(2*n-1) append!(total_circuit, shift(_cswap(), i) ) end append!(total_circuit, mesh(n)') return total_circuit end """""" this circuit contains 2n+4 qubits, where n+1 = len(a) = len(N) x[0] x[1] ... x[n-2] MS x[n-1] ki kx b[0] n+3 b[1] ... b[n] """""" function LNNModUCircuit(N::BinaryInteger, a::BinaryInteger, ra::BinaryInteger) ((length(N)==length(a)) && (length(N)==length(ra))) || error(""binary integer a, ar and N size mismatch."") L = length(a) n = L-1 total_circuit = QCircuit() append!(total_circuit, LNNCModMultiplierCircuit(N, a)) append!(total_circuit, shift(_QFT(L)', n+3) ) append!(total_circuit, move_site(n-1, 0)) append!(total_circuit, move_site(n+2, 1)) append!(total_circuit, move_site(n+2, 2)) append!(total_circuit, shift(move_site(0, n), n+3)) # controled swap append!(total_circuit, shift(control_swap(n), 2) ) append!(total_circuit, move_site(1, n+1)) append!(total_circuit, move_site(0, n-1)) append!(total_circuit, move_site(2*n+2, n+1)) append!(total_circuit, move_site(2*n+3, n+3)) append!(total_circuit, shift(_QFT(L), n+3)) append!(total_circuit, LNNCModMultiplierCircuit(N, ra)') return total_circuit end """""" compute fa,N (x) = a^x mod N 2n+3+m qubits alined as follows f[0] f[1] ... f[m-1] x[0] m x[1] ... x[n-2] MS x[n-1] m+n --ki-- kx m+n+1 b[0] m+n+2 b[1] ... b[n] @input @x m bits qnumber @b result: n bits qnumber, initialized to be |0> @output @b->(a^x)%N """""" function LNNModExponentiatorCircuit(N::BinaryInteger, a::BinaryInteger, m::Int) (length(N)==length(a)) || error(""binary integer a and N size mismatch."") total_circuit = QCircuit() L = length(N) n = L-1 ra = modular_inverse(a, N) qft_circuit = shift(_QFT(L), m+n+2) append!(total_circuit, qft_circuit) for i in (m-1):-1:0 mv = move_site(i, m+n) append!(total_circuit, mv) # central block operations append!(total_circuit, shift(LNNModUCircuit(N, a, ra), m-1)) append!(total_circuit, mv') a = modular_multiply(a, a, N) ra = modular_multiply(ra, ra, N) end append!(total_circuit, qft_circuit') return total_circuit end ","Julia" "Conjugate","guochu/VQC.jl","src/utility/shor/util.jl",".jl","1416","61","include(""binaryinteger.jl"") """""" circuit to move i to j """""" function move_site(i::Int, j::Int) circuit = QCircuit() (i==j) && return circuit if i < j for k = i:(j-1) # push!(circuit, ((k, k+1), SWAP)) push!(circuit, SWAPGate(k, k+1)) end else for k = i:-1:(j+1) # push!(circuit, ((k, k-1), SWAP)) push!(circuit, SWAPGate(k, k-1)) end end return circuit end # function compute_phase(a::BinaryInteger, j::Int) # s = 1 # n = length(a) # for k in 1:(j+1) # aj = a[n-(j+1-k)] # s = s*exp(aj*pi*im/2^(k-1)) # end # return s # end # rotationA(a::BinaryInteger, j::Int) = [1 0; 0 compute_phase(a, j)] function compute_phase(a::BinaryInteger, j::Int) s = 0. n = length(a) for k in 1:(j+1) aj = a[n-(j+1-k)] s += aj / 2^(k-1) end return s * pi end function control_swap_block(c::Int, n::Int, i::Int, inci::Int, j::Int, incj::Int) swap_i_j = QCircuit() # c_cnot = _row_kron(UP, eye(4)) + _row_kron(DOWN, CNOT) (i == j) && error(""position not allowed."") for k in 0:(n-1) # push!(swap_i_j, gate((j+k*incj, i+k*inci), CNOT)) push!(swap_i_j, CNOTGate(j+k*incj, i+k*inci)) # push!(swap_i_j, gate((c, i+k*inci, j+k*incj), c_cnot)) push!(swap_i_j, TOFFOLIGate(c, i+k*inci, j+k*incj)) # push!(swap_i_j, gate((j+k*incj, i+k*inci), CNOT)) push!(swap_i_j, CNOTGate(j+k*incj, i+k*inci)) end return swap_i_j end _QFT(L::Int) = shift(QFT(L), -1) ","Julia" "Conjugate","guochu/VQC.jl","src/utility/shor/Beauregard.jl",".jl","5369","259"," # using 2n+3 qubits # zero based circuit # QFTAdderCircuit(a::BinaryInteger) = QCircuit([gate(i, rotationA(a, i)) for i in 0:(length(a)-1)]) QFTAdderCircuit(a::BinaryInteger) = QCircuit([PHASEGate(i, compute_phase(a, i)) for i in 0:(length(a)-1)]) """""" n = length(a) n+1 qubits b[0] b[1] ... b[n-1] c control qubit """""" # QFTCAdderCircuit(c::Int, a::BinaryInteger) = QCircuit([gate((c, i), CONTROL(rotationA(a, i))) for i in 0:(length(a)-1)]) # QFTCAdderCircuit(c::Int, a::BinaryInteger) = QCircuit( # [CONTROLGate((c, i), rotationA(a, i)) for i in 0:(length(a)-1)]) QFTCAdderCircuit(c::Int, a::BinaryInteger) = QCircuit( [CPHASEGate((c, i), compute_phase(a, i)) for i in 0:(length(a)-1)]) """""" n = length(a) n+2 qubits b[0] b[1] ... b[n-1] c2 control qubit 2 c1 control qubit 1 """""" # QFTCCAdderCircuit(c1::Int, c2::Int, a::BinaryInteger) = QCircuit( # [gate((c1, c2, i), CONTROLCONTROL(rotationA(a, i))) for i in 0:(length(a)-1)]) QFTCCAdderCircuit(c1::Int, c2::Int, a::BinaryInteger) = QCircuit( [CCPHASEGate((c1, c2, i), compute_phase(a, i)) for i in 0:(length(a)-1)]) """""" this circuit contains n+4 qubits, where n+1 = length(a) = length(N) t qubit in |0> out |0> b[0] addition (most significant) qubit in |0> out |0> b[1] b[2] ... b[n] c2 c1 """""" function QFTCCModAdderCircuit(N::BinaryInteger, a::BinaryInteger) (length(N)==length(a)) || error(""binary integer a and N size mismatch."") L = length(a) n = L-1 total_circuit = QCircuit() cc_adder = shift(QFTCCAdderCircuit(L+1, L, a), 1) c_adder = shift(QFTCAdderCircuit(-1, N), 1) adder = shift(QFTAdderCircuit(N), 1) qft = shift(_QFT(L), 1) append!(total_circuit, cc_adder) append!(total_circuit, adder') append!(total_circuit, qft') # push!(total_circuit, gate((1, 0), CNOT)) push!(total_circuit, CNOTGate(1, 0)) append!(total_circuit, qft) append!(total_circuit, c_adder) append!(total_circuit, cc_adder') append!(total_circuit, qft') # push!(total_circuit, gate(1, X)) push!(total_circuit, XGate(1)) # push!(total_circuit, gate((1, 0), CNOT)) push!(total_circuit, CNOTGate(1, 0)) # push!(total_circuit, gate(1, X)) push!(total_circuit, XGate(1)) append!(total_circuit, qft) append!(total_circuit, cc_adder) return total_circuit end """""" this circuit contains 2n+3 qubits, where n+1 = length(a) = length(N) t qubit in |0> out |0> b[0] addition (most significant) qubit in |0> out |0> b[1] b[2] ... b[n] x[0] x[1] ... x[n-1] c control qubit """""" function QFTCModMultiplierCircuit(N::BinaryInteger, a::BinaryInteger) (length(N)==length(a)) || error(""binary integer a and N size mismatch."") L = length(a) n = L-1 total_circuit = QCircuit() mv1 = move_site(2*n+2, n+3) for i in 0:(n-1) mv2 = shift(move_site(n-1-i, 0), n+2) append!(total_circuit, mv2) append!(total_circuit, mv1) apow = modular_multiply(a, 2^i, N) madder = QFTCCModAdderCircuit(N, apow) append!(total_circuit, madder) append!(total_circuit, mv1') append!(total_circuit, mv2') end return total_circuit end """""" this circuit contains 2n+3 qubits, where n+1 = length(a) = length(N) t qubit in |0> out |0> b[0] addition (most significant) qubit in |0> out |0> b[1] b[2] ... b[n] x[0] x[1] ... x[n-1] c control qubit """""" function QFTModUCircuit(N::BinaryInteger, a::BinaryInteger, ra::BinaryInteger) L = length(a) n = L-1 qft = shift(_QFT(L), 1) c_swap = control_swap_block(2*n+2, n, 2, 1, n+2, 1) total_circuit = QCircuit() mult_circuit = QFTCModMultiplierCircuit(N, a) append!(total_circuit, mult_circuit) append!(total_circuit, qft') append!(total_circuit, c_swap) append!(total_circuit, qft) rmult_circuit = QFTCModMultiplierCircuit(N, ra) append!(total_circuit, rmult_circuit') return total_circuit end """""" compute fa,N (x) = a^x mod N 2n+2+m qubits alined as follows t qubit in |0> out |0> b[0] addition qubit int |0> out |0> b[1] ... b[n] t[0] t[1] ... t[n-1] x[0] x[1] ... x[m-1] @input @t n bits temporary qnumber, initialized to be |1> @x m bits qnumber @b result: n bits qnumber, initialized to be |0> @output @b->(a^x)%N """""" function QFTCModExponentiatorCircuit(N::BinaryInteger, a::BinaryInteger, m::Int) (length(N)==length(a)) || error(""binary integer a and N size mismatch."") L = length(N) n = L-1 ra = modular_inverse(a, N) total_circuit = QCircuit() c_swap = control_swap_block(2*n+2, n, 2, 1, n+2, 1) qft = shift(_QFT(L), 1) append!(total_circuit, qft) for i in (m-1):-1:0 mv = shift(move_site(i, 0), 2*n+2) append!(total_circuit, mv) # central block operations mult_circuit = QFTCModMultiplierCircuit(N, a) append!(total_circuit, mult_circuit) append!(total_circuit, qft') append!(total_circuit, c_swap) append!(total_circuit, qft) rmult_circuit = QFTCModMultiplierCircuit(N, ra) append!(total_circuit, rmult_circuit') append!(total_circuit, mv') a = modular_multiply(a, a, N) ra = modular_multiply(ra, ra, N) end append!(total_circuit, qft') return total_circuit end ","Julia" "Conjugate","guochu/VQC.jl","src/utility/shor/binaryinteger.jl",".jl","1965","64"," struct BinaryInteger value::Int svalue::Vector{Int} end get_value(x::BinaryInteger) = x.value get_svalue(x::BinaryInteger) = x.svalue num_bits(x::BinaryInteger) = length(get_svalue(x)) Base.length(x::BinaryInteger) = length(get_svalue(x)) Base.getindex(x::BinaryInteger, i::Int) = getindex(get_svalue(x), i) Base.iterate(x::BinaryInteger) = iterate(get_svalue(x)) Base.iterate(x::BinaryInteger, state) = iterate(get_svalue(x), state) Base.IndexStyle(::Type{<:BinaryInteger}) = IndexLinear() Base.firstindex(x::BinaryInteger) = firstindex(get_svalue(x)) Base.lastindex(x::BinaryInteger) = lastindex(get_svalue(x)) function BinaryInteger(v::Int, Nbits::Int) svalue = digits(v, base=2, pad=Nbits) (length(svalue) == Nbits) || error(""$Nbits is not enough for integer $v."") return BinaryInteger(v, reverse(svalue) ) end function modular_inverse(a::BinaryInteger, N::BinaryInteger) (num_bits(a) == num_bits(N)) || error(""nbits mismatch."") r = invmod(get_value(a), get_value(N)) return BinaryInteger(r, num_bits(a)) end function modular_multiply(a::Integer, b::Integer, N::BinaryInteger) r = (a * b) % get_value(N) return BinaryInteger(r, num_bits(N)) end function modular_multiply(a::BinaryInteger, b::Integer, N::BinaryInteger) (num_bits(a) == num_bits(N)) || error(""nbits mismatch."") return modular_multiply(get_value(a), b, N) end function modular_multiply(a::BinaryInteger, b::BinaryInteger, N::BinaryInteger) ((num_bits(a) == num_bits(b)) && (num_bits(a) == num_bits(N))) || error(""nbits mismatch."") return modular_multiply(get_value(a), get_value(b), N) end function modular_pow(bs::Integer, exponent::Integer, modulus::Integer) (modulus==1) && return 0 if exponent < 0 bs = modular_inverse(bs, modulus) exponent = -exponent end result=1 bs = bs % modulus while exponent > 0 if (exponent % 2 == 1) result = (result*bs) % modulus end exponent = exponent >> 1 bs = (bs*bs) % modulus end return result end ","Julia" "Conjugate","guochu/VQC.jl","src/utility/shor/orderfinding.jl",".jl","4379","151"," """""" n = len(a)-1 = len(N)-1 4*n+2 qubits is needed """""" function order_finding_qft_circuit(a::BinaryInteger, N::BinaryInteger; verbosity::Int=1) ai = get_value(a) Ni = get_value(N) (ai==1) && error(""the input a can not be 1."") (Ni==1) && error(""the input N can not be 1."") (gcd(ai, Ni)==1) || error(""a and N are not co-prime to each other."") # nmax = length(a) # precision = 2**(-2*nmax-1) n = length(a) L = n+1 a = BinaryInteger(get_value(a), L) N = BinaryInteger(get_value(N), L) (verbosity >= 3) && println(""n=$n, total number of qubits $(4*n+2)."") circuit = QCircuit() push!(circuit, gate(2*n+1, X)) for i in (2*n+2):(4*n+1) push!(circuit, gate(i, H)) end # circuit = shift(circuit, 2*n+2) append!(circuit, QFTCModExponentiatorCircuit(N, a, 2*n)) append!(circuit, shift(_QFT(2*n), 2*n+2)') return circuit # check N end function order_finding_by_qft(::Type{T}, a::Int, N::Int; verbosity::Int=1) where {T<:Number} L = max(length(digits(a, base=2)), length(digits(N, base=2))) state = StateVector(T, 4*L+2) a = BinaryInteger(a, L) N = BinaryInteger(N, L) circuit = shift(order_finding_qft_circuit(a, N, verbosity=verbosity), 1) # println(""max min position $(max_site(circuit.data)), $(min_site(circuit.data))."") # circuit = fuse_gate(circuit) apply_circuit!(circuit, state) r = Int[] for i in 0:(2*L-1) observer = QMeasure(2*L+i+3) istate, probability = apply_circuit!(observer, state) push!(r, istate) end # return sum([(r[2 * L - i]*1. / (1 << (i + 1))) for i in 0:(2 * L-1)]) return to_digits(r) end """""" see reference ""Implementation of Shor’s Algorithm on a Linear Nearest Neighbour Qubit Array"" n = len(a)-1 = len(N)-1 4*n+3 qubits is needed f[0] f[1] ... f[2n-1] x[0] 2n x[1] ... x[n-2] MS x[n-1] 3n kx b[0] b[1] ... b[n] """""" function order_finding_lnn_circuit(a::BinaryInteger, N::BinaryInteger; verbosity::Int=1) ai = get_value(a) Ni = get_value(N) (ai==1) && error(""the input a can not be 1."") (Ni==1) && error(""the input N can not be 1."") (gcd(ai, Ni)==1) || error(""a and N are not co-prime to each other."") # nmax = length(a) # precision = 2**(-2*nmax-1) n = length(a) L = n+1 a = BinaryInteger(get_value(a), L) N = BinaryInteger(get_value(N), L) (verbosity >= 3) && println(""n=$n, total number of qubits $(4*n+3)."") circuit = QCircuit() push!(circuit, gate(3*n, X)) for i in 0:(2*n-1) push!(circuit, gate(i, H)) end append!(circuit, LNNModExponentiatorCircuit(N, a, 2*n)) append!(circuit, _QFT(2*n)') append!(circuit, move_site(3*n, 3*n-1)) return circuit end function order_finding_by_lnn(::Type{T}, a::Int, N::Int; verbosity::Int=1) where {T<:Number} L = max(length(digits(a, base=2)), length(digits(N, base=2))) state = StateVector(T, 4*L+3) a = BinaryInteger(a, L) N = BinaryInteger(N, L) circuit = shift(order_finding_lnn_circuit(a, N, verbosity=verbosity), 1) # println(""max min position $(max_site(circuit.data)), $(min_site(circuit.data))."") # circuit = fuse_gate(circuit) apply_circuit!(circuit, state) # # testing # println(""testing...."") # for i in (3*L+1):(4*L+3) # observer = QMeasure(i) # istate, probability = apply!(observer, state) # println(""get $istate with probability $probability at $i-th qubit."") # end r = Int[] for i in 0:(2*L-1) observer = QMeasure(i+1) istate, probability = apply_circuit!(observer, state) push!(r, istate) end # return sum([(r[2 * L - i]*1. / (1 << (i + 1))) for i in 0:(2 * L-1)]) return to_digits(r) end function order_finding(::Type{T}, a::Int, N::Int; less_qubits::Bool=true, algorithm::Symbol=:lnn, verbosity::Int=1) where {T<:Number} if less_qubits return order_finding_scq(T, a, N; algorithm=algorithm, verbosity=verbosity) else if algorithm == :lnn return order_finding_by_lnn(T, a, N; verbosity=verbosity) elseif algorithm == :qft return order_finding_by_qft(T, a, N; verbosity=verbosity) else error(""algorithm $algorithm not implemented."") end end end order_finding(a::Int, N::Int) = order_finding(ComplexF64, a, N) ","Julia" "Conjugate","guochu/VQC.jl","src/utility/shor/orderfinding_sqc.jl",".jl","5795","224","# sqc : single qubit control to use less qubits function to_digits(s::Vector) r = 0. for i in 0:(length(s)-1) r = r + s[i+1]*2.0^(-i-1) end return r end apply_circuit!(gt, state) = apply!(gt, state) """""" see reference using the one control qubit trick this circuit contains 2n+3 qubits, where n+1 = len(a) = len(N) t qubit in |0> out |0> b[0] addition (most significant) qubit in |0> out |0> b[1] b[2] ... b[n] x[0] x[1] ... x[n-1] c control qubit """""" function order_finding_by_qft_impl(a::BinaryInteger, N::BinaryInteger, state; verbosity::Int=1) (length(N)==length(a)) || error(""binary integer a and N size mismatch."") ai = get_value(a) Ni = get_value(N) (ai==1) && error(""the input a can not be 1."") (Ni==1) && error(""the input N can not be 1."") (gcd(ai, Ni)==1) || error(""a and N are not co-prime to each other."") # nmax = length(a) # precision = 2**(-2*nmax-1) n = length(a) L = n+1 a = BinaryInteger(get_value(a), L) N = BinaryInteger(get_value(N), L) (verbosity >= 3) && println(""n=$n, total number of qubits $(2*n+3)."") control_site = 2*n+3 observer = QMeasure(control_site, auto_reset=true) ra = modular_inverse(a, N) qft_circuit = shift(_QFT(L), 2) apply_circuit!(qft_circuit, state) Hgate = gate(control_site, H) apply_circuit!(Hgate, state) astore = [] rastore = [] for i in 1:(2*n) push!(astore, a) push!(rastore, ra) a = modular_multiply(a, a, N) ra = modular_multiply(ra, ra, N) end r = [] # print('total number of measurements %s'%(2*n)) for i in 0:(2*n-1) apply_circuit!(Hgate, state) circuit = shift(QFTModUCircuit(N, astore[2*n-i], rastore[2*n-i]), 1) # println(""max min site $(max_site(circuit.data)), $(min_site(circuit.data))."") # println(""number of gates $(length(circuit))."") # circuit = fuse_gate(circuit) # println(""number of gates after gate fusion $(length(circuit))."") apply_circuit!(circuit, state) # apply rorate rot = gate(control_site, [1. 0.; 0. exp(-pi*im*to_digits(reverse(r)))]) apply_circuit!(rot, state) apply_circuit!(Hgate, state) istate, probability = apply_circuit!(observer, state) push!(r, istate) (verbosity >= 2) && println(""measurement outcome at $i-th step is $istate."") end y = sum([(r[2 * n - i]*1. / (1 << (i + 1))) for i in 0:(2 * n-1)]) return y # numerator, d = continuous_fraction(y, Ni-1) # (verbosity >= 1) && println(""numerator is $numerator, denominator is $d."") # # (modular_pow(ai, d, Ni)==1) && return d # (verbosity >= 2) && println(""order finding failed."") # # println(""fraction is $y."") # return -1 end function scq_order_finding_by_qft(::Type{T}, a::Int, N::Int; verbosity::Int=1) where {T<:Number} L = max(length(digits(a, base=2)), length(digits(N, base=2))) state = StateVector(T, 2*L+3) apply_circuit!(gate(2*L+2, X), state) return order_finding_by_qft_impl(BinaryInteger(a, L), BinaryInteger(N, L), state; verbosity=verbosity) end """""" see reference using the one control qubit trick ""Implementation of Shor’s Algorithm on a Linear Nearest Neighbour Qubit Array"" n = len(a)-1 = len(N)-1 2*n+4 qubits is needed x[0] x[1] ... x[n-2] MS x[n-1] n ki kx b[0] b[1] ... b[n] """""" function order_finding_by_lnn_impl(a::BinaryInteger, N::BinaryInteger, state; verbosity::Int=1) # assert(driver in ['lnn']) ai = get_value(a) Ni = get_value(N) (ai==1) && error(""the input a can not be 1."") (Ni==1) && error(""the input N can not be 1."") (gcd(ai, Ni)==1) || error(""a and N are not co-prime to each other."") # precision = 2**(-2*nmax-1) n = length(a) L = n+1 a = BinaryInteger(get_value(a), L) N = BinaryInteger(get_value(N), L) (verbosity >= 3) && println(""n=$n, total number of qubits $(2*n+4)."") observer = QMeasure(n+2, auto_reset=true) ra = modular_inverse(a, N) qft_circuit = shift(_QFT(L), n+4) apply_circuit!(qft_circuit, state) Hgate = gate(n+2, H) apply_circuit!(Hgate, state) astore = [] rastore = [] for i in 1:2*n push!(astore, a) push!(rastore, ra) a = modular_multiply(a, a, N) ra = modular_multiply(ra, ra, N) end r = [] for i in 0:(2*n-1) apply_circuit!(Hgate, state) circuit = shift(LNNModUCircuit(N, astore[2*n-i], rastore[2*n-i]), 1) # println(""max min site $(max_site(circuit.data)), $(min_site(circuit.data))."") # println(""number of gates $(length(circuit))."") # circuit = fuse_gate(circuit) # println(""number of gates after gate fusion $(length(circuit))."") apply_circuit!(circuit, state) # apply rorate rot = gate(n+2, [1. 0.; 0. exp(-pi*im*to_digits(reverse(r)))]) apply_circuit!(rot, state) apply_circuit!(Hgate, state) istate, probability = apply_circuit!(observer, state) push!(r, istate) (verbosity >= 2) && println(""measurement outcome at $i-th step is $istate."") end y = sum([(r[2 * n - i]*1. / (1 << (i + 1))) for i in 0:(2 * n-1)]) return y # println(""fraction is $y."") # return -1 end function scq_order_finding_by_lnn(::Type{T}, a::Int, N::Int; verbosity::Int=1) where {T<:Number} L = max(length(digits(a, base=2)), length(digits(N, base=2))) state = StateVector(T, 2*L+4) apply_circuit!(gate(L+1, X), state) return order_finding_by_lnn_impl(BinaryInteger(a, L), BinaryInteger(N, L), state; verbosity=verbosity) end """""" quantum order finding algorithm using single control qubits technique. """""" function order_finding_scq(::Type{T}, a::Int, N::Int; algorithm::Symbol=:lnn, verbosity::Int=1) where {T<:Number} if algorithm == :lnn return scq_order_finding_by_lnn(T, a, N; verbosity=verbosity) elseif algorithm == :qft return scq_order_finding_by_qft(T, a, N; verbosity=verbosity) else error(""algorithm $algorithm not implemented."") end end ","Julia" "Conjugate","guochu/VQC.jl","src/auxiliary/tensorops.jl",".jl","1375","53"," function swap!(qstate::AbstractVector, i::Int, j::Int) (i == j) && return if i < j fsize = 2^(i-1) msize = 2^(j-i-1) bsize = div(length(qstate), (fsize*4*msize)) s = reshape(qstate, (fsize, 2, msize, 2, bsize)) # tmp = Tensor{T}(undef, fsize, msize, bsize) tmp = s[:, 1, :, 2, :] s[:, 1, :, 2, :] = s[:, 2, :, 1, :] s[:, 2, :, 1, :] = tmp else swap!(qstate, j, i) end end function _entropy(v::AbstractVector{<:Real}) a = [(abs(item) <= 1.0e-12) ? 0. : item for item in v] a = [item for item in a if (item != 0.)] s = sum(a) a ./= s return -dot(a, log2.(a)) end function entropy(v::AbstractArray{T, 1}) where {T <: Real} a = _check_and_filter(v) return -dot(a, log2.(a)) end function renyi_entropy(v::AbstractArray{T, 1}; α::Real=1) where T α = convert(T, α) if α==one(α) return entropy(v) else a = _check_and_filter(v) a = v.^(α) return (1/(1-α)) * log2(sum(a)) end end function _check_and_filter(v::AbstractArray{<:Real}; tol::Real=1.0e-12) (abs(sum(v) - 1) <= tol) || throw(ArgumentError(""sum of singular values not equal to 1"")) oo = zero(eltype(v)) tol = convert(eltype(v), tol) for item in v ((item < oo) && (-item > tol)) && throw(ArgumentError(""negative singular values"")) end # return [(abs(item) <= tol) ? oo : item for item in v] return [item for item in v if abs(item) > tol] end","Julia" "Conjugate","guochu/VQC.jl","src/auxiliary/parallel_for.jl",".jl","2144","62","using Base.Threads const MIN_SIZE = 1024 get_size_1(total_itr::Int, n_threads::Int, thread_id::Int) = div(total_itr * thread_id, n_threads) get_size_2(total_itr::Int, n_threads::Int, thread_id::Int) = div(total_itr * (thread_id + 1), n_threads) """""" The inner function f is assumed to be Zero Based """""" function parallel_run(total_itr::Int, n_threads::Int, f::Function, args...) if (total_itr >= MIN_SIZE) && (n_threads > 1) # nave, resi, jobs = partition_jobs(total_itr, n_threads) Threads.@threads for thread_id in 0:(n_threads-1) ist = get_size_1(total_itr, n_threads, thread_id) ifn = get_size_2(total_itr, n_threads, thread_id) - 1 f(ist, ifn, args...) end else f(0, total_itr-1, args...) end end """""" The inner function f is assumed to be Zero Based """""" function parallel_sum(::Type{T}, total_itr::Int, n_threads::Int, f::Function, args...) where {T<:Real} if (total_itr >= MIN_SIZE) && (n_threads > 1) # nave, resi, jobs = partition_jobs(total_itr, n_threads) r = Atomic{T}(0) Threads.@threads for thread_id in 0:(n_threads-1) ist = get_size_1(total_itr, n_threads, thread_id) ifn = get_size_2(total_itr, n_threads, thread_id) - 1 atomic_add!(r, f(ist, ifn, args...)) end return r[] else return f(0, total_itr-1, args...) end end function parallel_sum(::Type{T}, total_itr::Int, n_threads::Int, f::Function, args...) where {T<:Complex} if (total_itr >= MIN_SIZE) && (n_threads > 1) # nave, resi, jobs = partition_jobs(total_itr, n_threads) RT = real(T) rr = Atomic{RT}(0) ri = Atomic{RT}(0) Threads.@threads for thread_id in 0:(n_threads-1) ist = get_size_1(total_itr, n_threads, thread_id) ifn = get_size_2(total_itr, n_threads, thread_id) - 1 tmp = f(ist, ifn, args...) atomic_add!(rr, real(tmp)) atomic_add!(ri, imag(tmp)) end return Complex(rr[], ri[]) else return f(0, total_itr-1, args...) end end ","Julia" "Conjugate","guochu/VQC.jl","src/auxiliary/distance.jl",".jl","168","11"," function _distance2(x, y) sA = real(dot(x, x)) sB = real(dot(y, y)) c = dot(x, y) r = sA+sB-2*real(c) return abs(r) end _distance(x, y) = sqrt(_distance2(x, y)) ","Julia" "Conjugate","guochu/VQC.jl","src/auxiliary/sampling.jl",".jl","313","18"," function discrete_sample(l::Vector{Float64}) isempty(l) && error(""no results."") s = sum(l) L = length(l) l1 = Vector{Float64}(undef, L+1) l1[1] = 0 for i=1:L l1[i+1] = l1[i] + l[i]/s end s = rand(Float64) for i = 1:L if (s >= l1[i] && s < l1[i+1]) return i end end return L end","Julia" "Conjugate","guochu/VQC.jl","src/auxiliary/indexop.jl",".jl","1509","75"," """""" move_selected_index_forward(a, I) move the indexes specified by I to the front of a # Arguments @ a::NTuple{N, Int}: the input tensor. @ I: tuple or vector of integer. """""" function move_selected_index_forward(a::Vector{T}, I) where {T} na = length(a) nI = length(I) b = Vector{T}(undef, na) k1 = 0 k2 = nI for i=1:na s = 0 while s != nI if i == I[s+1] b[s+1] = a[k1+1] k1 += 1 break end s += 1 end if s == nI b[k2+1]=a[k1+1] k1 += 1 k2 += 1 end end return b end function move_selected_index_forward(a::NTuple{N, T}, I) where {N, T} return NTuple{N, T}(move_selected_index_forward([a...], I)) end """""" move_selected_index_backward(a, I) move the indexes specified by I to the back of a # Arguments @ a::NTuple{N, Int}: the input tensor. @ I: tuple or vector of integer. """""" function move_selected_index_backward(a::Vector{T}, I) where {T} na = length(a) nI = length(I) nr = na - nI b = Vector{T}(undef, na) k1 = 0 k2 = 0 for i = 1:na s = 0 while s != nI if i == I[s+1] b[nr+s+1] = a[k1+1] k1 += 1 break end s += 1 end if s == nI b[k2+1] = a[k1+1] k2 += 1 k1 += 1 end end return b end function move_selected_index_backward(a::NTuple{N, T}, I) where {N, T} return NTuple{N, T}(move_selected_index_backward([a...], I)) end ","Julia" "Conjugate","guochu/VQC.jl","src/hamiltonian/util.jl",".jl","1030","44"," _get_mat(x::Tuple{Vector{AbstractMatrix}, Number}) = QuantumCircuits._kron_ops(reverse(x[1])) * x[2] _get_mat(x::QubitsTerm) = QuantumCircuits._kron_ops(reverse(oplist(x))) * coeff(x) function _get_mat(n::Int, x::QuantumCircuits.QOP_DATA_VALUE_TYPE) isempty(x) && error(""bond is empty."") m = zeros(_scalar_type(x), 2^n, 2^n) for item in x tmp = QuantumCircuits._kron_ops(reverse(item[1])) alpha = item[2] @. m += alpha * tmp end return m end function _scalar_type(x::QuantumCircuits.QOP_DATA_VALUE_TYPE) T = Int for (k, coef) in x T = promote_type(T, typeof(coef)) for item in k T = promote_type(T, eltype(item)) end end return T end function LinearAlgebra.ishermitian(x::QubitsTerm) (imag(coeff(x)) ≈ 0.) || return false for item in oplist(x) ishermitian(item) || return false end return true end function LinearAlgebra.ishermitian(x::QubitsOperator) for (k, v) in x.data m = _get_mat(length(k), v) ishermitian(m) || return false end return true end ","Julia" "Conjugate","guochu/VQC.jl","src/hamiltonian/expecs_dm/expecs_dm.jl",".jl","585","28"," include(""expec_dm_serial.jl"") include(""apply_qterms_dm.jl"") function expectation(m::QubitsTerm, state::DensityMatrix) isempty(m) && return tr(state) if length(positions(m)) <= 3 return expectation_value_serial(Tuple(positions(m)), _get_mat(m), storage(state)) else return tr(m * state) end end function expectation(m::QubitsOperator, state::DensityMatrix) if _largest_nterm(m) <= 3 r = zero(eltype(state)) for (k, v) in m.data r += expectation_value_serial(k, _get_mat(length(k), v), storage(state)) end return r else return tr(m * state) end end ","Julia" "Conjugate","guochu/VQC.jl","src/hamiltonian/expecs_dm/apply_qterms_dm.jl",".jl","713","34"," # apply hamiltonian term on density matrix function (m::QubitsTerm)(vr::DensityMatrix) v = vr.data vout = similar(v) _apply_qterm_util!(m, v, vout) return DensityMatrix(vout, nqubits(vr)) end function (m::QubitsOperator)(vr::DensityMatrix) v = vr.data vout = zeros(eltype(v), length(v)) if _largest_nterm(m) <= LARGEST_SUPPORTED_NTERMS _apply_util!(m, v, vout) else workspace = similar(v) for (k, dd) in m.data for item in dd _apply_qterm_util!(QubitsTerm(k, item[1], item[2]), v, workspace) vout .+= workspace end end end return DensityMatrix(vout, nqubits(vr)) end Base.:*(m::QubitsOperator, v::DensityMatrix) = m(v) Base.:*(m::QubitsTerm, v::DensityMatrix) = m(v) ","Julia" "Conjugate","guochu/VQC.jl","src/hamiltonian/expecs_dm/expec_dm_serial.jl",".jl","7876","182"," @inline get_2_by_2(state::AbstractMatrix, posa::Int, posb::Int) = SMatrix{2,2}(state[posa, posa], state[posb, posa], state[posa, posb], state[posb, posb]) @inline function get_4_by_4(state::AbstractMatrix, pos1::Int, pos2::Int, pos3::Int, pos4::Int) return SMatrix{4,4}(state[pos1, pos1], state[pos2, pos1], state[pos3, pos1], state[pos4, pos1], state[pos1, pos2], state[pos2, pos2], state[pos3, pos2], state[pos4, pos2], state[pos1, pos3], state[pos2, pos3], state[pos3, pos3], state[pos4, pos3], state[pos1, pos4], state[pos2, pos4], state[pos3, pos4], state[pos4, pos4]) end @inline function get_8_by_8(state::AbstractMatrix, pos1::Int, pos2::Int, pos3::Int, pos4::Int, pos5::Int, pos6::Int, pos7::Int, pos8::Int) return SMatrix{8,8}(state[pos1, pos1], state[pos2, pos1], state[pos3, pos1], state[pos4, pos1], state[pos5, pos1], state[pos6, pos1], state[pos7, pos1], state[pos8, pos1], state[pos1, pos2], state[pos2, pos2], state[pos3, pos2], state[pos4, pos2], state[pos5, pos2], state[pos6, pos2], state[pos7, pos2], state[pos8, pos2], state[pos1, pos3], state[pos2, pos3], state[pos3, pos3], state[pos4, pos3], state[pos5, pos3], state[pos6, pos3], state[pos7, pos3], state[pos8, pos3], state[pos1, pos4], state[pos2, pos4], state[pos3, pos4], state[pos4, pos4], state[pos5, pos4], state[pos6, pos4], state[pos7, pos4], state[pos8, pos4], state[pos1, pos5], state[pos2, pos5], state[pos3, pos5], state[pos4, pos5], state[pos5, pos5], state[pos6, pos5], state[pos7, pos5], state[pos8, pos5], state[pos1, pos6], state[pos2, pos6], state[pos3, pos6], state[pos4, pos6], state[pos5, pos6], state[pos6, pos6], state[pos7, pos6], state[pos8, pos6], state[pos1, pos7], state[pos2, pos7], state[pos3, pos7], state[pos4, pos7], state[pos5, pos7], state[pos6, pos7], state[pos7, pos7], state[pos8, pos7], state[pos1, pos8], state[pos2, pos8], state[pos3, pos8], state[pos4, pos8], state[pos5, pos8], state[pos6, pos8], state[pos7, pos8], state[pos8, pos8]) end function _expectation_value_util(pos::Int, m::AbstractMatrix, state::AbstractMatrix) (size(m, 1) == size(m, 2)) || error(""observable must be a square matrix."") (size(m, 1) == 2) || error(""input must be a 2 by 2 matrix."") sj = 2 s1 = 2^(pos-1) s2 = s1 * sj L = size(state, 1) r = zero(eltype(state)) for i in 0:s2:(L-1) for j in 0:(s1-1) pos_start = i + j + 1 v = get_2_by_2(state, pos_start, pos_start + s1) @fastmath r += tr(m * v) end end return r end # function _expectation_value_util(pos::Int, m::AbstractMatrix, state::AbstractMatrix, state_c::AbstractMatrix) # (size(m, 1) == size(m, 2)) || error(""observable must be a square matrix."") # (size(m, 1) == 2) || error(""input must be a 2 by 2 matrix."") # sj = 2 # s1 = 2^(pos-1) # s2 = s1 * sj # L = size(state, 1) # r = zero(eltype(state)) # for i in 0:s2:(L-1) # for j in 0:(s1-1) # pos_start = i + j + 1 # pos_b = pos_start + s1 # v = get_2_by_2(state, pos_start, pos_b) # v_c = get_2_by_2(state_c, pos_start, pos_b) # @fastmath r += dot(v_c, m, v) # end # end # return r # end function _expectation_value_util(key::Tuple{Int, Int}, m::AbstractMatrix, v::AbstractMatrix) (size(m, 1) == size(m, 2)) || error(""observable must be a square matrix."") (size(m, 1) == 4) || error(""input must be a 4 by 4 matrix."") L = size(v, 1) q1, q2 = key pos1, pos2 = 2^(q1-1), 2^(q2-1) stride1, stride2 = 2 * pos1, 2 * pos2 r = zero(eltype(v)) for i in 0:stride2:(L-1) for j in 0:stride1:(pos2-1) @inbounds for k in 0:(pos1-1) l = i + j + k + 1 vi = get_4_by_4(v, l, l + pos1, l + pos2, l + pos1 + pos2) @fastmath r += tr(m * vi) end end end return r end # function _expectation_value_util(key::Tuple{Int, Int}, m::AbstractMatrix, v::AbstractMatrix, v_c::AbstractMatrix) # (size(m, 1) == size(m, 2)) || error(""observable must be a square matrix."") # (size(m, 1) == 4) || error(""input must be a 4 by 4 matrix."") # L = size(v, 1) # q1, q2 = key # pos1, pos2 = 2^(q1-1), 2^(q2-1) # stride1, stride2 = 2 * pos1, 2 * pos2 # r = zero(eltype(v)) # for i in 0:stride2:(L-1) # for j in 0:stride1:(pos2-1) # @inbounds for k in 0:(pos1-1) # l = i + j + k + 1 # vi = get_4_by_4(v, l, l + pos1, l + pos2, l + pos1 + pos2) # vi_c = get_4_by_4(v_c, l, l + pos1, l + pos2, l + pos1 + pos2) # @fastmath r += dot(vi_c, m, vi) # end # end # end # return r # end function _expectation_value_util(key::Tuple{Int, Int, Int}, m::AbstractMatrix, v::AbstractMatrix) L = size(v, 1) q1, q2, q3 = key pos1, pos2, pos3 = 2^(q1-1), 2^(q2-1), 2^(q3-1) stride1, stride2, stride3 = 2 * pos1, 2 * pos2, 2 * pos3 r = zero(eltype(v)) for h in 0:stride3:(L-1) for i in 0:stride2:(pos3-1) for j in 0:stride1:(pos2-1) @inbounds for k in 0:(pos1-1) l000 = h + i + j + k + 1 l100 = l000 + pos1 l010 = l000 + pos2 l110 = l010 + pos1 l001 = l000 + pos3 l101 = l001 + pos1 l011 = l001 + pos2 l111 = l011 + pos1 vi = get_8_by_8(v, l000, l100, l010, l110, l001, l101, l011, l111) @fastmath r += tr(m * vi) end end end end return r end # function _expectation_value_util(key::Tuple{Int, Int, Int}, m::AbstractMatrix, v::AbstractMatrix, v_c::AbstractMatrix) # L = size(v, 1) # q1, q2, q3 = key # pos1, pos2, pos3 = 2^(q1-1), 2^(q2-1), 2^(q3-1) # stride1, stride2, stride3 = 2 * pos1, 2 * pos2, 2 * pos3 # r = zero(eltype(v)) # for h in 0:stride3:(L-1) # for i in 0:stride2:(pos3-1) # for j in 0:stride1:(pos2-1) # @inbounds for k in 0:(pos1-1) # l000 = h + i + j + k + 1 # l100 = l000 + pos1 # l010 = l000 + pos2 # l110 = l010 + pos1 # l001 = l000 + pos3 # l101 = l001 + pos1 # l011 = l001 + pos2 # l111 = l011 + pos1 # vi = get_8_by_8(v, l000, l100, l010, l110, l001, l101, l011, l111) # vi_c = get_8_by_8(v_c, l000, l100, l010, l110, l001, l101, l011, l111) # @fastmath r += dot(vi_c, m, vi) # end # end # end # end # return r # end # expectation_value_serial(pos::Int, m::AbstractMatrix, state::AbstractMatrix, state_c::AbstractMatrix) = _expectation_value_util( # pos, SMatrix{2,2, eltype(state)}(m), state, state_c) expectation_value_serial(pos::Int, m::AbstractMatrix, state::AbstractMatrix) = _expectation_value_util( pos, SMatrix{2,2, eltype(state)}(m), state) # expectation_value_serial(pos::Tuple{Int}, m::AbstractMatrix, state::AbstractMatrix, state_c::AbstractMatrix) = expectation_value_serial( # pos[1], m, state, state_c) expectation_value_serial(pos::Tuple{Int}, m::AbstractMatrix, state::AbstractMatrix) = expectation_value_serial( pos[1], m, state) # expectation_value_serial(pos::Tuple{Int, Int}, m::AbstractMatrix, state::AbstractMatrix, state_c::AbstractMatrix) = _expectation_value_util( # pos, SMatrix{4,4, eltype(state)}(m), state, state_c) expectation_value_serial(pos::Tuple{Int, Int}, m::AbstractMatrix, state::AbstractMatrix) = _expectation_value_util( pos, SMatrix{4,4, eltype(state)}(m), state) # expectation_value_serial(pos::Tuple{Int, Int, Int}, m::AbstractMatrix, state::AbstractMatrix, state_c::AbstractMatrix) = _expectation_value_util( # pos, m, state, state_c) expectation_value_serial(pos::Tuple{Int, Int, Int}, m::AbstractMatrix, state::AbstractMatrix) = _expectation_value_util( pos, SMatrix{8,8, eltype(state)}(m), state) ","Julia" "Conjugate","guochu/VQC.jl","src/hamiltonian/expecs/expec_high_qubit_terms.jl",".jl","4926","127"," function _expectation_value_fourbody_util(key::Tuple{Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2, q3, q4 = key pos1, pos2, pos3, pos4 = 1 << (q1-1), 1 << (q2-1), 1 << (q3-1), 1 << (q4-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(pos3 - 1, 2 * pos2 - 1) mask3 = xor(pos4 - 1, 2 * pos3 - 1) mask4 = xor(L - 1, 2 * pos4 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") function f(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, posd::Int, m1::Int, m2::Int, m3::Int, m4::Int, m5::Int, mat::AbstractMatrix, p::AbstractVector) r = zero(eltype(p)) @inbounds for i in ist:ifn l0000 = (16 * i & m5) | (8 * i & m4) | (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 l1000 = l0000 + posa l0100 = l0000 + posb l0010 = l0000 + posc l0001 = l0000 + posd l1100 = l0100 + posa l1010 = l0010 + posa l1001 = l1000 + posd l0110 = l0010 + posb l0101 = l0100 + posd l0011 = l0010 + posd l1110 = l1100 + posc l1101 = l1100 + posd l1011 = l1010 + posd l0111 = l0110 + posd l1111 = l1110 + posd vi = SVector(p[l0000], p[l1000], p[l0100], p[l1100], p[l0010], p[l1010], p[l0110], p[l1110], p[l0001], p[l1001], p[l0101], p[l1101], p[l0011], p[l1011], p[l0111], p[l1111]) @fastmath r += dot(vi, mat, vi) end return r end total_itr = div(L, 16) return parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, pos1, pos2, pos3, pos4, mask0, mask1, mask2, mask3, mask4, U, v) end expectation_value_threaded(key::Tuple{Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) = _expectation_value_fourbody_util( key, SMatrix{16,16, eltype(v)}(U), v) function _expectation_value_fivebody_util(key::Tuple{Int, Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2, q3, q4, q5 = key pos1, pos2, pos3, pos4, pos5 = 1 << (q1-1), 1 << (q2-1), 1 << (q3-1), 1 << (q4-1), 1 << (q5-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(pos3 - 1, 2 * pos2 - 1) mask3 = xor(pos4 - 1, 2 * pos3 - 1) mask4 = xor(pos5 - 1, 2 * pos4 - 1) mask5 = xor(L - 1, 2 * pos5 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") function f(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, posd::Int, pose::Int, m1::Int, m2::Int, m3::Int, m4::Int, m5::Int, m6::Int, mat::AbstractMatrix, p::AbstractVector) r = zero(eltype(p)) @inbounds for i in ist:ifn l00000 = (32 * i & m6) | (16 * i & m5) | (8 * i & m4) | (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 l10000 = l00000 + posa l01000 = l00000 + posb l00100 = l00000 + posc l00010 = l00000 + posd l00001 = l00000 + pose l11000 = l01000 + posa l10100 = l00100 + posa l10010 = l10000 + posd l10001 = l10000 + pose l01100 = l00100 + posb l01010 = l01000 + posd l01001 = l01000 + pose l00110 = l00100 + posd l00101 = l00100 + pose l00011 = l00010 + pose l11100 = l11000 + posc l11010 = l11000 + posd l11001 = l11000 + pose l10110 = l10100 + posd l10101 = l10100 + pose l10011 = l10010 + pose l01110 = l01100 + posd l01101 = l01100 + pose l01011 = l01010 + pose l00111 = l00110 + pose l11110 = l11100 + posd l11101 = l11100 + pose l11011 = l11010 + pose l10111 = l10110 + pose l01111 = l01110 + pose l11111 = l11110 + pose vi = SVector(p[l00000], p[l10000], p[l01000], p[l11000], p[l00100], p[l10100], p[l01100], p[l11100], p[l00010], p[l10010], p[l01010], p[l11010], p[l00110], p[l10110], p[l01110], p[l11110], p[l00001], p[l10001], p[l01001], p[l11001], p[l00101], p[l10101], p[l01101], p[l11101], p[l00011], p[l10011], p[l01011], p[l11011], p[l00111], p[l10111], p[l01111], p[l11111]) @fastmath r += dot(vi, mat, vi) end return r end total_itr = div(L, 32) parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, pos1, pos2, pos3, pos4, pos5, mask0, mask1, mask2, mask3, mask4, mask5, U, v) end expectation_value_threaded(key::Tuple{Int, Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) = _expectation_value_fivebody_util( key, SMatrix{32,32, eltype(v)}(U), v) ","Julia" "Conjugate","guochu/VQC.jl","src/hamiltonian/expecs/expec_serial.jl",".jl","4890","130"," function _expectation_value_util(pos::Int, m::AbstractMatrix, state::AbstractVector) (size(m, 1) == size(m, 2)) || error(""observable must be a square matrix."") (size(m, 1) == 2) || error(""input must be a 2 by 2 matrix."") sj = 2 s1 = 2^(pos-1) s2 = s1 * sj r = zero(eltype(state)) for i in 0:s2:(length(state)-1) for j in 0:(s1-1) pos_start = i + j + 1 v = SVector(state[pos_start], state[pos_start + s1]) @fastmath r += dot(v, m, v) end end return r end function _expectation_value_util(pos::Int, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) (size(m, 1) == size(m, 2)) || error(""observable must be a square matrix."") (size(m, 1) == 2) || error(""input must be a 2 by 2 matrix."") sj = 2 s1 = 2^(pos-1) s2 = s1 * sj r = zero(eltype(state)) for i in 0:s2:(length(state)-1) for j in 0:(s1-1) pos_start = i + j + 1 v = SVector(state[pos_start], state[pos_start + s1]) v_c = SVector(state_c[pos_start], state_c[pos_start + s1]) @fastmath r += dot(v_c, m, v) end end return r end function _expectation_value_util(key::Tuple{Int, Int}, m::AbstractMatrix, v::AbstractVector) (size(m, 1) == size(m, 2)) || error(""observable must be a square matrix."") (size(m, 1) == 4) || error(""input must be a 4 by 4 matrix."") L = length(v) q1, q2 = key pos1, pos2 = 2^(q1-1), 2^(q2-1) stride1, stride2 = 2 * pos1, 2 * pos2 r = zero(eltype(v)) for i in 0:stride2:(L-1) for j in 0:stride1:(pos2-1) @inbounds for k in 0:(pos1-1) l = i + j + k + 1 vi = SVector(v[l], v[l + pos1], v[l + pos2], v[l + pos1 + pos2]) @fastmath r += dot(vi, m, vi) end end end return r end function _expectation_value_util(key::Tuple{Int, Int}, m::AbstractMatrix, v::AbstractVector, v_c::AbstractVector) (size(m, 1) == size(m, 2)) || error(""observable must be a square matrix."") (size(m, 1) == 4) || error(""input must be a 4 by 4 matrix."") L = length(v) q1, q2 = key pos1, pos2 = 2^(q1-1), 2^(q2-1) stride1, stride2 = 2 * pos1, 2 * pos2 r = zero(eltype(v)) for i in 0:stride2:(L-1) for j in 0:stride1:(pos2-1) @inbounds for k in 0:(pos1-1) l = i + j + k + 1 vi = SVector(v[l], v[l + pos1], v[l + pos2], v[l + pos1 + pos2]) vi_c = SVector(v_c[l], v_c[l + pos1], v_c[l + pos2], v_c[l + pos1 + pos2]) @fastmath r += dot(vi_c, m, vi) end end end return r end function _expectation_value_util(key::Tuple{Int, Int, Int}, m::AbstractMatrix, v::AbstractVector, v_c::AbstractVector) L = length(v) q1, q2, q3 = key pos1, pos2, pos3 = 2^(q1-1), 2^(q2-1), 2^(q3-1) stride1, stride2, stride3 = 2 * pos1, 2 * pos2, 2 * pos3 r = zero(eltype(v)) for h in 0:stride3:(L-1) for i in 0:stride2:(pos3-1) for j in 0:stride1:(pos2-1) @inbounds for k in 0:(pos1-1) l000 = h + i + j + k + 1 l100 = l000 + pos1 l010 = l000 + pos2 l110 = l010 + pos1 l001 = l000 + pos3 l101 = l001 + pos1 l011 = l001 + pos2 l111 = l011 + pos1 vi = SVector(v[l000], v[l100], v[l010], v[l110], v[l001], v[l101], v[l011], v[l111]) vi_c = SVector(v_c[l000], v_c[l100], v_c[l010], v_c[l110], v_c[l001], v_c[l101], v_c[l011], v_c[l111]) @fastmath r += dot(vi_c, m, vi) end end end end return r end expectation_value_serial(pos::Int, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) = _expectation_value_util( pos, SMatrix{2,2, eltype(state)}(m), state, state_c) expectation_value_serial(pos::Int, m::AbstractMatrix, state::AbstractVector) = _expectation_value_util( pos, SMatrix{2,2, eltype(state)}(m), state) expectation_value_serial(pos::Tuple{Int}, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) = expectation_value_serial( pos[1], m, state, state_c) expectation_value_serial(pos::Tuple{Int}, m::AbstractMatrix, state::AbstractVector) = expectation_value_serial( pos[1], m, state) expectation_value_serial(pos::Tuple{Int, Int}, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) = _expectation_value_util( pos, SMatrix{4,4, eltype(state)}(m), state, state_c) expectation_value_serial(pos::Tuple{Int, Int}, m::AbstractMatrix, state::AbstractVector) = _expectation_value_util( pos, SMatrix{4,4, eltype(state)}(m), state) expectation_value_serial(pos::Tuple{Int, Int, Int}, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) = _expectation_value_util( pos, m, state, state_c) expectation_value_serial(pos::Tuple{Int, Int, Int}, m::AbstractMatrix, state::AbstractVector) = expectation_value_serial( pos, m, state, state) ","Julia" "Conjugate","guochu/VQC.jl","src/hamiltonian/expecs/expec_threaded.jl",".jl","25008","654"," """""" applys when key > 3, U is the transposed op """""" function _expectation_value_util_H(key::Int, U::AbstractMatrix, v::AbstractVector) L = length(v) sizek = 1 << (key - 1) mask0 = sizek - 1 mask1 = xor(L - 1, 2 * sizek - 1) f(ist::Int, ifn::Int, pos::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (16 * i & m2) | (8 * i & m1) + 1 l1 = l + pos vi = SMatrix{8, 2}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l1], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7]) vi_t = transpose(vi) @fastmath r += dot(vi_t, mat, vi_t) end return r end return parallel_sum(eltype(v), div(L, 16), Threads.nthreads(), f, sizek, mask0, mask1, U, v) end """""" applys when key <= 3, U is the transposed op """""" function _expectation_value_util_L(key::Int, U::AbstractMatrix, v::AbstractVector) L = length(v) f1(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 16 * i + 1 vi = SMatrix{2, 8}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l+9], p[l+10], p[l+11], p[l+12], p[l+13], p[l+14], p[l+15]) @fastmath r += dot(vi, mat, vi) end return r end f2(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 16 * i + 1 vi = SMatrix{2, 8}(p[l], p[l+2], p[l+1], p[l+3], p[l+4], p[l+6], p[l+5], p[l+7], p[l+8], p[l+10], p[l+9], p[l+11], p[l+12], p[l+14], p[l+13], p[l+15]) @fastmath r += dot(vi, mat, vi) end return r end f3(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 16 * i + 1 vi = SMatrix{2, 8}(p[l], p[l+4], p[l+1], p[l+5], p[l+2], p[l+6], p[l+3], p[l+7], p[l+8], p[l+12], p[l+9], p[l+13], p[l+10], p[l+14], p[l+11], p[l+15]) @fastmath r += dot(vi, mat, vi) end return r end if key == 1 f = f1 elseif key == 2 f = f2 elseif key == 3 f = f3 else error(""qubit position $key not allowed for L."") end parallel_sum(eltype(v), div(L, 16), Threads.nthreads(), f, U, v) end function _expectation_value_threaded_util(q0::Int, U::AbstractMatrix, v::AbstractVector) if q0 > 3 return _expectation_value_util_H(q0, SMatrix{2,2, eltype(v)}(U), v) else return _expectation_value_util_L(q0, SMatrix{2,2, eltype(v)}(U), v) end end _expectation_value_threaded_util(q0::Tuple{Int}, U::AbstractMatrix, v::AbstractVector) = _expectation_value_threaded_util( q0[1], U, v) """""" applys when both keys > 3, U is the transposed op """""" function _expectation_value_util_HH(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2 = key pos1, pos2 = 1 << (q1-1), 1 << (q2-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(L - 1, 2 * pos2 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") total_itr = div(L, 32) f(ist::Int, ifn::Int, posa::Int, posb::Int, m1::Int, m2::Int, m3::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) + 1 # l = div(l, 2) + 1 l1 = l + posa l2 = l + posb l3 = l2 + posa # println(""l0=$l, l1=$l1, l2=$l2, l3=$l3"") vi = SMatrix{8, 4}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l1], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7], p[l2], p[l2+1], p[l2+2], p[l2+3], p[l2+4], p[l2+5], p[l2+6], p[l2+7], p[l3], p[l3+1], p[l3+2], p[l3+3], p[l3+4], p[l3+5], p[l3+6], p[l3+7]) vi_t = transpose(vi) @fastmath r += dot(vi_t, mat, vi_t) end return r end parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, pos1, pos2, mask0, mask1, mask2, U, v) end """""" applys when q1 <= 3 and q2 > 4, U is the transposed op """""" function _expectation_value_util_LH(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2 = key sizej = 1 << (q2-1) mask0 = sizej - 1 mask1 = xor(L - 1, 2 * sizej - 1) f1H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{8, 4}(p[l+1], p[l+3], p[l+5], p[l+7], p[l+9], p[l+11], p[l+13], p[l+15], p[l+2], p[l+4], p[l+6], p[l+8], p[l+10], p[l+12], p[l+14], p[l+16], p[l1+1], p[l1+3], p[l1+5], p[l1+7], p[l1+9], p[l1+11], p[l1+13], p[l1+15], p[l1+2], p[l1+4], p[l1+6], p[l1+8], p[l1+10], p[l1+12], p[l1+14], p[l1+16]) vi_t = transpose(vi) @fastmath r += dot(vi_t, mat, vi_t) end return r end f2H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+5], p[l+6], p[l+9], p[l+10], p[l+13], p[l+14], p[l+3], p[l+4], p[l+7], p[l+8], p[l+11], p[l+12], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+5], p[l1+6], p[l1+9], p[l1+10], p[l1+13], p[l1+14], p[l1+3], p[l1+4], p[l1+7], p[l1+8], p[l1+11], p[l1+12], p[l1+15], p[l1+16]) vi_t = transpose(vi) @fastmath r += dot(vi_t, mat, vi_t) end return r end f3H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+3], p[l+4], p[l+9], p[l+10], p[l+11], p[l+12], p[l+5], p[l+6], p[l+7], p[l+8], p[l+13], p[l+14], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+9], p[l1+10], p[l1+11], p[l1+12], p[l1+5], p[l1+6], p[l1+7], p[l1+8], p[l1+13], p[l1+14], p[l1+15], p[l1+16]) vi_t = transpose(vi) @fastmath r += dot(vi_t, mat, vi_t) end return r end if q1 == 1 f = f1H elseif q1 == 2 f = f2H elseif q1 == 3 f = f3H else error(""qubit position $q1 not allowed for LH."") end total_itr = div(L, 32) parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, sizej, mask0, mask1, U, v) end """""" applys when both keys <= 4 """""" function _expectation_value_util_LL(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2 = key f12(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{4, 8}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l+9], p[l+10], p[l+11], p[l+12], p[l+13], p[l+14], p[l+15], p[l+16], p[l+17], p[l+18], p[l+19], p[l+20], p[l+21], p[l+22], p[l+23], p[l+24], p[l+25], p[l+26], p[l+27], p[l+28], p[l+29], p[l+30], p[l+31]) @fastmath r += dot(vi, mat, vi) end return r end f13(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{4, 8}(p[l], p[l+1], p[l+4], p[l+5], p[l+2], p[l+3], p[l+6], p[l+7], p[l+8], p[l+9], p[l+12], p[l+13], p[l+10], p[l+11], p[l+14], p[l+15], p[l+16], p[l+17], p[l+20], p[l+21], p[l+18], p[l+19], p[l+22], p[l+23], p[l+24], p[l+25], p[l+28], p[l+29], p[l+26], p[l+27], p[l+30], p[l+31]) @fastmath r += dot(vi, mat, vi) end return r end f14(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+9], p[l+10], p[l+3], p[l+4], p[l+11], p[l+12], p[l+5], p[l+6], p[l+13], p[l+14], p[l+7], p[l+8], p[l+15], p[l+16], p[l+17], p[l+18], p[l+25], p[l+26], p[l+19], p[l+20], p[l+27], p[l+28], p[l+21], p[l+22], p[l+29], p[l+30], p[l+23], p[l+24], p[l+31], p[l+32]) @fastmath r += dot(vi, mat, vi) end return r end f23(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{4, 8}(p[l], p[l+2], p[l+4], p[l+6], p[l+1], p[l+3], p[l+5], p[l+7], p[l+8], p[l+10], p[l+12], p[l+14], p[l+9], p[l+11], p[l+13], p[l+15], p[l+16], p[l+18], p[l+20], p[l+22], p[l+17], p[l+19], p[l+21], p[l+23], p[l+24], p[l+26], p[l+28], p[l+30], p[l+25], p[l+27], p[l+29], p[l+31]) @fastmath r += dot(vi, mat, vi) end return r end f24(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{4, 8}(p[l+1], p[l+3], p[l+9], p[l+11], p[l+2], p[l+4], p[l+10], p[l+12], p[l+5], p[l+7], p[l+13], p[l+15], p[l+6], p[l+8], p[l+14], p[l+16], p[l+17], p[l+19], p[l+25], p[l+27], p[l+18], p[l+20], p[l+26], p[l+28], p[l+21], p[l+23], p[l+29], p[l+31], p[l+22], p[l+24], p[l+30], p[l+32]) @fastmath r += dot(vi, mat, vi) end return r end f34(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{4, 8}(p[l+1], p[l+5], p[l+9], p[l+13], p[l+2], p[l+6], p[l+10], p[l+14], p[l+3], p[l+7], p[l+11], p[l+15], p[l+4], p[l+8], p[l+12], p[l+16], p[l+17], p[l+21], p[l+25], p[l+29], p[l+18], p[l+22], p[l+26], p[l+30], p[l+19], p[l+23], p[l+27], p[l+31], p[l+20], p[l+24], p[l+28], p[l+32]) @fastmath r += dot(vi, mat, vi) end return r end if q1==1 && q2 == 2 f = f12 elseif q1==1 && q2 == 3 f = f13 elseif q1==1 && q2 == 4 f = f14 elseif q1==2 && q2 == 3 f = f23 elseif q1==2 && q2 == 4 f = f24 elseif q1==3 && q2 == 4 f = f34 else error(""qubit position $q1 and $q2 not allowed for LL."") end total_itr = div(L, 32) parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, U, v) end function _expectation_value_threaded_util(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector) q0, q1 = key if q0 > 3 return _expectation_value_util_HH(key, SMatrix{4,4, eltype(v)}(U), v) elseif q1 > 4 return _expectation_value_util_LH(key, SMatrix{4,4, eltype(v)}(U), v) else return _expectation_value_util_LL(key, SMatrix{4,4, eltype(v)}(U), v) end end """""" applys when both keys > 2, U is assumed to be transposed """""" function _expectation_value_util_HHH(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2, q3 = key pos1, pos2, pos3 = 1 << (q1-1), 1 << (q2-1), 1 << (q3-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(pos3 - 1, 2 * pos2 - 1) mask3 = xor(L - 1, 2 * pos3 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") total_itr = div(L, 32) f(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, m4::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l000 = (32 * i & m4) | (16 * i & m3) | (8 * i & m2) | (4 * i & m1) + 1 l100 = l000 + posa l010 = l000 + posb l110 = l010 + posa l001 = l000 + posc l101 = l001 + posa l011 = l001 + posb l111 = l011 + posa # println(""$l000, $l100, $l010, $l110, $l001, $l101, $l011, $l111"") vi = SMatrix{4, 8}(p[l000], p[l000+1], p[l000+2], p[l000+3], p[l100], p[l100+1], p[l100+2], p[l100+3], p[l010], p[l010+1], p[l010+2], p[l010+3], p[l110], p[l110+1], p[l110+2], p[l110+3], p[l001], p[l001+1], p[l001+2], p[l001+3], p[l101], p[l101+1], p[l101+2], p[l101+3], p[l011], p[l011+1], p[l011+2], p[l011+3], p[l111], p[l111+1], p[l111+2], p[l111+3]) vi_t = transpose(vi) @fastmath r += dot(vi_t, mat, vi_t) end return r end parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, pos1, pos2, pos3, mask0, mask1, mask2, mask3, U, v) end """""" applys when q1 <= 2 and q2 > 3, U is the transposed op """""" function _expectation_value_util_LHH(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2, q3 = key sizej, sizel = 1 << (q2-1), 1 << (q3-1) mask0 = sizej - 1 mask1 = xor(sizel - 1, 2 * sizej - 1) mask2 = xor(L-1, 2 * sizel - 1) f1H(ist::Int, ifn::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) l1 = l + posb l2 = l + posc l3 = l2 + posb # println(""$l, $l1, $l2, $l3"") vi = SMatrix{4, 8}(p[l+1], p[l+3], p[l+5], p[l+7], p[l+2], p[l+4], p[l+6], p[l+8], p[l1+1], p[l1+3], p[l1+5], p[l1+7], p[l1+2], p[l1+4], p[l1+6], p[l1+8], p[l2+1], p[l2+3], p[l2+5], p[l2+7], p[l2+2], p[l2+4], p[l2+6], p[l2+8], p[l3+1], p[l3+3], p[l3+5], p[l3+7], p[l3+2], p[l3+4], p[l3+6], p[l3+8]) vi_t = transpose(vi) @fastmath r += dot(vi_t, mat, vi_t) end return r end f2H(ist::Int, ifn::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) l1 = l + posb l2 = l + posc l3 = l2 + posb vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+5], p[l+6], p[l+3], p[l+4], p[l+7], p[l+8], p[l1+1], p[l1+2], p[l1+5], p[l1+6], p[l1+3], p[l1+4], p[l1+7], p[l1+8], p[l2+1], p[l2+2], p[l2+5], p[l2+6], p[l2+3], p[l2+4], p[l2+7], p[l2+8], p[l3+1], p[l3+2], p[l3+5], p[l3+6], p[l3+3], p[l3+4], p[l3+7], p[l3+8]) vi_t = transpose(vi) @fastmath r += dot(vi_t, mat, vi_t) end return r end f3H(ist::Int, ifn::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) l1 = l + posb l2 = l + posc l3 = l2 + posb vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7], p[l1+8], p[l2+1], p[l2+2], p[l2+3], p[l2+4], p[l2+5], p[l2+6], p[l2+7], p[l2+8], p[l3+1], p[l3+2], p[l3+3], p[l3+4], p[l3+5], p[l3+6], p[l3+7], p[l3+8]) vi_t = transpose(vi) @fastmath r += dot(vi_t, mat, vi_t) end return r end if q1 == 1 f = f1H elseif q1 == 2 f = f2H elseif q1 == 3 f = f3H else error(""qubit position $q1 not allowed for LHH."") end (q2 > 3) || error(""qubit 2 position $q2 not allowed for LHH."") total_itr = div(L, 32) parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, sizej, sizel, mask0, mask1, mask2, U, v) end """""" applys when q1, q2 <= 3 and q3 > 4, U is the transposed op """""" function _expectation_value_util_LLH(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2, q3 = key sizej = 1 << (q3-1) mask0 = sizej - 1 mask1 = xor(L - 1, 2 * sizej - 1) f12H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{4, 8}(p[l+1], p[l+5], p[l+9], p[l+13], p[l+2], p[l+6], p[l+10], p[l+14], p[l+3], p[l+7], p[l+11], p[l+15], p[l+4], p[l+8], p[l+12], p[l+16], p[l1+1], p[l1+5], p[l1+9], p[l1+13], p[l1+2], p[l1+6], p[l1+10], p[l1+14], p[l1+3], p[l1+7], p[l1+11], p[l1+15], p[l1+4], p[l1+8], p[l1+12], p[l1+16]) vi_t = transpose(vi) @fastmath r += dot(vi_t, mat, vi_t) end return r end f13H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{4, 8}(p[l+1], p[l+3], p[l+9], p[l+11], p[l+2], p[l+4], p[l+10], p[l+12], p[l+5], p[l+7], p[l+13], p[l+15], p[l+6], p[l+8], p[l+14], p[l+16], p[l1+1], p[l1+3], p[l1+9], p[l1+11], p[l1+2], p[l1+4], p[l1+10], p[l1+12], p[l1+5], p[l1+7], p[l1+13], p[l1+15], p[l1+6], p[l1+8], p[l1+14], p[l1+16]) vi_t = transpose(vi) @fastmath r += dot(vi_t, mat, vi_t) end return r end f23H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+9], p[l+10], p[l+3], p[l+4], p[l+11], p[l+12], p[l+5], p[l+6], p[l+13], p[l+14], p[l+7], p[l+8], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+9], p[l1+10], p[l1+3], p[l1+4], p[l1+11], p[l1+12], p[l1+5], p[l1+6], p[l1+13], p[l1+14], p[l1+7], p[l1+8], p[l1+15], p[l1+16]) vi_t = transpose(vi) @fastmath r += dot(vi_t, mat, vi_t) end return r end if q1 == 1 && q2 == 2 f = f12H elseif q1 == 1 && q2 == 3 f = f13H elseif q1 == 2 && q2 == 3 f = f23H else error(""qubit position $q1 not allowed for LH."") end total_itr = div(L, 32) parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, sizej, mask0, mask1, U, v) end """""" applys when both keys <= 4 """""" function _expectation_value_util_LLL(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2, q3 = key f123(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{8, 4}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l+9], p[l+10], p[l+11], p[l+12], p[l+13], p[l+14], p[l+15], p[l+16], p[l+17], p[l+18], p[l+19], p[l+20], p[l+21], p[l+22], p[l+23], p[l+24], p[l+25], p[l+26], p[l+27], p[l+28], p[l+29], p[l+30], p[l+31]) @fastmath r += dot(vi, mat, vi) end return r end f124(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+3], p[l+4], p[l+9], p[l+10], p[l+11], p[l+12], p[l+5], p[l+6], p[l+7], p[l+8], p[l+13], p[l+14], p[l+15], p[l+16], p[l+17], p[l+18], p[l+19], p[l+20], p[l+25], p[l+26], p[l+27], p[l+28], p[l+21], p[l+22], p[l+23], p[l+24], p[l+29], p[l+30], p[l+31], p[l+32]) @fastmath r += dot(vi, mat, vi) end return r end f134(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+5], p[l+6], p[l+9], p[l+10], p[l+13], p[l+14], p[l+3], p[l+4], p[l+7], p[l+8], p[l+11], p[l+12], p[l+15], p[l+16], p[l+17], p[l+18], p[l+21], p[l+22], p[l+25], p[l+26], p[l+29], p[l+30], p[l+19], p[l+20], p[l+23], p[l+24], p[l+27], p[l+28], p[l+31], p[l+32]) @fastmath r += dot(vi, mat, vi) end return r end f234(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{8, 4}(p[l+1], p[l+3], p[l+5], p[l+7], p[l+9], p[l+11], p[l+13], p[l+15], p[l+2], p[l+4], p[l+6], p[l+8], p[l+10], p[l+12], p[l+14], p[l+16], p[l+17], p[l+19], p[l+21], p[l+23], p[l+25], p[l+27], p[l+29], p[l+31], p[l+18], p[l+20], p[l+22], p[l+24], p[l+26], p[l+28], p[l+30], p[l+32]) @fastmath r += dot(vi, mat, vi) end return r end if q1==1 && q2 == 2 && q3 == 3 f = f123 elseif q1==1 && q2 == 2 && q3 == 4 f = f124 elseif q1==1 && q2 == 3 && q3 == 4 f = f134 elseif q1==2 && q2 == 3 && q3 == 4 f = f234 else error(""qubit position $q1 and $q2 not allowed for LL."") end total_itr = div(L, 32) parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, U, v) end function _expectation_value_threaded_util(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) q0, q1, q2 = key if q0 > 2 return _expectation_value_util_HHH(key, SMatrix{8,8, eltype(v)}(U), v) elseif q1 > 3 return _expectation_value_util_LHH(key, SMatrix{8,8, eltype(v)}(U), v) elseif q2 > 4 return _expectation_value_util_LLH(key, SMatrix{8,8, eltype(v)}(U), v) else return _expectation_value_util_LLL(key, SMatrix{8,8, eltype(v)}(U), v) end end expectation_value_threaded(pos::Int, m::AbstractMatrix, state::AbstractVector) = _expectation_value_threaded_util( pos, m, state) expectation_value_threaded(pos::Tuple{Int}, m::AbstractMatrix, state::AbstractVector) = expectation_value_threaded( pos[1], m, state) expectation_value_threaded(pos::Tuple{Int, Int}, m::AbstractMatrix, state::AbstractVector) = _expectation_value_threaded_util( pos, m, state) expectation_value_threaded(pos::Tuple{Int, Int, Int}, m::AbstractMatrix, state::AbstractVector) = _expectation_value_threaded_util( pos, m, state) ","Julia" "Conjugate","guochu/VQC.jl","src/hamiltonian/expecs/expec_threaded_2.jl",".jl","35736","792"," """""" applys when key > 3, U is the transposed op """""" function _expectation_value_util_H(key::Int, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) sizek = 1 << (key - 1) mask0 = sizek - 1 mask1 = xor(L - 1, 2 * sizek - 1) f(ist::Int, ifn::Int, pos::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (16 * i & m2) | (8 * i & m1) + 1 l1 = l + pos vi = SMatrix{8, 2}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l1], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7]) vo = SMatrix{8, 2}(po[l], po[l+1], po[l+2], po[l+3], po[l+4], po[l+5], po[l+6], po[l+7], po[l1], po[l1+1], po[l1+2], po[l1+3], po[l1+4], po[l1+5], po[l1+6], po[l1+7]) @fastmath r += dot(transpose(vo), mat, transpose(vi)) end return r end return parallel_sum(eltype(v), div(L, 16), Threads.nthreads(), f, sizek, mask0, mask1, U, v, vout) end """""" applys when key <= 3, U is the transposed op """""" function _expectation_value_util_L(key::Int, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) f1(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 16 * i + 1 vi = SMatrix{2, 8}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l+9], p[l+10], p[l+11], p[l+12], p[l+13], p[l+14], p[l+15]) vo = SMatrix{2, 8}(po[l], po[l+1], po[l+2], po[l+3], po[l+4], po[l+5], po[l+6], po[l+7], po[l+8], po[l+9], po[l+10], po[l+11], po[l+12], po[l+13], po[l+14], po[l+15]) @fastmath r += dot(vo, mat, vi) end return r end f2(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 16 * i + 1 vi = SMatrix{2, 8}(p[l], p[l+2], p[l+1], p[l+3], p[l+4], p[l+6], p[l+5], p[l+7], p[l+8], p[l+10], p[l+9], p[l+11], p[l+12], p[l+14], p[l+13], p[l+15]) vo = SMatrix{2, 8}(po[l], po[l+2], po[l+1], po[l+3], po[l+4], po[l+6], po[l+5], po[l+7], po[l+8], po[l+10], po[l+9], po[l+11], po[l+12], po[l+14], po[l+13], po[l+15]) @fastmath r += dot(vo, mat, vi) end return r end f3(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 16 * i + 1 vi = SMatrix{2, 8}(p[l], p[l+4], p[l+1], p[l+5], p[l+2], p[l+6], p[l+3], p[l+7], p[l+8], p[l+12], p[l+9], p[l+13], p[l+10], p[l+14], p[l+11], p[l+15]) vo = SMatrix{2, 8}(po[l], po[l+4], po[l+1], po[l+5], po[l+2], po[l+6], po[l+3], po[l+7], po[l+8], po[l+12], po[l+9], po[l+13], po[l+10], po[l+14], po[l+11], po[l+15]) @fastmath r += dot(vo, mat, vi) end return r end if key == 1 f = f1 elseif key == 2 f = f2 elseif key == 3 f = f3 else error(""qubit position $key not allowed for L."") end parallel_sum(eltype(v), div(L, 16), Threads.nthreads(), f, U, v, vout) end function _expectation_value_threaded_util(q0::Int, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) if q0 > 3 return _expectation_value_util_H(q0, SMatrix{2,2, eltype(v)}(U), v, vout) else return _expectation_value_util_L(q0, SMatrix{2,2, eltype(v)}(U), v, vout) end end _expectation_value_threaded_util(q0::Tuple{Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) = _expectation_value_threaded_util( q0[1], U, v, vout) """""" applys when both keys > 3, U is the transposed op """""" function _expectation_value_util_HH(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2 = key pos1, pos2 = 1 << (q1-1), 1 << (q2-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(L - 1, 2 * pos2 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") total_itr = div(L, 32) f(ist::Int, ifn::Int, posa::Int, posb::Int, m1::Int, m2::Int, m3::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) + 1 # l = div(l, 2) + 1 l1 = l + posa l2 = l + posb l3 = l2 + posa # println(""l0=$l, l1=$l1, l2=$l2, l3=$l3"") vi = SMatrix{8, 4}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l1], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7], p[l2], p[l2+1], p[l2+2], p[l2+3], p[l2+4], p[l2+5], p[l2+6], p[l2+7], p[l3], p[l3+1], p[l3+2], p[l3+3], p[l3+4], p[l3+5], p[l3+6], p[l3+7]) vo = SMatrix{8, 4}(po[l], po[l+1], po[l+2], po[l+3], po[l+4], po[l+5], po[l+6], po[l+7], po[l1], po[l1+1], po[l1+2], po[l1+3], po[l1+4], po[l1+5], po[l1+6], po[l1+7], po[l2], po[l2+1], po[l2+2], po[l2+3], po[l2+4], po[l2+5], po[l2+6], po[l2+7], po[l3], po[l3+1], po[l3+2], po[l3+3], po[l3+4], po[l3+5], po[l3+6], po[l3+7]) @fastmath r += dot(transpose(vo), mat, transpose(vi)) end return r end parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, pos1, pos2, mask0, mask1, mask2, U, v, vout) end """""" applys when q1 <= 3 and q2 > 4, U is the transposed op """""" function _expectation_value_util_LH(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2 = key sizej = 1 << (q2-1) mask0 = sizej - 1 mask1 = xor(L - 1, 2 * sizej - 1) f1H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{8, 4}(p[l+1], p[l+3], p[l+5], p[l+7], p[l+9], p[l+11], p[l+13], p[l+15], p[l+2], p[l+4], p[l+6], p[l+8], p[l+10], p[l+12], p[l+14], p[l+16], p[l1+1], p[l1+3], p[l1+5], p[l1+7], p[l1+9], p[l1+11], p[l1+13], p[l1+15], p[l1+2], p[l1+4], p[l1+6], p[l1+8], p[l1+10], p[l1+12], p[l1+14], p[l1+16]) vo = SMatrix{8, 4}(po[l+1], po[l+3], po[l+5], po[l+7], po[l+9], po[l+11], po[l+13], po[l+15], po[l+2], po[l+4], po[l+6], po[l+8], po[l+10], po[l+12], po[l+14], po[l+16], po[l1+1], po[l1+3], po[l1+5], po[l1+7], po[l1+9], po[l1+11], po[l1+13], po[l1+15], po[l1+2], po[l1+4], po[l1+6], po[l1+8], po[l1+10], po[l1+12], po[l1+14], po[l1+16]) @fastmath r += dot(transpose(vo), mat, transpose(vi)) end return r end f2H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+5], p[l+6], p[l+9], p[l+10], p[l+13], p[l+14], p[l+3], p[l+4], p[l+7], p[l+8], p[l+11], p[l+12], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+5], p[l1+6], p[l1+9], p[l1+10], p[l1+13], p[l1+14], p[l1+3], p[l1+4], p[l1+7], p[l1+8], p[l1+11], p[l1+12], p[l1+15], p[l1+16]) vo = SMatrix{8, 4}(po[l+1], po[l+2], po[l+5], po[l+6], po[l+9], po[l+10], po[l+13], po[l+14], po[l+3], po[l+4], po[l+7], po[l+8], po[l+11], po[l+12], po[l+15], po[l+16], po[l1+1], po[l1+2], po[l1+5], po[l1+6], po[l1+9], po[l1+10], po[l1+13], po[l1+14], po[l1+3], po[l1+4], po[l1+7], po[l1+8], po[l1+11], po[l1+12], po[l1+15], po[l1+16]) @fastmath r += dot(transpose(vo), mat, transpose(vi)) end return r end f3H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+3], p[l+4], p[l+9], p[l+10], p[l+11], p[l+12], p[l+5], p[l+6], p[l+7], p[l+8], p[l+13], p[l+14], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+9], p[l1+10], p[l1+11], p[l1+12], p[l1+5], p[l1+6], p[l1+7], p[l1+8], p[l1+13], p[l1+14], p[l1+15], p[l1+16]) vo = SMatrix{8, 4}(po[l+1], po[l+2], po[l+3], po[l+4], po[l+9], po[l+10], po[l+11], po[l+12], po[l+5], po[l+6], po[l+7], po[l+8], po[l+13], po[l+14], po[l+15], po[l+16], po[l1+1], po[l1+2], po[l1+3], po[l1+4], po[l1+9], po[l1+10], po[l1+11], po[l1+12], po[l1+5], po[l1+6], po[l1+7], po[l1+8], po[l1+13], po[l1+14], po[l1+15], po[l1+16]) @fastmath r += dot(transpose(vo), mat, transpose(vi)) end return r end if q1 == 1 f = f1H elseif q1 == 2 f = f2H elseif q1 == 3 f = f3H else error(""qubit position $q1 not allowed for LH."") end total_itr = div(L, 32) parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, sizej, mask0, mask1, U, v, vout) end """""" applys when both keys <= 4 """""" function _expectation_value_util_LL(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2 = key f12(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{4, 8}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l+9], p[l+10], p[l+11], p[l+12], p[l+13], p[l+14], p[l+15], p[l+16], p[l+17], p[l+18], p[l+19], p[l+20], p[l+21], p[l+22], p[l+23], p[l+24], p[l+25], p[l+26], p[l+27], p[l+28], p[l+29], p[l+30], p[l+31]) vo = SMatrix{4, 8}(po[l], po[l+1], po[l+2], po[l+3], po[l+4], po[l+5], po[l+6], po[l+7], po[l+8], po[l+9], po[l+10], po[l+11], po[l+12], po[l+13], po[l+14], po[l+15], po[l+16], po[l+17], po[l+18], po[l+19], po[l+20], po[l+21], po[l+22], po[l+23], po[l+24], po[l+25], po[l+26], po[l+27], po[l+28], po[l+29], po[l+30], po[l+31]) @fastmath r += dot(vo, mat, vi) end return r end f13(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{4, 8}(p[l], p[l+1], p[l+4], p[l+5], p[l+2], p[l+3], p[l+6], p[l+7], p[l+8], p[l+9], p[l+12], p[l+13], p[l+10], p[l+11], p[l+14], p[l+15], p[l+16], p[l+17], p[l+20], p[l+21], p[l+18], p[l+19], p[l+22], p[l+23], p[l+24], p[l+25], p[l+28], p[l+29], p[l+26], p[l+27], p[l+30], p[l+31]) vo = SMatrix{4, 8}(po[l], po[l+1], po[l+4], po[l+5], po[l+2], po[l+3], po[l+6], po[l+7], po[l+8], po[l+9], po[l+12], po[l+13], po[l+10], po[l+11], po[l+14], po[l+15], po[l+16], po[l+17], po[l+20], po[l+21], po[l+18], po[l+19], po[l+22], po[l+23], po[l+24], po[l+25], po[l+28], po[l+29], po[l+26], po[l+27], po[l+30], po[l+31]) @fastmath r += dot(vo, mat, vi) end return r end f14(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+9], p[l+10], p[l+3], p[l+4], p[l+11], p[l+12], p[l+5], p[l+6], p[l+13], p[l+14], p[l+7], p[l+8], p[l+15], p[l+16], p[l+17], p[l+18], p[l+25], p[l+26], p[l+19], p[l+20], p[l+27], p[l+28], p[l+21], p[l+22], p[l+29], p[l+30], p[l+23], p[l+24], p[l+31], p[l+32]) vo = SMatrix{4, 8}(po[l+1], po[l+2], po[l+9], po[l+10], po[l+3], po[l+4], po[l+11], po[l+12], po[l+5], po[l+6], po[l+13], po[l+14], po[l+7], po[l+8], po[l+15], po[l+16], po[l+17], po[l+18], po[l+25], po[l+26], po[l+19], po[l+20], po[l+27], po[l+28], po[l+21], po[l+22], po[l+29], po[l+30], po[l+23], po[l+24], po[l+31], po[l+32]) @fastmath r += dot(vo, mat, vi) end return r end f23(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{4, 8}(p[l], p[l+2], p[l+4], p[l+6], p[l+1], p[l+3], p[l+5], p[l+7], p[l+8], p[l+10], p[l+12], p[l+14], p[l+9], p[l+11], p[l+13], p[l+15], p[l+16], p[l+18], p[l+20], p[l+22], p[l+17], p[l+19], p[l+21], p[l+23], p[l+24], p[l+26], p[l+28], p[l+30], p[l+25], p[l+27], p[l+29], p[l+31]) vo = SMatrix{4, 8}(po[l], po[l+2], po[l+4], po[l+6], po[l+1], po[l+3], po[l+5], po[l+7], po[l+8], po[l+10], po[l+12], po[l+14], po[l+9], po[l+11], po[l+13], po[l+15], po[l+16], po[l+18], po[l+20], po[l+22], po[l+17], po[l+19], po[l+21], po[l+23], po[l+24], po[l+26], po[l+28], po[l+30], po[l+25], po[l+27], po[l+29], po[l+31]) @fastmath r += dot(vo, mat, vi) end return r end f24(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{4, 8}(p[l+1], p[l+3], p[l+9], p[l+11], p[l+2], p[l+4], p[l+10], p[l+12], p[l+5], p[l+7], p[l+13], p[l+15], p[l+6], p[l+8], p[l+14], p[l+16], p[l+17], p[l+19], p[l+25], p[l+27], p[l+18], p[l+20], p[l+26], p[l+28], p[l+21], p[l+23], p[l+29], p[l+31], p[l+22], p[l+24], p[l+30], p[l+32]) vo = SMatrix{4, 8}(po[l+1], po[l+3], po[l+9], po[l+11], po[l+2], po[l+4], po[l+10], po[l+12], po[l+5], po[l+7], po[l+13], po[l+15], po[l+6], po[l+8], po[l+14], po[l+16], po[l+17], po[l+19], po[l+25], po[l+27], po[l+18], po[l+20], po[l+26], po[l+28], po[l+21], po[l+23], po[l+29], po[l+31], po[l+22], po[l+24], po[l+30], po[l+32]) @fastmath r += dot(vo, mat, vi) end return r end f34(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{4, 8}(p[l+1], p[l+5], p[l+9], p[l+13], p[l+2], p[l+6], p[l+10], p[l+14], p[l+3], p[l+7], p[l+11], p[l+15], p[l+4], p[l+8], p[l+12], p[l+16], p[l+17], p[l+21], p[l+25], p[l+29], p[l+18], p[l+22], p[l+26], p[l+30], p[l+19], p[l+23], p[l+27], p[l+31], p[l+20], p[l+24], p[l+28], p[l+32]) vo = SMatrix{4, 8}(po[l+1], po[l+5], po[l+9], po[l+13], po[l+2], po[l+6], po[l+10], po[l+14], po[l+3], po[l+7], po[l+11], po[l+15], po[l+4], po[l+8], po[l+12], po[l+16], po[l+17], po[l+21], po[l+25], po[l+29], po[l+18], po[l+22], po[l+26], po[l+30], po[l+19], po[l+23], po[l+27], po[l+31], po[l+20], po[l+24], po[l+28], po[l+32]) @fastmath r += dot(vo, mat, vi) end return r end if q1==1 && q2 == 2 f = f12 elseif q1==1 && q2 == 3 f = f13 elseif q1==1 && q2 == 4 f = f14 elseif q1==2 && q2 == 3 f = f23 elseif q1==2 && q2 == 4 f = f24 elseif q1==3 && q2 == 4 f = f34 else error(""qubit position $q1 and $q2 not allowed for LL."") end total_itr = div(L, 32) parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, U, v, vout) end function _expectation_value_threaded_util(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) q0, q1 = key if q0 > 3 return _expectation_value_util_HH(key, SMatrix{4,4, eltype(v)}(U), v, vout) elseif q1 > 4 return _expectation_value_util_LH(key, SMatrix{4,4, eltype(v)}(U), v, vout) else return _expectation_value_util_LL(key, SMatrix{4,4, eltype(v)}(U), v, vout) end end """""" applys when both keys > 2, U is assumed to be transposed """""" function _expectation_value_util_HHH(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2, q3 = key pos1, pos2, pos3 = 1 << (q1-1), 1 << (q2-1), 1 << (q3-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(pos3 - 1, 2 * pos2 - 1) mask3 = xor(L - 1, 2 * pos3 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") total_itr = div(L, 32) f(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, m4::Int, mat, p, po) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l000 = (32 * i & m4) | (16 * i & m3) | (8 * i & m2) | (4 * i & m1) + 1 l100 = l000 + posa l010 = l000 + posb l110 = l010 + posa l001 = l000 + posc l101 = l001 + posa l011 = l001 + posb l111 = l011 + posa # println(""$l000, $l100, $l010, $l110, $l001, $l101, $l011, $l111"") vi = SMatrix{4, 8}(p[l000], p[l000+1], p[l000+2], p[l000+3], p[l100], p[l100+1], p[l100+2], p[l100+3], p[l010], p[l010+1], p[l010+2], p[l010+3], p[l110], p[l110+1], p[l110+2], p[l110+3], p[l001], p[l001+1], p[l001+2], p[l001+3], p[l101], p[l101+1], p[l101+2], p[l101+3], p[l011], p[l011+1], p[l011+2], p[l011+3], p[l111], p[l111+1], p[l111+2], p[l111+3]) vo = SMatrix{4, 8}(po[l000], po[l000+1], po[l000+2], po[l000+3], po[l100], po[l100+1], po[l100+2], po[l100+3], po[l010], po[l010+1], po[l010+2], po[l010+3], po[l110], po[l110+1], po[l110+2], po[l110+3], po[l001], po[l001+1], po[l001+2], po[l001+3], po[l101], po[l101+1], po[l101+2], po[l101+3], po[l011], po[l011+1], po[l011+2], po[l011+3], po[l111], po[l111+1], po[l111+2], po[l111+3]) @fastmath r += dot(transpose(vo), mat, transpose(vi)) end return r end parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, pos1, pos2, pos3, mask0, mask1, mask2, mask3, U, v, vout) end """""" applys when q1 <= 2 and q2 > 3, U is the transposed op """""" function _expectation_value_util_LHH(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2, q3 = key sizej, sizel = 1 << (q2-1), 1 << (q3-1) mask0 = sizej - 1 mask1 = xor(sizel - 1, 2 * sizej - 1) mask2 = xor(L-1, 2 * sizel - 1) f1H(ist::Int, ifn::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, mat, p, po) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) l1 = l + posb l2 = l + posc l3 = l2 + posb # println(""$l, $l1, $l2, $l3"") vi = SMatrix{4, 8}(p[l+1], p[l+3], p[l+5], p[l+7], p[l+2], p[l+4], p[l+6], p[l+8], p[l1+1], p[l1+3], p[l1+5], p[l1+7], p[l1+2], p[l1+4], p[l1+6], p[l1+8], p[l2+1], p[l2+3], p[l2+5], p[l2+7], p[l2+2], p[l2+4], p[l2+6], p[l2+8], p[l3+1], p[l3+3], p[l3+5], p[l3+7], p[l3+2], p[l3+4], p[l3+6], p[l3+8]) vo = SMatrix{4, 8}(po[l+1], po[l+3], po[l+5], po[l+7], po[l+2], po[l+4], po[l+6], po[l+8], po[l1+1], po[l1+3], po[l1+5], po[l1+7], po[l1+2], po[l1+4], po[l1+6], po[l1+8], po[l2+1], po[l2+3], po[l2+5], po[l2+7], po[l2+2], po[l2+4], po[l2+6], po[l2+8], po[l3+1], po[l3+3], po[l3+5], po[l3+7], po[l3+2], po[l3+4], po[l3+6], po[l3+8]) @fastmath r += dot(transpose(vo), mat, transpose(vi)) end return r end f2H(ist::Int, ifn::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, mat, p, po) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) l1 = l + posb l2 = l + posc l3 = l2 + posb vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+5], p[l+6], p[l+3], p[l+4], p[l+7], p[l+8], p[l1+1], p[l1+2], p[l1+5], p[l1+6], p[l1+3], p[l1+4], p[l1+7], p[l1+8], p[l2+1], p[l2+2], p[l2+5], p[l2+6], p[l2+3], p[l2+4], p[l2+7], p[l2+8], p[l3+1], p[l3+2], p[l3+5], p[l3+6], p[l3+3], p[l3+4], p[l3+7], p[l3+8]) vo = SMatrix{4, 8}(po[l+1], po[l+2], po[l+5], po[l+6], po[l+3], po[l+4], po[l+7], po[l+8], po[l1+1], po[l1+2], po[l1+5], po[l1+6], po[l1+3], po[l1+4], po[l1+7], po[l1+8], po[l2+1], po[l2+2], po[l2+5], po[l2+6], po[l2+3], po[l2+4], po[l2+7], po[l2+8], po[l3+1], po[l3+2], po[l3+5], po[l3+6], po[l3+3], po[l3+4], po[l3+7], po[l3+8]) @fastmath r += dot(transpose(vo), mat, transpose(vi)) end return r end f3H(ist::Int, ifn::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, mat, p, po) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) l1 = l + posb l2 = l + posc l3 = l2 + posb vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7], p[l1+8], p[l2+1], p[l2+2], p[l2+3], p[l2+4], p[l2+5], p[l2+6], p[l2+7], p[l2+8], p[l3+1], p[l3+2], p[l3+3], p[l3+4], p[l3+5], p[l3+6], p[l3+7], p[l3+8]) vo = SMatrix{4, 8}(po[l+1], po[l+2], po[l+3], po[l+4], po[l+5], po[l+6], po[l+7], po[l+8], po[l1+1], po[l1+2], po[l1+3], po[l1+4], po[l1+5], po[l1+6], po[l1+7], po[l1+8], po[l2+1], po[l2+2], po[l2+3], po[l2+4], po[l2+5], po[l2+6], po[l2+7], po[l2+8], po[l3+1], po[l3+2], po[l3+3], po[l3+4], po[l3+5], po[l3+6], po[l3+7], po[l3+8]) @fastmath r += dot(transpose(vo), mat, transpose(vi)) end return r end if q1 == 1 f = f1H elseif q1 == 2 f = f2H elseif q1 == 3 f = f3H else error(""qubit position $q1 not allowed for LHH."") end (q2 > 3) || error(""qubit 2 position $q2 not allowed for LHH."") total_itr = div(L, 32) parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, sizej, sizel, mask0, mask1, mask2, U, v, vout) end """""" applys when q1, q2 <= 3 and q3 > 4, U is the transposed op """""" function _expectation_value_util_LLH(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2, q3 = key sizej = 1 << (q3-1) mask0 = sizej - 1 mask1 = xor(L - 1, 2 * sizej - 1) f12H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat, p, po) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{4, 8}(p[l+1], p[l+5], p[l+9], p[l+13], p[l+2], p[l+6], p[l+10], p[l+14], p[l+3], p[l+7], p[l+11], p[l+15], p[l+4], p[l+8], p[l+12], p[l+16], p[l1+1], p[l1+5], p[l1+9], p[l1+13], p[l1+2], p[l1+6], p[l1+10], p[l1+14], p[l1+3], p[l1+7], p[l1+11], p[l1+15], p[l1+4], p[l1+8], p[l1+12], p[l1+16]) vo = SMatrix{4, 8}(po[l+1], po[l+5], po[l+9], po[l+13], po[l+2], po[l+6], po[l+10], po[l+14], po[l+3], po[l+7], po[l+11], po[l+15], po[l+4], po[l+8], po[l+12], po[l+16], po[l1+1], po[l1+5], po[l1+9], po[l1+13], po[l1+2], po[l1+6], po[l1+10], po[l1+14], po[l1+3], po[l1+7], po[l1+11], po[l1+15], po[l1+4], po[l1+8], po[l1+12], po[l1+16]) @fastmath r += dot(transpose(vo), mat, transpose(vi)) end return r end f13H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat, p, po) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{4, 8}(p[l+1], p[l+3], p[l+9], p[l+11], p[l+2], p[l+4], p[l+10], p[l+12], p[l+5], p[l+7], p[l+13], p[l+15], p[l+6], p[l+8], p[l+14], p[l+16], p[l1+1], p[l1+3], p[l1+9], p[l1+11], p[l1+2], p[l1+4], p[l1+10], p[l1+12], p[l1+5], p[l1+7], p[l1+13], p[l1+15], p[l1+6], p[l1+8], p[l1+14], p[l1+16]) vo = SMatrix{4, 8}(po[l+1], po[l+3], po[l+9], po[l+11], po[l+2], po[l+4], po[l+10], po[l+12], po[l+5], po[l+7], po[l+13], po[l+15], po[l+6], po[l+8], po[l+14], po[l+16], po[l1+1], po[l1+3], po[l1+9], po[l1+11], po[l1+2], po[l1+4], po[l1+10], po[l1+12], po[l1+5], po[l1+7], po[l1+13], po[l1+15], po[l1+6], po[l1+8], po[l1+14], po[l1+16]) @fastmath r += dot(transpose(vo), mat, transpose(vi)) end return r end f23H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat, p, po) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+9], p[l+10], p[l+3], p[l+4], p[l+11], p[l+12], p[l+5], p[l+6], p[l+13], p[l+14], p[l+7], p[l+8], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+9], p[l1+10], p[l1+3], p[l1+4], p[l1+11], p[l1+12], p[l1+5], p[l1+6], p[l1+13], p[l1+14], p[l1+7], p[l1+8], p[l1+15], p[l1+16]) vo = SMatrix{4, 8}(po[l+1], po[l+2], po[l+9], po[l+10], po[l+3], po[l+4], po[l+11], po[l+12], po[l+5], po[l+6], po[l+13], po[l+14], po[l+7], po[l+8], po[l+15], po[l+16], po[l1+1], po[l1+2], po[l1+9], po[l1+10], po[l1+3], po[l1+4], po[l1+11], po[l1+12], po[l1+5], po[l1+6], po[l1+13], po[l1+14], po[l1+7], po[l1+8], po[l1+15], po[l1+16]) @fastmath r += dot(transpose(vo), mat, transpose(vi)) end return r end if q1 == 1 && q2 == 2 f = f12H elseif q1 == 1 && q2 == 3 f = f13H elseif q1 == 2 && q2 == 3 f = f23H else error(""qubit position $q1 not allowed for LH."") end total_itr = div(L, 32) parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, sizej, mask0, mask1, U, v, vout) end """""" applys when both keys <= 4 """""" function _expectation_value_util_LLL(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2, q3 = key f123(ist::Int, ifn::Int, mat::AbstractMatrix, p, po) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{8, 4}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l+9], p[l+10], p[l+11], p[l+12], p[l+13], p[l+14], p[l+15], p[l+16], p[l+17], p[l+18], p[l+19], p[l+20], p[l+21], p[l+22], p[l+23], p[l+24], p[l+25], p[l+26], p[l+27], p[l+28], p[l+29], p[l+30], p[l+31]) vo = SMatrix{8, 4}(po[l], po[l+1], po[l+2], po[l+3], po[l+4], po[l+5], po[l+6], po[l+7], po[l+8], po[l+9], po[l+10], po[l+11], po[l+12], po[l+13], po[l+14], po[l+15], po[l+16], po[l+17], po[l+18], po[l+19], po[l+20], po[l+21], po[l+22], po[l+23], po[l+24], po[l+25], po[l+26], po[l+27], po[l+28], po[l+29], po[l+30], po[l+31]) @fastmath r += dot(vo, mat, vi) end return r end f124(ist::Int, ifn::Int, mat::AbstractMatrix, p, po) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+3], p[l+4], p[l+9], p[l+10], p[l+11], p[l+12], p[l+5], p[l+6], p[l+7], p[l+8], p[l+13], p[l+14], p[l+15], p[l+16], p[l+17], p[l+18], p[l+19], p[l+20], p[l+25], p[l+26], p[l+27], p[l+28], p[l+21], p[l+22], p[l+23], p[l+24], p[l+29], p[l+30], p[l+31], p[l+32]) vo = SMatrix{8, 4}(po[l+1], po[l+2], po[l+3], po[l+4], po[l+9], po[l+10], po[l+11], po[l+12], po[l+5], po[l+6], po[l+7], po[l+8], po[l+13], po[l+14], po[l+15], po[l+16], po[l+17], po[l+18], po[l+19], po[l+20], po[l+25], po[l+26], po[l+27], po[l+28], po[l+21], po[l+22], po[l+23], po[l+24], po[l+29], po[l+30], po[l+31], po[l+32]) @fastmath r += dot(vo, mat, vi) end return r end f134(ist::Int, ifn::Int, mat::AbstractMatrix, p, po) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+5], p[l+6], p[l+9], p[l+10], p[l+13], p[l+14], p[l+3], p[l+4], p[l+7], p[l+8], p[l+11], p[l+12], p[l+15], p[l+16], p[l+17], p[l+18], p[l+21], p[l+22], p[l+25], p[l+26], p[l+29], p[l+30], p[l+19], p[l+20], p[l+23], p[l+24], p[l+27], p[l+28], p[l+31], p[l+32]) vo = SMatrix{8, 4}(po[l+1], po[l+2], po[l+5], po[l+6], po[l+9], po[l+10], po[l+13], po[l+14], po[l+3], po[l+4], po[l+7], po[l+8], po[l+11], po[l+12], po[l+15], po[l+16], po[l+17], po[l+18], po[l+21], po[l+22], po[l+25], po[l+26], po[l+29], po[l+30], po[l+19], po[l+20], po[l+23], po[l+24], po[l+27], po[l+28], po[l+31], po[l+32]) @fastmath r += dot(vo, mat, vi) end return r end f234(ist::Int, ifn::Int, mat::AbstractMatrix, p, po) = begin r = zero(eltype(p)) @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{8, 4}(p[l+1], p[l+3], p[l+5], p[l+7], p[l+9], p[l+11], p[l+13], p[l+15], p[l+2], p[l+4], p[l+6], p[l+8], p[l+10], p[l+12], p[l+14], p[l+16], p[l+17], p[l+19], p[l+21], p[l+23], p[l+25], p[l+27], p[l+29], p[l+31], p[l+18], p[l+20], p[l+22], p[l+24], p[l+26], p[l+28], p[l+30], p[l+32]) vo = SMatrix{8, 4}(po[l+1], po[l+3], po[l+5], po[l+7], po[l+9], po[l+11], po[l+13], po[l+15], po[l+2], po[l+4], po[l+6], po[l+8], po[l+10], po[l+12], po[l+14], po[l+16], po[l+17], po[l+19], po[l+21], po[l+23], po[l+25], po[l+27], po[l+29], po[l+31], po[l+18], po[l+20], po[l+22], po[l+24], po[l+26], po[l+28], po[l+30], po[l+32]) @fastmath r += dot(vo, mat, vi) end return r end if q1==1 && q2 == 2 && q3 == 3 f = f123 elseif q1==1 && q2 == 2 && q3 == 4 f = f124 elseif q1==1 && q2 == 3 && q3 == 4 f = f134 elseif q1==2 && q2 == 3 && q3 == 4 f = f234 else error(""qubit position $q1 and $q2 not allowed for LL."") end total_itr = div(L, 32) parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, U, v, vout) end function _expectation_value_threaded_util(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) q0, q1, q2 = key if q0 > 2 return _expectation_value_util_HHH(key, SMatrix{8,8, eltype(v)}(U), v, vout) elseif q1 > 3 return _expectation_value_util_LHH(key, SMatrix{8,8, eltype(v)}(U), v, vout) elseif q2 > 4 return _expectation_value_util_LLH(key, SMatrix{8,8, eltype(v)}(U), v, vout) else return _expectation_value_util_LLL(key, SMatrix{8,8, eltype(v)}(U), v, vout) end end expectation_value_threaded(pos::Int, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) = _expectation_value_threaded_util( pos, m, state, state_c) expectation_value_threaded(pos::Tuple{Int}, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) = expectation_value_threaded( pos[1], m, state, state_c) expectation_value_threaded(pos::Tuple{Int, Int}, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) = _expectation_value_threaded_util( pos, m, state, state_c) expectation_value_threaded(pos::Tuple{Int, Int, Int}, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) = _expectation_value_threaded_util( pos, m, state, state_c) ","Julia" "Conjugate","guochu/VQC.jl","src/hamiltonian/expecs/expec_high_qubit_terms_2.jl",".jl","5747","135"," function _expectation_value_fourbody_util(key::Tuple{Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2, q3, q4 = key pos1, pos2, pos3, pos4 = 1 << (q1-1), 1 << (q2-1), 1 << (q3-1), 1 << (q4-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(pos3 - 1, 2 * pos2 - 1) mask3 = xor(pos4 - 1, 2 * pos3 - 1) mask4 = xor(L - 1, 2 * pos4 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") function f(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, posd::Int, m1::Int, m2::Int, m3::Int, m4::Int, m5::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) r = zero(eltype(p)) @inbounds for i in ist:ifn l0000 = (16 * i & m5) | (8 * i & m4) | (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 l1000 = l0000 + posa l0100 = l0000 + posb l0010 = l0000 + posc l0001 = l0000 + posd l1100 = l0100 + posa l1010 = l0010 + posa l1001 = l1000 + posd l0110 = l0010 + posb l0101 = l0100 + posd l0011 = l0010 + posd l1110 = l1100 + posc l1101 = l1100 + posd l1011 = l1010 + posd l0111 = l0110 + posd l1111 = l1110 + posd vi = SVector(p[l0000], p[l1000], p[l0100], p[l1100], p[l0010], p[l1010], p[l0110], p[l1110], p[l0001], p[l1001], p[l0101], p[l1101], p[l0011], p[l1011], p[l0111], p[l1111]) vo = SVector(po[l0000], po[l1000], po[l0100], po[l1100], po[l0010], po[l1010], po[l0110], po[l1110], po[l0001], po[l1001], po[l0101], po[l1101], po[l0011], po[l1011], po[l0111], po[l1111]) @fastmath r += dot(vo, mat, vi) end return r end total_itr = div(L, 16) parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, pos1, pos2, pos3, pos4, mask0, mask1, mask2, mask3, mask4, U, v, vout) end expectation_value_threaded(key::Tuple{Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) = _expectation_value_fourbody_util( key, SMatrix{16,16, eltype(v)}(U), v, vout) function _expectation_value_fivebody_util(key::Tuple{Int, Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2, q3, q4, q5 = key pos1, pos2, pos3, pos4, pos5 = 1 << (q1-1), 1 << (q2-1), 1 << (q3-1), 1 << (q4-1), 1 << (q5-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(pos3 - 1, 2 * pos2 - 1) mask3 = xor(pos4 - 1, 2 * pos3 - 1) mask4 = xor(pos5 - 1, 2 * pos4 - 1) mask5 = xor(L - 1, 2 * pos5 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") function f(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, posd::Int, pose::Int, m1::Int, m2::Int, m3::Int, m4::Int, m5::Int, m6::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) r = zero(eltype(p)) @inbounds for i in ist:ifn l00000 = (32 * i & m6) | (16 * i & m5) | (8 * i & m4) | (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 l10000 = l00000 + posa l01000 = l00000 + posb l00100 = l00000 + posc l00010 = l00000 + posd l00001 = l00000 + pose l11000 = l01000 + posa l10100 = l00100 + posa l10010 = l10000 + posd l10001 = l10000 + pose l01100 = l00100 + posb l01010 = l01000 + posd l01001 = l01000 + pose l00110 = l00100 + posd l00101 = l00100 + pose l00011 = l00010 + pose l11100 = l11000 + posc l11010 = l11000 + posd l11001 = l11000 + pose l10110 = l10100 + posd l10101 = l10100 + pose l10011 = l10010 + pose l01110 = l01100 + posd l01101 = l01100 + pose l01011 = l01010 + pose l00111 = l00110 + pose l11110 = l11100 + posd l11101 = l11100 + pose l11011 = l11010 + pose l10111 = l10110 + pose l01111 = l01110 + pose l11111 = l11110 + pose vi = SVector(p[l00000], p[l10000], p[l01000], p[l11000], p[l00100], p[l10100], p[l01100], p[l11100], p[l00010], p[l10010], p[l01010], p[l11010], p[l00110], p[l10110], p[l01110], p[l11110], p[l00001], p[l10001], p[l01001], p[l11001], p[l00101], p[l10101], p[l01101], p[l11101], p[l00011], p[l10011], p[l01011], p[l11011], p[l00111], p[l10111], p[l01111], p[l11111]) vo = SVector(po[l00000], po[l10000], po[l01000], po[l11000], po[l00100], po[l10100], po[l01100], po[l11100], po[l00010], po[l10010], po[l01010], po[l11010], po[l00110], po[l10110], po[l01110], po[l11110], po[l00001], po[l10001], po[l01001], po[l11001], po[l00101], po[l10101], po[l01101], po[l11101], po[l00011], po[l10011], po[l01011], po[l11011], po[l00111], po[l10111], po[l01111], po[l11111]) @fastmath r += dot(vo, mat, vi) end return r end total_itr = div(L, 32) parallel_sum(eltype(v), total_itr, Threads.nthreads(), f, pos1, pos2, pos3, pos4, pos5, mask0, mask1, mask2, mask3, mask4, mask5, U, v, vout) end expectation_value_threaded(key::Tuple{Int, Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) = _expectation_value_fivebody_util( key, SMatrix{32,32, eltype(v)}(U), v, vout) ","Julia" "Conjugate","guochu/VQC.jl","src/hamiltonian/expecs/expecs.jl",".jl","6158","132"," include(""expec_serial.jl"") include(""expec_threaded.jl"") include(""expec_threaded_2.jl"") include(""expec_high_qubit_terms.jl"") include(""expec_high_qubit_terms_2.jl"") function expectation(m::QubitsTerm, state::StateVector) isempty(m) && return dot(state, state) if length(positions(m)) <= LARGEST_SUPPORTED_NTERMS return expectation_value(Tuple(positions(m)), _get_mat(m), storage(state)) else return dot(state, m * state) end end function expectation(m::QubitsOperator, state::StateVector) if _largest_nterm(m) <= LARGEST_SUPPORTED_NTERMS r = zero(eltype(state)) for (k, v) in m.data r += expectation_value(k, _get_mat(length(k), v), storage(state)) end return r else # state = storage(state) # workspace = similar(state) # state_2 = zeros(eltype(state), length(state)) # for (k, v) in m.data # for item in v # _apply_qterm_util!(QubitsTerm(k, item[1], item[2]), state, workspace) # state_2 .+= workspace # end # end # return dot(state, state_2) return dot(state, m * state) end end function expectation(state_c::StateVector, m::QubitsTerm, state::StateVector) isempty(m) && return dot(state_c, state) if length(positions(m)) <= LARGEST_SUPPORTED_NTERMS return expectation_value(Tuple(positions(m)), _get_mat(m), storage(state), storage(state_c)) else return dot(state_c, m * state) end end function expectation(state_c::StateVector, m::QubitsOperator, state::StateVector) if _largest_nterm(m) <= LARGEST_SUPPORTED_NTERMS r = zero(eltype(state)) for (k, v) in m.data r += expectation_value(k, _get_mat(length(k), v), storage(state), storage(state_c)) end return r else # state = storage(state) # workspace = similar(state) # state_2 = zeros(eltype(state), length(state)) # for (k, v) in m.data # for item in v # _apply_qterm_util!(QubitsTerm(k, item[1], item[2]), state, workspace) # state_2 .+= workspace # end # end # return dot(state_c, state_2) return dot(state_c, m * state) end end expectation(m::Gate, state::StateVector) = expectation_value(ordered_positions(m), ordered_mat(m), storage(state)) expectation(state_c::StateVector, m::Gate, state::StateVector) = expectation_value( ordered_positions(m), ordered_mat(m), storage(state), storage(state_c)) expectation(state_c::StateVector, m::AbstractMatrix, state::StateVector) = dot(storage(state_c), m, storage(state)) expectation(m::AbstractMatrix, state::StateVector) = dot(state, m, state) expectation_value(pos::Int, m::AbstractMatrix, state::AbstractVector) = (length(state) >= 32) ? expectation_value_threaded( pos, m, state) : expectation_value_serial(pos, m, state) expectation_value(pos::Int, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) = (length(state) >= 32) ? expectation_value_threaded( pos, m, state, state_c) : expectation_value_serial(pos, m, state, state_c) expectation_value(pos::Tuple{Int}, m::AbstractMatrix, state::AbstractVector) = expectation_value(pos[1], m, state) expectation_value(pos::Tuple{Int}, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) = expectation_value( pos[1], m, state, state_c) expectation_value(pos::Tuple{Int, Int}, m::AbstractMatrix, state::AbstractVector) = (length(state) >= 32) ? expectation_value_threaded( pos, m, state) : expectation_value_serial(pos, m, state) expectation_value(pos::Tuple{Int, Int}, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) = (length(state) >= 32) ? expectation_value_threaded( pos, m, state, state_c) : expectation_value_serial(pos, m, state, state_c) expectation_value(pos::Tuple{Int, Int}, m::AbstractArray{T, 4}, state::AbstractVector) where T = expectation_value( pos, reshape(m, 4, 4), state) expectation_value(pos::Tuple{Int, Int}, m::AbstractArray{T, 4}, state::AbstractVector, state_c::AbstractVector) where T = expectation_value( pos, reshape(m, 4, 4), state, state_c) expectation_value(pos::Tuple{Int, Int, Int}, m::AbstractMatrix, state::AbstractVector) = (length(state) >= 32) ? expectation_value_threaded( pos, m, state) : expectation_value_serial(pos, m, state) expectation_value(pos::Tuple{Int, Int, Int}, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) = (length(state) >= 32) ? expectation_value_threaded( pos, m, state, state_c) : expectation_value_serial(pos, m, state, state_c) expectation_value(pos::Tuple{Int, Int, Int}, m::AbstractArray{T, 6}, state::AbstractVector) where T = expectation_value( pos, reshape(m, 8, 8), state) expectation_value(pos::Tuple{Int, Int, Int}, m::AbstractArray{T, 6}, state::AbstractVector, state_c::AbstractVector) where T = expectation_value( pos, reshape(m, 8, 8), state, state_c) expectation_value(pos::Tuple{Int, Int, Int, Int}, m::AbstractMatrix, state::AbstractVector) = expectation_value_threaded( pos, m, state) expectation_value(pos::Tuple{Int, Int, Int, Int}, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) = expectation_value_threaded( pos, m, state, state_c) expectation_value(pos::Tuple{Int, Int, Int, Int}, m::AbstractArray{T, 8}, state::AbstractVector) where T = expectation_value( pos, Matrix{eltype(state)}(reshape(m, 16, 16)), state) expectation_value(pos::Tuple{Int, Int, Int, Int}, m::AbstractArray{T, 8}, state::AbstractVector, state_c::AbstractVector) where T = expectation_value( pos, Matrix{eltype(state)}(reshape(m, 16, 16)), state, state_c) expectation_value(pos::Tuple{Int, Int, Int, Int, Int}, m::AbstractMatrix, state::AbstractVector) = expectation_value_threaded( pos, m, state) expectation_value(pos::Tuple{Int, Int, Int, Int, Int}, m::AbstractMatrix, state::AbstractVector, state_c::AbstractVector) = expectation_value_threaded( pos, m, state, state_c) expectation_value(pos::Tuple{Int, Int, Int, Int, Int}, m::AbstractArray{T, 10}, state::AbstractVector) where T = expectation_value( pos, Matrix{eltype(state)}(reshape(m, 32, 32)), state) expectation_value(pos::Tuple{Int, Int, Int, Int, Int}, m::AbstractArray{T, 10}, state::AbstractVector, state_c::AbstractVector) where T = expectation_value( pos, Matrix{eltype(state)}(reshape(m, 32, 32)), state, state_c) ","Julia" "Conjugate","guochu/VQC.jl","src/hamiltonian/apply_qterms/long_range_threaded.jl",".jl","6932","181"," function _apply_fourbody_term_impl!(key::Tuple{Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2, q3, q4 = key pos1, pos2, pos3, pos4 = 1 << (q1-1), 1 << (q2-1), 1 << (q3-1), 1 << (q4-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(pos3 - 1, 2 * pos2 - 1) mask3 = xor(pos4 - 1, 2 * pos3 - 1) mask4 = xor(L - 1, 2 * pos4 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") function f(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, posd::Int, m1::Int, m2::Int, m3::Int, m4::Int, m5::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) @inbounds for i in ist:ifn l0000 = (16 * i & m5) | (8 * i & m4) | (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 l1000 = l0000 + posa l0100 = l0000 + posb l0010 = l0000 + posc l0001 = l0000 + posd l1100 = l0100 + posa l1010 = l0010 + posa l1001 = l1000 + posd l0110 = l0010 + posb l0101 = l0100 + posd l0011 = l0010 + posd l1110 = l1100 + posc l1101 = l1100 + posd l1011 = l1010 + posd l0111 = l0110 + posd l1111 = l1110 + posd vi = SVector(p[l0000], p[l1000], p[l0100], p[l1100], p[l0010], p[l1010], p[l0110], p[l1110], p[l0001], p[l1001], p[l0101], p[l1101], p[l0011], p[l1011], p[l0111], p[l1111]) @fastmath begin vo = mat * vi po[l0000] += vo[1] po[l1000] += vo[2] po[l0100] += vo[3] po[l1100] += vo[4] po[l0010] += vo[5] po[l1010] += vo[6] po[l0110] += vo[7] po[l1110] += vo[8] po[l0001] += vo[9] po[l1001] += vo[10] po[l0101] += vo[11] po[l1101] += vo[12] po[l0011] += vo[13] po[l1011] += vo[14] po[l0111] += vo[15] po[l1111] += vo[16] end end end total_itr = div(L, 16) parallel_run(total_itr, Threads.nthreads(), f, pos1, pos2, pos3, pos4, mask0, mask1, mask2, mask3, mask4, U, v, vout) end _apply_gate_threaded2!(key::Tuple{Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) = _apply_fourbody_term_impl!( key, SMatrix{16,16, eltype(v)}(U), v, vout) _apply_gate_2!(key::Tuple{Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) = _apply_gate_threaded2!( key, U, v, vout) function _apply_fivebody_term_impl!(key::Tuple{Int, Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2, q3, q4, q5 = key pos1, pos2, pos3, pos4, pos5 = 1 << (q1-1), 1 << (q2-1), 1 << (q3-1), 1 << (q4-1), 1 << (q5-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(pos3 - 1, 2 * pos2 - 1) mask3 = xor(pos4 - 1, 2 * pos3 - 1) mask4 = xor(pos5 - 1, 2 * pos4 - 1) mask5 = xor(L - 1, 2 * pos5 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") function f(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, posd::Int, pose::Int, m1::Int, m2::Int, m3::Int, m4::Int, m5::Int, m6::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) @inbounds for i in ist:ifn l00000 = (32 * i & m6) | (16 * i & m5) | (8 * i & m4) | (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 l10000 = l00000 + posa l01000 = l00000 + posb l00100 = l00000 + posc l00010 = l00000 + posd l00001 = l00000 + pose l11000 = l01000 + posa l10100 = l00100 + posa l10010 = l10000 + posd l10001 = l10000 + pose l01100 = l00100 + posb l01010 = l01000 + posd l01001 = l01000 + pose l00110 = l00100 + posd l00101 = l00100 + pose l00011 = l00010 + pose l11100 = l11000 + posc l11010 = l11000 + posd l11001 = l11000 + pose l10110 = l10100 + posd l10101 = l10100 + pose l10011 = l10010 + pose l01110 = l01100 + posd l01101 = l01100 + pose l01011 = l01010 + pose l00111 = l00110 + pose l11110 = l11100 + posd l11101 = l11100 + pose l11011 = l11010 + pose l10111 = l10110 + pose l01111 = l01110 + pose l11111 = l11110 + pose vi = SVector(p[l00000], p[l10000], p[l01000], p[l11000], p[l00100], p[l10100], p[l01100], p[l11100], p[l00010], p[l10010], p[l01010], p[l11010], p[l00110], p[l10110], p[l01110], p[l11110], p[l00001], p[l10001], p[l01001], p[l11001], p[l00101], p[l10101], p[l01101], p[l11101], p[l00011], p[l10011], p[l01011], p[l11011], p[l00111], p[l10111], p[l01111], p[l11111]) @fastmath begin vo = mat * vi po[l00000] += vo[1] po[l10000] += vo[2] po[l01000] += vo[3] po[l11000] += vo[4] po[l00100] += vo[5] po[l10100] += vo[6] po[l01100] += vo[7] po[l11100] += vo[8] po[l00010] += vo[9] po[l10010] += vo[10] po[l01010] += vo[11] po[l11010] += vo[12] po[l00110] += vo[13] po[l10110] += vo[14] po[l01110] += vo[15] po[l11110] += vo[16] po[l00001] += vo[17] po[l10001] += vo[18] po[l01001] += vo[19] po[l11001] += vo[20] po[l00101] += vo[21] po[l10101] += vo[22] po[l01101] += vo[23] po[l11101] += vo[24] po[l00011] += vo[25] po[l10011] += vo[26] po[l01011] += vo[27] po[l11011] += vo[28] po[l00111] += vo[29] po[l10111] += vo[30] po[l01111] += vo[31] po[l11111] += vo[32] end end end total_itr = div(L, 32) parallel_run(total_itr, Threads.nthreads(), f, pos1, pos2, pos3, pos4, pos5, mask0, mask1, mask2, mask3, mask4, mask5, U, v, vout) end _apply_gate_threaded2!(key::Tuple{Int, Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) = _apply_fivebody_term_impl!( key, SMatrix{32,32, eltype(v)}(U), v, vout) ","Julia" "Conjugate","guochu/VQC.jl","src/hamiltonian/apply_qterms/apply_qterms.jl",".jl","1440","65","include(""short_range_serial.jl"") include(""short_range_threaded.jl"") include(""long_range_threaded.jl"") function (m::QubitsTerm)(vr::StateVector) v = storage(vr) vout = similar(v) _apply_qterm_util!(m, v, vout) return StateVector(vout, nqubits(vr)) end function (m::QubitsOperator)(vr::StateVector) v = storage(vr) vout = zeros(eltype(v), length(v)) if _largest_nterm(m) <= LARGEST_SUPPORTED_NTERMS _apply_util!(m, v, vout) else workspace = similar(v) for (k, dd) in m.data for item in dd _apply_qterm_util!(QubitsTerm(k, item[1], item[2]), v, workspace) vout .+= workspace end end end return StateVector(vout, nqubits(vr)) end Base.:*(m::QubitsOperator, v::StateVector) = m(v) Base.:*(m::QubitsTerm, v::StateVector) = m(v) const LARGEST_SUPPORTED_NTERMS = 5 function _largest_nterm(x::QubitsOperator) n = 0 for (k, v) in x.data n = max(n, length(k)) end return n end function _apply_qterm_util!(m::QubitsTerm, v::AbstractVector, vout::AbstractVector) tmp = coeff(m) @. vout = tmp * v if length(v) >= 32 for (pos, mat) in zip(positions(m), oplist(m)) _apply_gate_threaded2!(pos, mat, vout) end else for (pos, mat) in zip(positions(m), oplist(m)) _apply_gate_2!(pos, mat, vout) end end end _apply_util!(m::QubitsOperator, v::AbstractVector, vout::AbstractVector) = (length(v) >= 32) ? _apply_threaded_util!( m, v, vout) : _apply_serial_util!(m, v, vout) ","Julia" "Conjugate","guochu/VQC.jl","src/hamiltonian/apply_qterms/short_range_threaded.jl",".jl","58807","1528"," """""" applys when key > 3, U is the transposed op """""" function _apply_onebody_gate_H!(key::Int, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) sizek = 1 << (key - 1) mask0 = sizek - 1 mask1 = xor(L - 1, 2 * sizek - 1) f(ist::Int, ifn::Int, pos::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = (16 * i & m2) | (8 * i & m1) + 1 l1 = l + pos vi = SMatrix{8, 2}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l1], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7]) @fastmath begin vo = vi * mat po[l] += vo[1] po[l+1] += vo[2] po[l+2] += vo[3] po[l+3] += vo[4] po[l+4] += vo[5] po[l+5] += vo[6] po[l+6] += vo[7] po[l+7] += vo[8] po[l1] += vo[9] po[l1+1] += vo[10] po[l1+2] += vo[11] po[l1+3] += vo[12] po[l1+4] += vo[13] po[l1+5] += vo[14] po[l1+6] += vo[15] po[l1+7] += vo[16] end end end parallel_run(div(L, 16), Threads.nthreads(), f, sizek, mask0, mask1, U, v, vout) end """""" applys when key <= 3, U is the transposed op """""" function _apply_onebody_gate_L!(key::Int, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) f1(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = 16 * i + 1 vi = SMatrix{2, 8}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l+9], p[l+10], p[l+11], p[l+12], p[l+13], p[l+14], p[l+15]) @fastmath begin vo = mat * vi po[l] += vo[1] po[l+1] += vo[2] po[l+2] += vo[3] po[l+3] += vo[4] po[l+4] += vo[5] po[l+5] += vo[6] po[l+6] += vo[7] po[l+7] += vo[8] po[l+8] += vo[9] po[l+9] += vo[10] po[l+10] += vo[11] po[l+11] += vo[12] po[l+12] += vo[13] po[l+13] += vo[14] po[l+14] += vo[15] po[l+15] += vo[16] end # @fastmath po[l:(l+15)] .+= mat * vi end end f2(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = 16 * i + 1 vi = SMatrix{2, 8}(p[l], p[l+2], p[l+1], p[l+3], p[l+4], p[l+6], p[l+5], p[l+7], p[l+8], p[l+10], p[l+9], p[l+11], p[l+12], p[l+14], p[l+13], p[l+15]) @fastmath begin vo = mat * vi po[l] += vo[1] po[l+2] += vo[2] po[l+1] += vo[3] po[l+3] += vo[4] po[l+4] += vo[5] po[l+6] += vo[6] po[l+5] += vo[7] po[l+7] += vo[8] po[l+8] += vo[9] po[l+10] += vo[10] po[l+9] += vo[11] po[l+11] += vo[12] po[l+12] += vo[13] po[l+14] += vo[14] po[l+13] += vo[15] po[l+15] += vo[16] end # @fastmath p[l], p[l+2], p[l+1], p[l+3], p[l+4], p[l+6], p[l+5], p[l+7], # p[l+8], p[l+10], p[l+9], p[l+11], p[l+12], p[l+14], p[l+13], p[l+15] = mat * vi end end f3(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = 16 * i + 1 vi = SMatrix{2, 8}(p[l], p[l+4], p[l+1], p[l+5], p[l+2], p[l+6], p[l+3], p[l+7], p[l+8], p[l+12], p[l+9], p[l+13], p[l+10], p[l+14], p[l+11], p[l+15]) @fastmath begin vo = mat * vi po[l] += vo[1] po[l+4] += vo[2] po[l+1] += vo[3] po[l+5] += vo[4] po[l+2] += vo[5] po[l+6] += vo[6] po[l+3] += vo[7] po[l+7] += vo[8] po[l+8] += vo[9] po[l+12] += vo[10] po[l+9] += vo[11] po[l+13] += vo[12] po[l+10] += vo[13] po[l+14] += vo[14] po[l+11] += vo[15] po[l+15] += vo[16] end # @fastmath p[l], p[l+4], p[l+1], p[l+5], p[l+2], p[l+6], p[l+3], p[l+7], # p[l+8], p[l+12], p[l+9], p[l+13], p[l+10], p[l+14], p[l+11], p[l+15] = mat * vi end end if key == 1 f = f1 elseif key == 2 f = f2 elseif key == 3 f = f3 else error(""qubit position $key not allowed for L."") end parallel_run(div(L, 16), Threads.nthreads(), f, U, v, vout) end function _apply_gate_threaded2!(q0::Int, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) if q0 > 3 return _apply_onebody_gate_H!(q0, SMatrix{2,2, eltype(v)}(transpose(U)), v, vout) else return _apply_onebody_gate_L!(q0, SMatrix{2,2, eltype(v)}(U), v, vout) end end _apply_gate_threaded2!(q0::Tuple{Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) = _apply_gate_threaded2!( q0[1], U, v, vout) """""" applys when both keys > 3, U is the transposed op """""" function _apply_twobody_gate_HH!(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2 = key pos1, pos2 = 1 << (q1-1), 1 << (q2-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(L - 1, 2 * pos2 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") total_itr = div(L, 32) f(ist::Int, ifn::Int, posa::Int, posb::Int, m1::Int, m2::Int, m3::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) + 1 # l = div(l, 2) + 1 l1 = l + posa l2 = l + posb l3 = l2 + posa # println(""l0=$l, l1=$l1, l2=$l2, l3=$l3"") vi = SMatrix{8, 4}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l1], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7], p[l2], p[l2+1], p[l2+2], p[l2+3], p[l2+4], p[l2+5], p[l2+6], p[l2+7], p[l3], p[l3+1], p[l3+2], p[l3+3], p[l3+4], p[l3+5], p[l3+6], p[l3+7]) @fastmath begin vo = vi * mat po[l] += vo[1] po[l+1] += vo[2] po[l+2] += vo[3] po[l+3] += vo[4] po[l+4] += vo[5] po[l+5] += vo[6] po[l+6] += vo[7] po[l+7] += vo[8] po[l1] += vo[9] po[l1+1] += vo[10] po[l1+2] += vo[11] po[l1+3] += vo[12] po[l1+4] += vo[13] po[l1+5] += vo[14] po[l1+6] += vo[15] po[l1+7] += vo[16] po[l2] += vo[17] po[l2+1] += vo[18] po[l2+2] += vo[19] po[l2+3] += vo[20] po[l2+4] += vo[21] po[l2+5] += vo[22] po[l2+6] += vo[23] po[l2+7] += vo[24] po[l3] += vo[25] po[l3+1] += vo[26] po[l3+2] += vo[27] po[l3+3] += vo[28] po[l3+4] += vo[29] po[l3+5] += vo[30] po[l3+6] += vo[31] po[l3+7] += vo[32] end # @fastmath p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], # p[l1], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7], # p[l2], p[l2+1], p[l2+2], p[l2+3], p[l2+4], p[l2+5], p[l2+6], p[l2+7], # p[l3], p[l3+1], p[l3+2], p[l3+3], p[l3+4], p[l3+5], p[l3+6], p[l3+7] = vi * mat end end parallel_run(total_itr, Threads.nthreads(), f, pos1, pos2, mask0, mask1, mask2, U, v, vout) end """""" applys when q1 <= 3 and q2 > 4, U is the transposed op """""" function _apply_twobody_gate_LH!(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2 = key sizej = 1 << (q2-1) mask0 = sizej - 1 mask1 = xor(L - 1, 2 * sizej - 1) f1H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{8, 4}(p[l+1], p[l+3], p[l+5], p[l+7], p[l+9], p[l+11], p[l+13], p[l+15], p[l+2], p[l+4], p[l+6], p[l+8], p[l+10], p[l+12], p[l+14], p[l+16], p[l1+1], p[l1+3], p[l1+5], p[l1+7], p[l1+9], p[l1+11], p[l1+13], p[l1+15], p[l1+2], p[l1+4], p[l1+6], p[l1+8], p[l1+10], p[l1+12], p[l1+14], p[l1+16]) @fastmath begin vo = vi * mat po[l+1] += vo[1] po[l+3] += vo[2] po[l+5] += vo[3] po[l+7] += vo[4] po[l+9] += vo[5] po[l+11] += vo[6] po[l+13] += vo[7] po[l+15] += vo[8] po[l+2] += vo[9] po[l+4] += vo[10] po[l+6] += vo[11] po[l+8] += vo[12] po[l+10] += vo[13] po[l+12] += vo[14] po[l+14] += vo[15] po[l+16] += vo[16] po[l1+1] += vo[17] po[l1+3] += vo[18] po[l1+5] += vo[19] po[l1+7] += vo[20] po[l1+9] += vo[21] po[l1+11] += vo[22] po[l1+13] += vo[23] po[l1+15] += vo[24] po[l1+2] += vo[25] po[l1+4] += vo[26] po[l1+6] += vo[27] po[l1+8] += vo[28] po[l1+10] += vo[29] po[l1+12] += vo[30] po[l1+14] += vo[31] po[l1+16] += vo[32] end # @fastmath p[l+1], p[l+3], p[l+5], p[l+7], p[l+9], p[l+11], p[l+13], p[l+15], # p[l+2], p[l+4], p[l+6], p[l+8], p[l+10], p[l+12], p[l+14], p[l+16], # p[l1+1], p[l1+3], p[l1+5], p[l1+7], p[l1+9], p[l1+11], p[l1+13], p[l1+15], # p[l1+2], p[l1+4], p[l1+6], p[l1+8], p[l1+10], p[l1+12], p[l1+14], p[l1+16] = vi * mat end end f2H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+5], p[l+6], p[l+9], p[l+10], p[l+13], p[l+14], p[l+3], p[l+4], p[l+7], p[l+8], p[l+11], p[l+12], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+5], p[l1+6], p[l1+9], p[l1+10], p[l1+13], p[l1+14], p[l1+3], p[l1+4], p[l1+7], p[l1+8], p[l1+11], p[l1+12], p[l1+15], p[l1+16]) @fastmath begin vo = vi * mat po[l+1] += vo[1] po[l+2] += vo[2] po[l+5] += vo[3] po[l+6] += vo[4] po[l+9] += vo[5] po[l+10] += vo[6] po[l+13] += vo[7] po[l+14] += vo[8] po[l+3] += vo[9] po[l+4] += vo[10] po[l+7] += vo[11] po[l+8] += vo[12] po[l+11] += vo[13] po[l+12] += vo[14] po[l+15] += vo[15] po[l+16] += vo[16] po[l1+1] += vo[17] po[l1+2] += vo[18] po[l1+5] += vo[19] po[l1+6] += vo[20] po[l1+9] += vo[21] po[l1+10] += vo[22] po[l1+13] += vo[23] po[l1+14] += vo[24] po[l1+3] += vo[25] po[l1+4] += vo[26] po[l1+7] += vo[27] po[l1+8] += vo[28] po[l1+11] += vo[29] po[l1+12] += vo[30] po[l1+15] += vo[31] po[l1+16] += vo[32] end # @fastmath p[l+1], p[l+2], p[l+5], p[l+6], p[l+9], p[l+10], p[l+13], p[l+14], # p[l+3], p[l+4], p[l+7], p[l+8], p[l+11], p[l+12], p[l+15], p[l+16], # p[l1+1], p[l1+2], p[l1+5], p[l1+6], p[l1+9], p[l1+10], p[l1+13], p[l1+14], # p[l1+3], p[l1+4], p[l1+7], p[l1+8], p[l1+11], p[l1+12], p[l1+15], p[l1+16] = vi * mat end end f3H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+3], p[l+4], p[l+9], p[l+10], p[l+11], p[l+12], p[l+5], p[l+6], p[l+7], p[l+8], p[l+13], p[l+14], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+9], p[l1+10], p[l1+11], p[l1+12], p[l1+5], p[l1+6], p[l1+7], p[l1+8], p[l1+13], p[l1+14], p[l1+15], p[l1+16]) @fastmath begin vo = vi * mat po[l+1] += vo[1] po[l+2] += vo[2] po[l+3] += vo[3] po[l+4] += vo[4] po[l+9] += vo[5] po[l+10] += vo[6] po[l+11] += vo[7] po[l+12] += vo[8] po[l+5] += vo[9] po[l+6] += vo[10] po[l+7] += vo[11] po[l+8] += vo[12] po[l+13] += vo[13] po[l+14] += vo[14] po[l+15] += vo[15] po[l+16] += vo[16] po[l1+1] += vo[17] po[l1+2] += vo[18] po[l1+3] += vo[19] po[l1+4] += vo[20] po[l1+9] += vo[21] po[l1+10] += vo[22] po[l1+11] += vo[23] po[l1+12] += vo[24] po[l1+5] += vo[25] po[l1+6] += vo[26] po[l1+7] += vo[27] po[l1+8] += vo[28] po[l1+13] += vo[29] po[l1+14] += vo[30] po[l1+15] += vo[31] po[l1+16] += vo[32] end # @fastmath p[l+1], p[l+2], p[l+3], p[l+4], p[l+9], p[l+10], p[l+11], p[l+12], # p[l+5], p[l+6], p[l+7], p[l+8], p[l+13], p[l+14], p[l+15], p[l+16], # p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+9], p[l1+10], p[l1+11], p[l1+12], # p[l1+5], p[l1+6], p[l1+7], p[l1+8], p[l1+13], p[l1+14], p[l1+15], p[l1+16] = vi * mat end end if q1 == 1 f = f1H elseif q1 == 2 f = f2H elseif q1 == 3 f = f3H else error(""qubit position $q1 not allowed for LH."") end total_itr = div(L, 32) parallel_run(total_itr, Threads.nthreads(), f, sizej, mask0, mask1, U, v, vout) end """""" applys when both keys <= 4 """""" function _apply_twobody_gate_LL!(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2 = key f12(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{4, 8}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l+9], p[l+10], p[l+11], p[l+12], p[l+13], p[l+14], p[l+15], p[l+16], p[l+17], p[l+18], p[l+19], p[l+20], p[l+21], p[l+22], p[l+23], p[l+24], p[l+25], p[l+26], p[l+27], p[l+28], p[l+29], p[l+30], p[l+31]) @fastmath begin vo = mat * vi po[l] += vo[1] po[l+1] += vo[2] po[l+2] += vo[3] po[l+3] += vo[4] po[l+4] += vo[5] po[l+5] += vo[6] po[l+6] += vo[7] po[l+7] += vo[8] po[l+8] += vo[9] po[l+9] += vo[10] po[l+10] += vo[11] po[l+11] += vo[12] po[l+12] += vo[13] po[l+13] += vo[14] po[l+14] += vo[15] po[l+15] += vo[16] po[l+16] += vo[17] po[l+17] += vo[18] po[l+18] += vo[19] po[l+19] += vo[20] po[l+20] += vo[21] po[l+21] += vo[22] po[l+22] += vo[23] po[l+23] += vo[24] po[l+24] += vo[25] po[l+25] += vo[26] po[l+26] += vo[27] po[l+27] += vo[28] po[l+28] += vo[29] po[l+29] += vo[30] po[l+30] += vo[31] po[l+31] += vo[32] end # @fastmath po[l:(l+31)] = mat * vi end end f13(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{4, 8}(p[l], p[l+1], p[l+4], p[l+5], p[l+2], p[l+3], p[l+6], p[l+7], p[l+8], p[l+9], p[l+12], p[l+13], p[l+10], p[l+11], p[l+14], p[l+15], p[l+16], p[l+17], p[l+20], p[l+21], p[l+18], p[l+19], p[l+22], p[l+23], p[l+24], p[l+25], p[l+28], p[l+29], p[l+26], p[l+27], p[l+30], p[l+31]) @fastmath begin vo = mat * vi po[l] += vo[1] po[l+1] += vo[2] po[l+4] += vo[3] po[l+5] += vo[4] po[l+2] += vo[5] po[l+3] += vo[6] po[l+6] += vo[7] po[l+7] += vo[8] po[l+8] += vo[9] po[l+9] += vo[10] po[l+12] += vo[11] po[l+13] += vo[12] po[l+10] += vo[13] po[l+11] += vo[14] po[l+14] += vo[15] po[l+15] += vo[16] po[l+16] += vo[17] po[l+17] += vo[18] po[l+20] += vo[19] po[l+21] += vo[20] po[l+18] += vo[21] po[l+19] += vo[22] po[l+22] += vo[23] po[l+23] += vo[24] po[l+24] += vo[25] po[l+25] += vo[26] po[l+28] += vo[27] po[l+29] += vo[28] po[l+26] += vo[29] po[l+27] += vo[30] po[l+30] += vo[31] po[l+31] += vo[32] end # @fastmath p[l], p[l+1], p[l+4], p[l+5], p[l+2], p[l+3], p[l+6], p[l+7], # p[l+8], p[l+9], p[l+12], p[l+13], p[l+10], p[l+11], p[l+14], p[l+15], # p[l+16], p[l+17], p[l+20], p[l+21], p[l+18], p[l+19], p[l+22], p[l+23], # p[l+24], p[l+25], p[l+28], p[l+29], p[l+26], p[l+27], p[l+30], p[l+31] = mat * vi end end f14(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+9], p[l+10], p[l+3], p[l+4], p[l+11], p[l+12], p[l+5], p[l+6], p[l+13], p[l+14], p[l+7], p[l+8], p[l+15], p[l+16], p[l+17], p[l+18], p[l+25], p[l+26], p[l+19], p[l+20], p[l+27], p[l+28], p[l+21], p[l+22], p[l+29], p[l+30], p[l+23], p[l+24], p[l+31], p[l+32]) @fastmath begin vo = mat * vi po[l+1] += vo[1] po[l+2] += vo[2] po[l+9] += vo[3] po[l+10] += vo[4] po[l+3] += vo[5] po[l+4] += vo[6] po[l+11] += vo[7] po[l+12] += vo[8] po[l+5] += vo[9] po[l+6] += vo[10] po[l+13] += vo[11] po[l+14] += vo[12] po[l+7] += vo[13] po[l+8] += vo[14] po[l+15] += vo[15] po[l+16] += vo[16] po[l+17] += vo[17] po[l+18] += vo[18] po[l+25] += vo[19] po[l+26] += vo[20] po[l+19] += vo[21] po[l+20] += vo[22] po[l+27] += vo[23] po[l+28] += vo[24] po[l+21] += vo[25] po[l+22] += vo[26] po[l+29] += vo[27] po[l+30] += vo[28] po[l+23] += vo[29] po[l+24] += vo[30] po[l+31] += vo[31] po[l+32] += vo[32] end # @fastmath p[l+1], p[l+2], p[l+9], p[l+10], p[l+3], p[l+4], p[l+11], p[l+12], # p[l+5], p[l+6], p[l+13], p[l+14], p[l+7], p[l+8], p[l+15], p[l+16], # p[l+17], p[l+18], p[l+25], p[l+26], p[l+19], p[l+20], p[l+27], p[l+28], # p[l+21], p[l+22], p[l+29], p[l+30], p[l+23], p[l+24], p[l+31], p[l+32] = mat * vi end end f23(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{4, 8}(p[l], p[l+2], p[l+4], p[l+6], p[l+1], p[l+3], p[l+5], p[l+7], p[l+8], p[l+10], p[l+12], p[l+14], p[l+9], p[l+11], p[l+13], p[l+15], p[l+16], p[l+18], p[l+20], p[l+22], p[l+17], p[l+19], p[l+21], p[l+23], p[l+24], p[l+26], p[l+28], p[l+30], p[l+25], p[l+27], p[l+29], p[l+31]) @fastmath begin vo = mat * vi po[l] += vo[1] po[l+2] += vo[2] po[l+4] += vo[3] po[l+6] += vo[4] po[l+1] += vo[5] po[l+3] += vo[6] po[l+5] += vo[7] po[l+7] += vo[8] po[l+8] += vo[9] po[l+10] += vo[10] po[l+12] += vo[11] po[l+14] += vo[12] po[l+9] += vo[13] po[l+11] += vo[14] po[l+13] += vo[15] po[l+15] += vo[16] po[l+16] += vo[17] po[l+18] += vo[18] po[l+20] += vo[19] po[l+22] += vo[20] po[l+17] += vo[21] po[l+19] += vo[22] po[l+21] += vo[23] po[l+23] += vo[24] po[l+24] += vo[25] po[l+26] += vo[26] po[l+28] += vo[27] po[l+30] += vo[28] po[l+25] += vo[29] po[l+27] += vo[30] po[l+29] += vo[31] po[l+31] += vo[32] end # @fastmath p[l], p[l+2], p[l+4], p[l+6], p[l+1], p[l+3], p[l+5], p[l+7], # p[l+8], p[l+10], p[l+12], p[l+14], p[l+9], p[l+11], p[l+13], p[l+15], # p[l+16], p[l+18], p[l+20], p[l+22], p[l+17], p[l+19], p[l+21], p[l+23], # p[l+24], p[l+26], p[l+28], p[l+30], p[l+25], p[l+27], p[l+29], p[l+31] = mat * vi end end f24(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{4, 8}(p[l+1], p[l+3], p[l+9], p[l+11], p[l+2], p[l+4], p[l+10], p[l+12], p[l+5], p[l+7], p[l+13], p[l+15], p[l+6], p[l+8], p[l+14], p[l+16], p[l+17], p[l+19], p[l+25], p[l+27], p[l+18], p[l+20], p[l+26], p[l+28], p[l+21], p[l+23], p[l+29], p[l+31], p[l+22], p[l+24], p[l+30], p[l+32]) @fastmath begin vo = mat * vi po[l+1] += vo[1] po[l+3] += vo[2] po[l+9] += vo[3] po[l+11] += vo[4] po[l+2] += vo[5] po[l+4] += vo[6] po[l+10] += vo[7] po[l+12] += vo[8] po[l+5] += vo[9] po[l+7] += vo[10] po[l+13] += vo[11] po[l+15] += vo[12] po[l+6] += vo[13] po[l+8] += vo[14] po[l+14] += vo[15] po[l+16] += vo[16] po[l+17] += vo[17] po[l+19] += vo[18] po[l+25] += vo[19] po[l+27] += vo[20] po[l+18] += vo[21] po[l+20] += vo[22] po[l+26] += vo[23] po[l+28] += vo[24] po[l+21] += vo[25] po[l+23] += vo[26] po[l+29] += vo[27] po[l+31] += vo[28] po[l+22] += vo[29] po[l+24] += vo[30] po[l+30] += vo[31] po[l+32] += vo[32] end # @fastmath p[l+1], p[l+3], p[l+9], p[l+11], p[l+2], p[l+4], p[l+10], p[l+12], # p[l+5], p[l+7], p[l+13], p[l+15], p[l+6], p[l+8], p[l+14], p[l+16], # p[l+17], p[l+19], p[l+25], p[l+27], p[l+18], p[l+20], p[l+26], p[l+28], # p[l+21], p[l+23], p[l+29], p[l+31], p[l+22], p[l+24], p[l+30], p[l+32] = mat * vi end end f34(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{4, 8}(p[l+1], p[l+5], p[l+9], p[l+13], p[l+2], p[l+6], p[l+10], p[l+14], p[l+3], p[l+7], p[l+11], p[l+15], p[l+4], p[l+8], p[l+12], p[l+16], p[l+17], p[l+21], p[l+25], p[l+29], p[l+18], p[l+22], p[l+26], p[l+30], p[l+19], p[l+23], p[l+27], p[l+31], p[l+20], p[l+24], p[l+28], p[l+32]) @fastmath begin vo = mat * vi po[l+1] += vo[1] po[l+5] += vo[2] po[l+9] += vo[3] po[l+13] += vo[4] po[l+2] += vo[5] po[l+6] += vo[6] po[l+10] += vo[7] po[l+14] += vo[8] po[l+3] += vo[9] po[l+7] += vo[10] po[l+11] += vo[11] po[l+15] += vo[12] po[l+4] += vo[13] po[l+8] += vo[14] po[l+12] += vo[15] po[l+16] += vo[16] po[l+17] += vo[17] po[l+21] += vo[18] po[l+25] += vo[19] po[l+29] += vo[20] po[l+18] += vo[21] po[l+22] += vo[22] po[l+26] += vo[23] po[l+30] += vo[24] po[l+19] += vo[25] po[l+23] += vo[26] po[l+27] += vo[27] po[l+31] += vo[28] po[l+20] += vo[29] po[l+24] += vo[30] po[l+28] += vo[31] po[l+32] += vo[32] end # @fastmath p[l+1], p[l+5], p[l+9], p[l+13], p[l+2], p[l+6], p[l+10], p[l+14], # p[l+3], p[l+7], p[l+11], p[l+15], p[l+4], p[l+8], p[l+12], p[l+16], # p[l+17], p[l+21], p[l+25], p[l+29], p[l+18], p[l+22], p[l+26], p[l+30], # p[l+19], p[l+23], p[l+27], p[l+31], p[l+20], p[l+24], p[l+28], p[l+32] = mat * vi end end if q1==1 && q2 == 2 f = f12 elseif q1==1 && q2 == 3 f = f13 elseif q1==1 && q2 == 4 f = f14 elseif q1==2 && q2 == 3 f = f23 elseif q1==2 && q2 == 4 f = f24 elseif q1==3 && q2 == 4 f = f34 else error(""qubit position $q1 and $q2 not allowed for LL."") end total_itr = div(L, 32) parallel_run(total_itr, Threads.nthreads(), f, U, v, vout) end function _apply_gate_threaded2!(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) q0, q1 = key if q0 > 3 return _apply_twobody_gate_HH!(key, SMatrix{4,4, eltype(v)}(transpose(U)), v, vout) elseif q1 > 4 return _apply_twobody_gate_LH!(key, SMatrix{4,4, eltype(v)}(transpose(U)), v, vout) else return _apply_twobody_gate_LL!(key, SMatrix{4,4, eltype(v)}(U), v, vout) end end """""" applys when both keys > 2, U is assumed to be transposed """""" function _apply_threebody_gate_HHH!(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2, q3 = key pos1, pos2, pos3 = 1 << (q1-1), 1 << (q2-1), 1 << (q3-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(pos3 - 1, 2 * pos2 - 1) mask3 = xor(L - 1, 2 * pos3 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") total_itr = div(L, 32) f(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, m4::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l000 = (32 * i & m4) | (16 * i & m3) | (8 * i & m2) | (4 * i & m1) + 1 l100 = l000 + posa l010 = l000 + posb l110 = l010 + posa l001 = l000 + posc l101 = l001 + posa l011 = l001 + posb l111 = l011 + posa # println(""$l000, $l100, $l010, $l110, $l001, $l101, $l011, $l111"") vi = SMatrix{4, 8}(p[l000], p[l000+1], p[l000+2], p[l000+3], p[l100], p[l100+1], p[l100+2], p[l100+3], p[l010], p[l010+1], p[l010+2], p[l010+3], p[l110], p[l110+1], p[l110+2], p[l110+3], p[l001], p[l001+1], p[l001+2], p[l001+3], p[l101], p[l101+1], p[l101+2], p[l101+3], p[l011], p[l011+1], p[l011+2], p[l011+3], p[l111], p[l111+1], p[l111+2], p[l111+3]) @fastmath begin vo = vi * mat po[l000] += vo[1] po[l000+1] += vo[2] po[l000+2] += vo[3] po[l000+3] += vo[4] po[l100] += vo[5] po[l100+1] += vo[6] po[l100+2] += vo[7] po[l100+3] += vo[8] po[l010] += vo[9] po[l010+1] += vo[10] po[l010+2] += vo[11] po[l010+3] += vo[12] po[l110] += vo[13] po[l110+1] += vo[14] po[l110+2] += vo[15] po[l110+3] += vo[16] po[l001] += vo[17] po[l001+1] += vo[18] po[l001+2] += vo[19] po[l001+3] += vo[20] po[l101] += vo[21] po[l101+1] += vo[22] po[l101+2] += vo[23] po[l101+3] += vo[24] po[l011] += vo[25] po[l011+1] += vo[26] po[l011+2] += vo[27] po[l011+3] += vo[28] po[l111] += vo[29] po[l111+1] += vo[30] po[l111+2] += vo[31] po[l111+3] += vo[32] end # @fastmath p[l000], p[l000+1], p[l000+2], p[l000+3], # p[l100], p[l100+1], p[l100+2], p[l100+3], # p[l010], p[l010+1], p[l010+2], p[l010+3], # p[l110], p[l110+1], p[l110+2], p[l110+3], # p[l001], p[l001+1], p[l001+2], p[l001+3], # p[l101], p[l101+1], p[l101+2], p[l101+3], # p[l011], p[l011+1], p[l011+2], p[l011+3], # p[l111], p[l111+1], p[l111+2], p[l111+3] = vi * mat end end parallel_run(total_itr, Threads.nthreads(), f, pos1, pos2, pos3, mask0, mask1, mask2, mask3, U, v, vout) end """""" applys when q1 <= 2 and q2 > 3, U is the transposed op """""" function _apply_threebody_gate_LHH!(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2, q3 = key sizej, sizel = 1 << (q2-1), 1 << (q3-1) mask0 = sizej - 1 mask1 = xor(sizel - 1, 2 * sizej - 1) mask2 = xor(L-1, 2 * sizel - 1) f1H(ist::Int, ifn::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) l1 = l + posb l2 = l + posc l3 = l2 + posb # println(""$l, $l1, $l2, $l3"") vi = SMatrix{4, 8}(p[l+1], p[l+3], p[l+5], p[l+7], p[l+2], p[l+4], p[l+6], p[l+8], p[l1+1], p[l1+3], p[l1+5], p[l1+7], p[l1+2], p[l1+4], p[l1+6], p[l1+8], p[l2+1], p[l2+3], p[l2+5], p[l2+7], p[l2+2], p[l2+4], p[l2+6], p[l2+8], p[l3+1], p[l3+3], p[l3+5], p[l3+7], p[l3+2], p[l3+4], p[l3+6], p[l3+8]) @fastmath begin vo = vi * mat po[l+1] += vo[1] po[l+3] += vo[2] po[l+5] += vo[3] po[l+7] += vo[4] po[l+2] += vo[5] po[l+4] += vo[6] po[l+6] += vo[7] po[l+8] += vo[8] po[l1+1] += vo[9] po[l1+3] += vo[10] po[l1+5] += vo[11] po[l1+7] += vo[12] po[l1+2] += vo[13] po[l1+4] += vo[14] po[l1+6] += vo[15] po[l1+8] += vo[16] po[l2+1] += vo[17] po[l2+3] += vo[18] po[l2+5] += vo[19] po[l2+7] += vo[20] po[l2+2] += vo[21] po[l2+4] += vo[22] po[l2+6] += vo[23] po[l2+8] += vo[24] po[l3+1] += vo[25] po[l3+3] += vo[26] po[l3+5] += vo[27] po[l3+7] += vo[28] po[l3+2] += vo[29] po[l3+4] += vo[30] po[l3+6] += vo[31] po[l3+8] += vo[32] end # @fastmath p[l+1], p[l+3], p[l+5], p[l+7], # p[l+2], p[l+4], p[l+6], p[l+8], # p[l1+1], p[l1+3], p[l1+5], p[l1+7], # p[l1+2], p[l1+4], p[l1+6], p[l1+8], # p[l2+1], p[l2+3], p[l2+5], p[l2+7], # p[l2+2], p[l2+4], p[l2+6], p[l2+8], # p[l3+1], p[l3+3], p[l3+5], p[l3+7], # p[l3+2], p[l3+4], p[l3+6], p[l3+8] = vi * mat end end f2H(ist::Int, ifn::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) l1 = l + posb l2 = l + posc l3 = l2 + posb vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+5], p[l+6], p[l+3], p[l+4], p[l+7], p[l+8], p[l1+1], p[l1+2], p[l1+5], p[l1+6], p[l1+3], p[l1+4], p[l1+7], p[l1+8], p[l2+1], p[l2+2], p[l2+5], p[l2+6], p[l2+3], p[l2+4], p[l2+7], p[l2+8], p[l3+1], p[l3+2], p[l3+5], p[l3+6], p[l3+3], p[l3+4], p[l3+7], p[l3+8]) @fastmath begin vo = vi * mat po[l+1] += vo[1] po[l+2] += vo[2] po[l+5] += vo[3] po[l+6] += vo[4] po[l+3] += vo[5] po[l+4] += vo[6] po[l+7] += vo[7] po[l+8] += vo[8] po[l1+1] += vo[9] po[l1+2] += vo[10] po[l1+5] += vo[11] po[l1+6] += vo[12] po[l1+3] += vo[13] po[l1+4] += vo[14] po[l1+7] += vo[15] po[l1+8] += vo[16] po[l2+1] += vo[17] po[l2+2] += vo[18] po[l2+5] += vo[19] po[l2+6] += vo[20] po[l2+3] += vo[21] po[l2+4] += vo[22] po[l2+7] += vo[23] po[l2+8] += vo[24] po[l3+1] += vo[25] po[l3+2] += vo[26] po[l3+5] += vo[27] po[l3+6] += vo[28] po[l3+3] += vo[29] po[l3+4] += vo[30] po[l3+7] += vo[31] po[l3+8] += vo[32] end # @fastmath p[l+1], p[l+2], p[l+5], p[l+6], # p[l+3], p[l+4], p[l+7], p[l+8], # p[l1+1], p[l1+2], p[l1+5], p[l1+6], # p[l1+3], p[l1+4], p[l1+7], p[l1+8], # p[l2+1], p[l2+2], p[l2+5], p[l2+6], # p[l2+3], p[l2+4], p[l2+7], p[l2+8], # p[l3+1], p[l3+2], p[l3+5], p[l3+6], # p[l3+3], p[l3+4], p[l3+7], p[l3+8] = vi * mat end end f3H(ist::Int, ifn::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) l1 = l + posb l2 = l + posc l3 = l2 + posb vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7], p[l1+8], p[l2+1], p[l2+2], p[l2+3], p[l2+4], p[l2+5], p[l2+6], p[l2+7], p[l2+8], p[l3+1], p[l3+2], p[l3+3], p[l3+4], p[l3+5], p[l3+6], p[l3+7], p[l3+8]) @fastmath begin vo = vi * mat po[l+1] += vo[1] po[l+2] += vo[2] po[l+3] += vo[3] po[l+4] += vo[4] po[l+5] += vo[5] po[l+6] += vo[6] po[l+7] += vo[7] po[l+8] += vo[8] po[l1+1] += vo[9] po[l1+2] += vo[10] po[l1+3] += vo[11] po[l1+4] += vo[12] po[l1+5] += vo[13] po[l1+6] += vo[14] po[l1+7] += vo[15] po[l1+8] += vo[16] po[l2+1] += vo[17] po[l2+2] += vo[18] po[l2+3] += vo[19] po[l2+4] += vo[20] po[l2+5] += vo[21] po[l2+6] += vo[22] po[l2+7] += vo[23] po[l2+8] += vo[24] po[l3+1] += vo[25] po[l3+2] += vo[26] po[l3+3] += vo[27] po[l3+4] += vo[28] po[l3+5] += vo[29] po[l3+6] += vo[30] po[l3+7] += vo[31] po[l3+8] += vo[32] end # @fastmath p[l+1], p[l+2], p[l+3], p[l+4], # p[l+5], p[l+6], p[l+7], p[l+8], # p[l1+1], p[l1+2], p[l1+3], p[l1+4], # p[l1+5], p[l1+6], p[l1+7], p[l1+8], # p[l2+1], p[l2+2], p[l2+3], p[l2+4], # p[l2+5], p[l2+6], p[l2+7], p[l2+8], # p[l3+1], p[l3+2], p[l3+3], p[l3+4], # p[l3+5], p[l3+6], p[l3+7], p[l3+8] = vi * mat end end if q1 == 1 f = f1H elseif q1 == 2 f = f2H elseif q1 == 3 f = f3H else error(""qubit position $q1 not allowed for LHH."") end (q2 > 3) || error(""qubit 2 position $q2 not allowed for LHH."") total_itr = div(L, 32) parallel_run(total_itr, Threads.nthreads(), f, sizej, sizel, mask0, mask1, mask2, U, v, vout) end """""" applys when q1, q2 <= 3 and q3 > 4, U is the transposed op """""" function _apply_threebody_gate_LLH!(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2, q3 = key sizej = 1 << (q3-1) mask0 = sizej - 1 mask1 = xor(L - 1, 2 * sizej - 1) f12H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{4, 8}(p[l+1], p[l+5], p[l+9], p[l+13], p[l+2], p[l+6], p[l+10], p[l+14], p[l+3], p[l+7], p[l+11], p[l+15], p[l+4], p[l+8], p[l+12], p[l+16], p[l1+1], p[l1+5], p[l1+9], p[l1+13], p[l1+2], p[l1+6], p[l1+10], p[l1+14], p[l1+3], p[l1+7], p[l1+11], p[l1+15], p[l1+4], p[l1+8], p[l1+12], p[l1+16]) @fastmath begin vo = vi * mat po[l+1] += vo[1] po[l+5] += vo[2] po[l+9] += vo[3] po[l+13] += vo[4] po[l+2] += vo[5] po[l+6] += vo[6] po[l+10] += vo[7] po[l+14] += vo[8] po[l+3] += vo[9] po[l+7] += vo[10] po[l+11] += vo[11] po[l+15] += vo[12] po[l+4] += vo[13] po[l+8] += vo[14] po[l+12] += vo[15] po[l+16] += vo[16] po[l1+1] += vo[17] po[l1+5] += vo[18] po[l1+9] += vo[19] po[l1+13] += vo[20] po[l1+2] += vo[21] po[l1+6] += vo[22] po[l1+10] += vo[23] po[l1+14] += vo[24] po[l1+3] += vo[25] po[l1+7] += vo[26] po[l1+11] += vo[27] po[l1+15] += vo[28] po[l1+4] += vo[29] po[l1+8] += vo[30] po[l1+12] += vo[31] po[l1+16] += vo[32] end # @fastmath p[l+1], p[l+5], p[l+9], p[l+13], # p[l+2], p[l+6], p[l+10], p[l+14], # p[l+3], p[l+7], p[l+11], p[l+15], # p[l+4], p[l+8], p[l+12], p[l+16], # p[l1+1], p[l1+5], p[l1+9], p[l1+13], # p[l1+2], p[l1+6], p[l1+10], p[l1+14], # p[l1+3], p[l1+7], p[l1+11], p[l1+15], # p[l1+4], p[l1+8], p[l1+12], p[l1+16] = vi * mat end end f13H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{4, 8}(p[l+1], p[l+3], p[l+9], p[l+11], p[l+2], p[l+4], p[l+10], p[l+12], p[l+5], p[l+7], p[l+13], p[l+15], p[l+6], p[l+8], p[l+14], p[l+16], p[l1+1], p[l1+3], p[l1+9], p[l1+11], p[l1+2], p[l1+4], p[l1+10], p[l1+12], p[l1+5], p[l1+7], p[l1+13], p[l1+15], p[l1+6], p[l1+8], p[l1+14], p[l1+16]) @fastmath begin vo = vi * mat po[l+1] += vo[1] po[l+3] += vo[2] po[l+9] += vo[3] po[l+11] += vo[4] po[l+2] += vo[5] po[l+4] += vo[6] po[l+10] += vo[7] po[l+12] += vo[8] po[l+5] += vo[9] po[l+7] += vo[10] po[l+13] += vo[11] po[l+15] += vo[12] po[l+6] += vo[13] po[l+8] += vo[14] po[l+14] += vo[15] po[l+16] += vo[16] po[l1+1] += vo[17] po[l1+3] += vo[18] po[l1+9] += vo[19] po[l1+11] += vo[20] po[l1+2] += vo[21] po[l1+4] += vo[22] po[l1+10] += vo[23] po[l1+12] += vo[24] po[l1+5] += vo[25] po[l1+7] += vo[26] po[l1+13] += vo[27] po[l1+15] += vo[28] po[l1+6] += vo[29] po[l1+8] += vo[30] po[l1+14] += vo[31] po[l1+16] += vo[32] end # @fastmath p[l+1], p[l+3], p[l+9], p[l+11], # p[l+2], p[l+4], p[l+10], p[l+12], # p[l+5], p[l+7], p[l+13], p[l+15], # p[l+6], p[l+8], p[l+14], p[l+16], # p[l1+1], p[l1+3], p[l1+9], p[l1+11], # p[l1+2], p[l1+4], p[l1+10], p[l1+12], # p[l1+5], p[l1+7], p[l1+13], p[l1+15], # p[l1+6], p[l1+8], p[l1+14], p[l1+16] = vi * mat end end f23H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+9], p[l+10], p[l+3], p[l+4], p[l+11], p[l+12], p[l+5], p[l+6], p[l+13], p[l+14], p[l+7], p[l+8], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+9], p[l1+10], p[l1+3], p[l1+4], p[l1+11], p[l1+12], p[l1+5], p[l1+6], p[l1+13], p[l1+14], p[l1+7], p[l1+8], p[l1+15], p[l1+16]) @fastmath begin vo = vi * mat po[l+1] += vo[1] po[l+2] += vo[2] po[l+9] += vo[3] po[l+10] += vo[4] po[l+3] += vo[5] po[l+4] += vo[6] po[l+11] += vo[7] po[l+12] += vo[8] po[l+5] += vo[9] po[l+6] += vo[10] po[l+13] += vo[11] po[l+14] += vo[12] po[l+7] += vo[13] po[l+8] += vo[14] po[l+15] += vo[15] po[l+16] += vo[16] po[l1+1] += vo[17] po[l1+2] += vo[18] po[l1+9] += vo[19] po[l1+10] += vo[20] po[l1+3] += vo[21] po[l1+4] += vo[22] po[l1+11] += vo[23] po[l1+12] += vo[24] po[l1+5] += vo[25] po[l1+6] += vo[26] po[l1+13] += vo[27] po[l1+14] += vo[28] po[l1+7] += vo[29] po[l1+8] += vo[30] po[l1+15] += vo[31] po[l1+16] += vo[32] end # @fastmath p[l+1], p[l+2], p[l+9], p[l+10], # p[l+3], p[l+4], p[l+11], p[l+12], # p[l+5], p[l+6], p[l+13], p[l+14], # p[l+7], p[l+8], p[l+15], p[l+16], # p[l1+1], p[l1+2], p[l1+9], p[l1+10], # p[l1+3], p[l1+4], p[l1+11], p[l1+12], # p[l1+5], p[l1+6], p[l1+13], p[l1+14], # p[l1+7], p[l1+8], p[l1+15], p[l1+16] = vi * mat end end if q1 == 1 && q2 == 2 f = f12H elseif q1 == 1 && q2 == 3 f = f13H elseif q1 == 2 && q2 == 3 f = f23H else error(""qubit position $q1 not allowed for LH."") end total_itr = div(L, 32) parallel_run(total_itr, Threads.nthreads(), f, sizej, mask0, mask1, U, v, vout) end """""" applys when both keys <= 4 """""" function _apply_threebody_gate_LLL!(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2, q3 = key f123(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{8, 4}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l+9], p[l+10], p[l+11], p[l+12], p[l+13], p[l+14], p[l+15], p[l+16], p[l+17], p[l+18], p[l+19], p[l+20], p[l+21], p[l+22], p[l+23], p[l+24], p[l+25], p[l+26], p[l+27], p[l+28], p[l+29], p[l+30], p[l+31]) @fastmath begin vo = mat * vi po[l] += vo[1] po[l+1] += vo[2] po[l+2] += vo[3] po[l+3] += vo[4] po[l+4] += vo[5] po[l+5] += vo[6] po[l+6] += vo[7] po[l+7] += vo[8] po[l+8] += vo[9] po[l+9] += vo[10] po[l+10] += vo[11] po[l+11] += vo[12] po[l+12] += vo[13] po[l+13] += vo[14] po[l+14] += vo[15] po[l+15] += vo[16] po[l+16] += vo[17] po[l+17] += vo[18] po[l+18] += vo[19] po[l+19] += vo[20] po[l+20] += vo[21] po[l+21] += vo[22] po[l+22] += vo[23] po[l+23] += vo[24] po[l+24] += vo[25] po[l+25] += vo[26] po[l+26] += vo[27] po[l+27] += vo[28] po[l+28] += vo[29] po[l+29] += vo[30] po[l+30] += vo[31] po[l+31] += vo[32] end # @fastmath p[l:(l+31)]= mat * vi end end f124(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+3], p[l+4], p[l+9], p[l+10], p[l+11], p[l+12], p[l+5], p[l+6], p[l+7], p[l+8], p[l+13], p[l+14], p[l+15], p[l+16], p[l+17], p[l+18], p[l+19], p[l+20], p[l+25], p[l+26], p[l+27], p[l+28], p[l+21], p[l+22], p[l+23], p[l+24], p[l+29], p[l+30], p[l+31], p[l+32]) @fastmath begin vo = mat * vi po[l+1] += vo[1] po[l+2] += vo[2] po[l+3] += vo[3] po[l+4] += vo[4] po[l+9] += vo[5] po[l+10] += vo[6] po[l+11] += vo[7] po[l+12] += vo[8] po[l+5] += vo[9] po[l+6] += vo[10] po[l+7] += vo[11] po[l+8] += vo[12] po[l+13] += vo[13] po[l+14] += vo[14] po[l+15] += vo[15] po[l+16] += vo[16] po[l+17] += vo[17] po[l+18] += vo[18] po[l+19] += vo[19] po[l+20] += vo[20] po[l+25] += vo[21] po[l+26] += vo[22] po[l+27] += vo[23] po[l+28] += vo[24] po[l+21] += vo[25] po[l+22] += vo[26] po[l+23] += vo[27] po[l+24] += vo[28] po[l+29] += vo[29] po[l+30] += vo[30] po[l+31] += vo[31] po[l+32] += vo[32] end # @fastmath p[l+1], p[l+2], p[l+3], p[l+4], p[l+9], p[l+10], p[l+11], p[l+12], # p[l+5], p[l+6], p[l+7], p[l+8], p[l+13], p[l+14], p[l+15], p[l+16], # p[l+17], p[l+18], p[l+19], p[l+20], p[l+25], p[l+26], p[l+27], p[l+28], # p[l+21], p[l+22], p[l+23], p[l+24], p[l+29], p[l+30], p[l+31], p[l+32] = mat * vi end end f134(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+5], p[l+6], p[l+9], p[l+10], p[l+13], p[l+14], p[l+3], p[l+4], p[l+7], p[l+8], p[l+11], p[l+12], p[l+15], p[l+16], p[l+17], p[l+18], p[l+21], p[l+22], p[l+25], p[l+26], p[l+29], p[l+30], p[l+19], p[l+20], p[l+23], p[l+24], p[l+27], p[l+28], p[l+31], p[l+32]) @fastmath begin vo = mat * vi po[l+1] += vo[1] po[l+2] += vo[2] po[l+5] += vo[3] po[l+6] += vo[4] po[l+9] += vo[5] po[l+10] += vo[6] po[l+13] += vo[7] po[l+14] += vo[8] po[l+3] += vo[9] po[l+4] += vo[10] po[l+7] += vo[11] po[l+8] += vo[12] po[l+11] += vo[13] po[l+12] += vo[14] po[l+15] += vo[15] po[l+16] += vo[16] po[l+17] += vo[17] po[l+18] += vo[18] po[l+21] += vo[19] po[l+22] += vo[20] po[l+25] += vo[21] po[l+26] += vo[22] po[l+29] += vo[23] po[l+30] += vo[24] po[l+19] += vo[25] po[l+20] += vo[26] po[l+23] += vo[27] po[l+24] += vo[28] po[l+27] += vo[29] po[l+28] += vo[30] po[l+31] += vo[31] po[l+32] += vo[32] end # @fastmath p[l+1], p[l+2], p[l+5], p[l+6], p[l+9], p[l+10], p[l+13], p[l+14], # p[l+3], p[l+4], p[l+7], p[l+8], p[l+11], p[l+12], p[l+15], p[l+16], # p[l+17], p[l+18], p[l+21], p[l+22], p[l+25], p[l+26], p[l+29], p[l+30], # p[l+19], p[l+20], p[l+23], p[l+24], p[l+27], p[l+28], p[l+31], p[l+32] = mat * vi end end f234(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector, po::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{8, 4}(p[l+1], p[l+3], p[l+5], p[l+7], p[l+9], p[l+11], p[l+13], p[l+15], p[l+2], p[l+4], p[l+6], p[l+8], p[l+10], p[l+12], p[l+14], p[l+16], p[l+17], p[l+19], p[l+21], p[l+23], p[l+25], p[l+27], p[l+29], p[l+31], p[l+18], p[l+20], p[l+22], p[l+24], p[l+26], p[l+28], p[l+30], p[l+32]) @fastmath begin vo = mat * vi po[l+1] += vo[1] po[l+3] += vo[2] po[l+5] += vo[3] po[l+7] += vo[4] po[l+9] += vo[5] po[l+11] += vo[6] po[l+13] += vo[7] po[l+15] += vo[8] po[l+2] += vo[9] po[l+4] += vo[10] po[l+6] += vo[11] po[l+8] += vo[12] po[l+10] += vo[13] po[l+12] += vo[14] po[l+14] += vo[15] po[l+16] += vo[16] po[l+17] += vo[17] po[l+19] += vo[18] po[l+21] += vo[19] po[l+23] += vo[20] po[l+25] += vo[21] po[l+27] += vo[22] po[l+29] += vo[23] po[l+31] += vo[24] po[l+18] += vo[25] po[l+20] += vo[26] po[l+22] += vo[27] po[l+24] += vo[28] po[l+26] += vo[29] po[l+28] += vo[30] po[l+30] += vo[31] po[l+32] += vo[32] end # @fastmath p[l+1], p[l+3], p[l+5], p[l+7], p[l+9], p[l+11], p[l+13], p[l+15], # p[l+2], p[l+4], p[l+6], p[l+8], p[l+10], p[l+12], p[l+14], p[l+16], # p[l+17], p[l+19], p[l+21], p[l+23], p[l+25], p[l+27], p[l+29], p[l+31], # p[l+18], p[l+20], p[l+22], p[l+24], p[l+26], p[l+28], p[l+30], p[l+32] = mat * vi end end if q1==1 && q2 == 2 && q3 == 3 f = f123 elseif q1==1 && q2 == 2 && q3 == 4 f = f124 elseif q1==1 && q2 == 3 && q3 == 4 f = f134 elseif q1==2 && q2 == 3 && q3 == 4 f = f234 else error(""qubit position $q1 and $q2 not allowed for LL."") end total_itr = div(L, 32) parallel_run(total_itr, Threads.nthreads(), f, U, v, vout) end function _apply_gate_threaded2!(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) q0, q1, q2 = key if q0 > 2 return _apply_threebody_gate_HHH!(key, SMatrix{8,8, eltype(v)}(transpose(U)), v, vout) elseif q1 > 3 return _apply_threebody_gate_LHH!(key, SMatrix{8,8, eltype(v)}(transpose(U)), v, vout) elseif q2 > 4 return _apply_threebody_gate_LLH!(key, SMatrix{8,8, eltype(v)}(transpose(U)), v, vout) else return _apply_threebody_gate_LLL!(key, SMatrix{8,8, eltype(v)}(U), v, vout) end end # assume vout is initialized with 0s function _apply_threaded_util!(m::QubitsOperator, v::AbstractVector, vout::AbstractVector) for (k, bond) in m.data _apply_gate_threaded2!(k, _get_mat(length(k), bond), v, vout) end return vout end ","Julia" "Conjugate","guochu/VQC.jl","src/hamiltonian/apply_qterms/short_range_serial.jl",".jl","3442","99"," function _apply_gate_2_impl!(key::Int, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) pos = 2^(key-1) strid = pos * 2 for i in 0:strid:(L-1) @inbounds for j in 0:(pos-1) l = i + j + 1 vi1 = v[l] vi2 = v[l + pos] @fastmath vo1 = U[1,1] * vi1 + U[1,2] * vi2 @fastmath vo2 = U[2,1] * vi1 + U[2,2] * vi2 vout[l] += vo1 vout[l + pos] += vo2 end end end _apply_gate_2!(key::Int, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) = _apply_gate_2_impl!( key, SMatrix{2,2, eltype(v)}(U), v, vout) _apply_gate_2!(key::Tuple{Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) = _apply_gate_2!( key[1], U, v, vout) function _apply_gate_2_impl!(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) # U = Matrix(transpose(reshape(U, 4, 4))) L = length(v) q1, q2 = key pos1, pos2 = 2^(q1-1), 2^(q2-1) stride1, stride2 = 2 * pos1, 2 * pos2 for i in 0:stride2:(L-1) for j in 0:stride1:(pos2-1) @inbounds for k in 0:(pos1-1) l = i + j + k + 1 vi = SVector(v[l], v[l + pos1], v[l + pos2], v[l + pos1 + pos2]) @fastmath vo = U * vi vout[l] += vo[1] vout[l + pos1] += vo[2] vout[l + pos2] += vo[3] vout[l + pos1 + pos2] += vo[4] end end end end _apply_gate_2!(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) = _apply_gate_2_impl!( key, SMatrix{4,4, eltype(v)}(U), v, vout) function _apply_gate_2_impl!(key::Tuple{Int, Int, Int}, m::AbstractMatrix, v::AbstractVector, vout::AbstractVector) L = length(v) q1, q2, q3 = key pos1, pos2, pos3 = 2^(q1-1), 2^(q2-1), 2^(q3-1) stride1, stride2, stride3 = 2 * pos1, 2 * pos2, 2 * pos3 for h in 0:stride3:(L-1) for i in 0:stride2:(pos3-1) for j in 0:stride1:(pos2-1) @inbounds for k in 0:(pos1-1) l000 = h + i + j + k + 1 l100 = l000 + pos1 l010 = l000 + pos2 l110 = l010 + pos1 l001 = l000 + pos3 l101 = l001 + pos1 l011 = l001 + pos2 l111 = l011 + pos1 vi = SVector(v[l000], v[l100], v[l010], v[l110], v[l001], v[l101], v[l011], v[l111]) @fastmath begin vo = m * vi vout[l000] += vo[1] vout[l100] += vo[2] vout[l010] += vo[3] vout[l110] += vo[4] vout[l001] += vo[5] vout[l101] += vo[6] vout[l011] += vo[7] vout[l111] += vo[8] end end end end end end _apply_gate_2!(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector, vout::AbstractVector) = _apply_gate_2_impl!( key, SMatrix{8,8, eltype(v)}(U), v, vout) function _apply_serial_util!(m::QubitsOperator, v::AbstractVector, vout::AbstractVector) for (k, bond) in m.data _apply_gate_2!(k, _get_mat(length(k), bond), v, vout) end return vout end ","Julia" "Conjugate","guochu/VQC.jl","src/applygates/applygates.jl",".jl","89","5"," include(""generic/generic.jl"") include(""specific/specific.jl"") include(""apply_qmaps.jl"")","Julia" "Conjugate","guochu/VQC.jl","src/applygates/apply_qmaps.jl",".jl","2439","87"," """""" apply!(x::QuantumMap, state::DensityMatrix) apply a generc quantum channel on the quantum state """""" function apply!(x::QuantumMap, state::DensityMatrix) @assert _check_pos_range(x, nqubits(state)) T = eltype(state) if (eltype(x) <: Complex) && (T <: Real) state = convert(DensityMatrix{Complex{T}}, state) end _qmap_apply_threaded!(x, state.data, nqubits(state)) return state end apply!(x::QuantumMap, state::StateVector) = apply!(x, DensityMatrix(state)) """""" apply_dagger!(x::QuantumMap, state::DensityMatrix) apply the hermitian conjugate of quantum map on rho this function is needed for auto-differentiation """""" function apply_dagger!(x::QuantumMap, state::DensityMatrix) @assert _check_pos_range(x, nqubits(state)) T = eltype(state) if (eltype(x) <: Complex) && (T <: Real) state = convert(DensityMatrix{Complex{T}}, state) end _qmap_apply_dagger_threaded!(x, state.data, nqubits(state)) return state end """""" apply_inverse!(x::QuantumMap, state::DensityMatrix) apply the inverse of quantum map on rho, this requires the supermatrix to be invertable. this function is needed for auto-differentiation """""" function apply_inverse!(x::QuantumMap, state::DensityMatrix) @assert _check_pos_range(x, nqubits(state)) T = eltype(state) if (eltype(x) <: Complex) && (T <: Real) state = convert(DensityMatrix{Complex{T}}, state) end _qmap_apply_inverse_threaded!(x, state.data, nqubits(state)) return state end # unitary gate operation on density matrix function _qmap_apply_threaded!(x::QuantumMap{N}, s::AbstractVector, n::Int) where N pos = ordered_positions(x) pos2 = ntuple(i->pos[i]+n, N) all_pos = (pos..., pos2...) m = ordered_supermat(x) if length(s) >= 32 _apply_gate_threaded2!(all_pos, m, s) else _apply_gate_2!(all_pos, m, s) end end function _qmap_apply_dagger_threaded!(x::QuantumMap{N}, s::AbstractVector, n::Int) where N pos = ordered_positions(x) pos2 = ntuple(i->pos[i]+n, N) all_pos = (pos..., pos2...) m = ordered_supermat(x) if length(s) >= 32 _apply_gate_threaded2!(all_pos, m', s) else _apply_gate_2!(all_pos, m', s) end end function _qmap_apply_inverse_threaded!(x::QuantumMap{N}, s::AbstractVector, n::Int) where N pos = ordered_positions(x) pos2 = ntuple(i->pos[i]+n, N) all_pos = (pos..., pos2...) m = ordered_supermat(x) if length(s) >= 32 _apply_gate_threaded2!(all_pos, inv(m), s) else _apply_gate_2!(all_pos, inv(m), s) end end ","Julia" "Conjugate","guochu/VQC.jl","src/applygates/specific/phasegate.jl",".jl","1323","44"," """""" specialization for PHASEGate """""" function apply_threaded!(gt::PHASEGate, v::AbstractVector) (length(v) < 32) && return apply_serial!(gt, v) L = length(v) sizek = 1 << (ordered_positions(gt)[1] - 1) mask0 = sizek - 1 mask1 = xor(L - 1, 2 * sizek - 1) f(ist::Int, ifn::Int, pos::Int, m1::Int, m2::Int, alpha::Number, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (2 * i & m2) | (i & m1) + pos @fastmath p[l] *= alpha end end exp_phi = convert(eltype(v), exp(im * parameters(gt)[1] )) total_itr = div(L, 2) parallel_run(total_itr, Threads.nthreads(), f, sizek+1, mask0, mask1, exp_phi, v) end """""" specialization for XGate """""" function apply_threaded!(gt::XGate, v::AbstractVector) (length(v) < 32) && return apply_serial!(gt, v) L = length(v) sizek = 1 << (ordered_positions(gt)[1] - 1) mask0 = sizek - 1 mask1 = xor(L - 1, 2 * sizek - 1) f(ist::Int, ifn::Int, pos::Int, m1::Int, m2::Int, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (2 * i & m2) | (i & m1) + 1 l1 = l + pos @fastmath p[l], p[l1] = p[l1], p[l] end end total_itr = div(L, 2) parallel_run(total_itr, Threads.nthreads(), f, sizek, mask0, mask1, v) end ","Julia" "Conjugate","guochu/VQC.jl","src/applygates/specific/fredkingate.jl",".jl","3455","105"," function apply_threaded!(gt::FREDKINGate, v::AbstractVector) (length(v) < 32) && return apply_serial!(gt, v) L = length(v) q1, q2, q3 = ordered_positions(gt) pos1, pos2, pos3 = 1 << (q1-1), 1 << (q2-1), 1 << (q3-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(pos3 - 1, 2 * pos2 - 1) mask3 = xor(L - 1, 2 * pos3 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") f_f(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, m4::Int, p::AbstractVector) = begin @inbounds for i in ist:ifn l000 = (8 * i & m4) | (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 # l100 = l000 + posa l010 = l000 + posb l110 = l010 + posa l001 = l000 + posc l101 = l001 + posa # l011 = l001 + posb # l111 = l011 + posa @fastmath p[l110], p[l101] = p[l101], p[l110] end end f_m(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, m4::Int, p::AbstractVector) = begin @inbounds for i in ist:ifn l000 = (8 * i & m4) | (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 # l100 = l000 + posa l010 = l000 + posb l110 = l010 + posa l001 = l000 + posc # l101 = l001 + posa l011 = l001 + posb # l111 = l011 + posa @fastmath p[l110], p[l011] = p[l011], p[l110] end end f_e(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, m4::Int, p::AbstractVector) = begin @inbounds for i in ist:ifn l000 = (8 * i & m4) | (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 # l100 = l000 + posa # l010 = l000 + posb # l110 = l010 + posa l001 = l000 + posc l101 = l001 + posa l011 = l001 + posb # l111 = l011 + posa @fastmath p[l101], p[l011] = p[l011], p[l101] end end target = positions(gt)[1] if target == q1 f = f_f elseif target == q2 f = f_m elseif target == q3 f = f_e else error(""target $target does not exist in $key."") end total_itr = div(L, 8) parallel_run(total_itr, Threads.nthreads(), f, pos1, pos2, pos3, mask0, mask1, mask2, mask3, v) end function apply_threaded!(gt::CCPHASEGate, v::AbstractVector) (length(v) < 32) && return apply_serial!(gt, v) L = length(v) q1, q2, q3 = ordered_positions(gt) pos1, pos2, pos3 = 1 << (q1-1), 1 << (q2-1), 1 << (q3-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(pos3 - 1, 2 * pos2 - 1) mask3 = xor(L - 1, 2 * pos3 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") f(ist::Int, ifn::Int, posabc1::Int, m1::Int, m2::Int, m3::Int, m4::Int, alpha::Number, p::AbstractVector) = begin @inbounds for i in ist:ifn l111 = (8 * i & m4) | (4 * i & m3) | (2 * i & m2) | (i & m1) + posabc1 @fastmath p[l111] *= alpha end end exp_phi = convert(eltype(v), exp(im * parameters(gt)[1] )) total_itr = div(L, 8) parallel_run(total_itr, Threads.nthreads(), f, pos1+pos2+pos3+1, mask0, mask1, mask2, mask3, exp_phi, v) end ","Julia" "Conjugate","guochu/VQC.jl","src/applygates/specific/specific.jl",".jl","116","7"," include(""swapgates.jl"") # specialized gates include(""phasegate.jl"") include(""czgate.jl"") include(""fredkingate.jl"")","Julia" "Conjugate","guochu/VQC.jl","src/applygates/specific/swapgates.jl",".jl","1763","50"," function apply_threaded!(gt::SWAPGate, v::AbstractVector) (length(v) < 32) && return apply_serial!(gt, v) L = length(v) q1, q2 = ordered_positions(gt) pos1, pos2 = 1 << (q1-1), 1 << (q2-1) mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(L - 1, 2 * pos2 - 1) f(ist::Int, ifn::Int, posa::Int, posb::Int, m1::Int, m2::Int, m3::Int, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 l1 = l + posa l2 = l + posb p[l1], p[l2] = p[l2], p[l1] end end total_itr = div(L, 4) parallel_run(total_itr, Threads.nthreads(), f, pos1, pos2, mask0, mask1, mask2, v) end function _apply_iswap_util!(gt, v::AbstractVector, coef::Number) L = length(v) q1, q2 = ordered_positions(gt) pos1, pos2 = 1 << (q1-1), 1 << (q2-1) mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(L - 1, 2 * pos2 - 1) f(ist::Int, ifn::Int, posa::Int, posb::Int, m1::Int, m2::Int, m3::Int, coeff::Number, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 l1 = l + posa l2 = l + posb @fastmath p[l1], p[l2] = coeff*p[l2], coeff*p[l1] end end total_itr = div(L, 4) parallel_run(total_itr, Threads.nthreads(), f, pos1, pos2, mask0, mask1, mask2, convert(eltype(v), coef), v) end apply_threaded!(gt::iSWAPGate, v::AbstractVector) = (length(v) >= 32) ? _apply_iswap_util!( gt, v, im) : apply_serial!(gt, v) apply_threaded!(gt::AdjointQuantumGate{iSWAPGate}, v::AbstractVector) = (length(v) >= 32) ? _apply_iswap_util!( gt, v, -im) : apply_serial!(gt, v) ","Julia" "Conjugate","guochu/VQC.jl","src/applygates/specific/czgate.jl",".jl","2746","96"," """""" specialized for CZ gate """""" function apply_threaded!(gt::CZGate, v::AbstractVector) (length(v) < 32) && return apply_serial!(gt, v) L = length(v) q1, q2 = ordered_positions(gt) pos1, pos2 = 1 << (q1-1), 1 << (q2-1) mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(L - 1, 2 * pos2 - 1) f(ist::Int, ifn::Int, posab1::Int, m1::Int, m2::Int, m3::Int, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (4 * i & m3) | (2 * i & m2) | (i & m1) + posab1 p[l] = -p[l] end end total_itr = div(L, 4) parallel_run(total_itr, Threads.nthreads(), f, pos1+pos2+1, mask0, mask1, mask2, v) end """""" specialized for CNOT gate """""" function apply_threaded!(gt::CNOTGate, v::AbstractVector) (length(v) < 32) && return apply_serial!(gt, v) L = length(v) q1, q2 = ordered_positions(gt) pos1, pos2 = 1 << (q1-1), 1 << (q2-1) mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(L - 1, 2 * pos2 - 1) f_f(ist::Int, ifn::Int, posa::Int, posb::Int, m1::Int, m2::Int, m3::Int, p::AbstractVector) = begin @inbounds for i in ist:ifn l00 = (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 l10 = l00 + posa l01 = l00 + posb l11 = l01 + posa p[l10], p[l11] = p[l11], p[l10] end end f_e(ist::Int, ifn::Int, posa::Int, posb::Int, m1::Int, m2::Int, m3::Int, p::AbstractVector) = begin @inbounds for i in ist:ifn l00 = (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 l10 = l00 + posa l01 = l00 + posb l11 = l01 + posa p[l01], p[l11] = p[l11], p[l01] end end if positions(gt)[1] == q1 f = f_f else f = f_e end total_itr = div(L, 4) parallel_run(total_itr, Threads.nthreads(), f, pos1, pos2, mask0, mask1, mask2, v) end """""" specialized for CPHASE gate """""" function apply_threaded!(gt::CPHASEGate, v::AbstractVector) (length(v) < 32) && return apply_serial!(gt, v) L = length(v) q1, q2 = ordered_positions(gt) pos1, pos2 = 1 << (q1-1), 1 << (q2-1) mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(L - 1, 2 * pos2 - 1) f(ist::Int, ifn::Int, posab1::Int, m1::Int, m2::Int, m3::Int, alpha::Number, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (4 * i & m3) | (2 * i & m2) | (i & m1) + posab1 @fastmath p[l] *= alpha end end exp_phi = convert(eltype(v), exp(im * parameters(gt)[1] )) total_itr = div(L, 4) parallel_run(total_itr, Threads.nthreads(), f, pos1+pos2+1, mask0, mask1, mask2, exp_phi, v) end ","Julia" "Conjugate","guochu/VQC.jl","src/applygates/generic/threaded_long_range.jl",".jl","5741","135","# experimental support for 4-qubit and 5-qubit gate operation function _apply_fourbody_gate_impl!(key::Tuple{Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2, q3, q4 = key pos1, pos2, pos3, pos4 = 1 << (q1-1), 1 << (q2-1), 1 << (q3-1), 1 << (q4-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(pos3 - 1, 2 * pos2 - 1) mask3 = xor(pos4 - 1, 2 * pos3 - 1) mask4 = xor(L - 1, 2 * pos4 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") f(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, posd::Int, m1::Int, m2::Int, m3::Int, m4::Int, m5::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l0000 = (16 * i & m5) | (8 * i & m4) | (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 l1000 = l0000 + posa l0100 = l0000 + posb l0010 = l0000 + posc l0001 = l0000 + posd l1100 = l0100 + posa l1010 = l0010 + posa l1001 = l1000 + posd l0110 = l0010 + posb l0101 = l0100 + posd l0011 = l0010 + posd l1110 = l1100 + posc l1101 = l1100 + posd l1011 = l1010 + posd l0111 = l0110 + posd l1111 = l1110 + posd # println(""$l000, $l100, $l010, $l110, $l001, $l101, $l011, $l111"") vi = SVector(p[l0000], p[l1000], p[l0100], p[l1100], p[l0010], p[l1010], p[l0110], p[l1110], p[l0001], p[l1001], p[l0101], p[l1101], p[l0011], p[l1011], p[l0111], p[l1111]) @fastmath p[l0000], p[l1000], p[l0100], p[l1100], p[l0010], p[l1010], p[l0110], p[l1110], p[l0001], p[l1001], p[l0101], p[l1101], p[l0011], p[l1011], p[l0111], p[l1111] = mat * vi end end total_itr = div(L, 16) parallel_run(total_itr, Threads.nthreads(), f, pos1, pos2, pos3, pos4, mask0, mask1, mask2, mask3, mask4, U, v) end _apply_gate_threaded2!(key::Tuple{Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) = _apply_fourbody_gate_impl!( key, SMatrix{16,16, eltype(v)}(U), v) # used in apply_serial when n = 4 _apply_gate_2!(key::Tuple{Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) = _apply_gate_threaded2!(key, U, v) # This takes forever to compile function _apply_fivebody_gate_impl!(key::Tuple{Int, Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2, q3, q4, q5 = key pos1, pos2, pos3, pos4, pos5 = 1 << (q1-1), 1 << (q2-1), 1 << (q3-1), 1 << (q4-1), 1 << (q5-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(pos3 - 1, 2 * pos2 - 1) mask3 = xor(pos4 - 1, 2 * pos3 - 1) mask4 = xor(pos5 - 1, 2 * pos4 - 1) mask5 = xor(L - 1, 2 * pos5 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") function f(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, posd::Int, pose::Int, m1::Int, m2::Int, m3::Int, m4::Int, m5::Int, m6::Int, mat::AbstractMatrix, p::AbstractVector) @inbounds for i in ist:ifn l00000 = (32 * i & m6) | (16 * i & m5) | (8 * i & m4) | (4 * i & m3) | (2 * i & m2) | (i & m1) + 1 l10000 = l00000 + posa l01000 = l00000 + posb l00100 = l00000 + posc l00010 = l00000 + posd l00001 = l00000 + pose l11000 = l01000 + posa l10100 = l00100 + posa l10010 = l10000 + posd l10001 = l10000 + pose l01100 = l00100 + posb l01010 = l01000 + posd l01001 = l01000 + pose l00110 = l00100 + posd l00101 = l00100 + pose l00011 = l00010 + pose l11100 = l11000 + posc l11010 = l11000 + posd l11001 = l11000 + pose l10110 = l10100 + posd l10101 = l10100 + pose l10011 = l10010 + pose l01110 = l01100 + posd l01101 = l01100 + pose l01011 = l01010 + pose l00111 = l00110 + pose l11110 = l11100 + posd l11101 = l11100 + pose l11011 = l11010 + pose l10111 = l10110 + pose l01111 = l01110 + pose l11111 = l11110 + pose # println(""$l000, $l100, $l010, $l110, $l001, $l101, $l011, $l111"") vi = SVector(p[l00000], p[l10000], p[l01000], p[l11000], p[l00100], p[l10100], p[l01100], p[l11100], p[l00010], p[l10010], p[l01010], p[l11010], p[l00110], p[l10110], p[l01110], p[l11110], p[l00001], p[l10001], p[l01001], p[l11001], p[l00101], p[l10101], p[l01101], p[l11101], p[l00011], p[l10011], p[l01011], p[l11011], p[l00111], p[l10111], p[l01111], p[l11111]) @fastmath p[l00000], p[l10000], p[l01000], p[l11000], p[l00100], p[l10100], p[l01100], p[l11100], p[l00010], p[l10010], p[l01010], p[l11010], p[l00110], p[l10110], p[l01110], p[l11110], p[l00001], p[l10001], p[l01001], p[l11001], p[l00101], p[l10101], p[l01101], p[l11101], p[l00011], p[l10011], p[l01011], p[l11011], p[l00111], p[l10111], p[l01111], p[l11111] = mat * vi end end total_itr = div(L, 32) parallel_run(total_itr, Threads.nthreads(), f, pos1, pos2, pos3, pos4, pos5, mask0, mask1, mask2, mask3, mask4, mask5, U, v) end _apply_gate_threaded2!(key::Tuple{Int, Int, Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) = _apply_fivebody_gate_impl!( key, SMatrix{32,32, eltype(v)}(U), v) ","Julia" "Conjugate","guochu/VQC.jl","src/applygates/generic/threaded_short_range.jl",".jl","34508","768","# one, two, three-qubit gate operations """""" applys when key > 3, U is the transposed op """""" function _apply_onebody_gate_H!(key::Int, U::AbstractMatrix, v::AbstractVector) L = length(v) sizek = 1 << (key - 1) mask0 = sizek - 1 mask1 = xor(L - 1, 2 * sizek - 1) f(ist::Int, ifn::Int, pos::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (16 * i & m2) | (8 * i & m1) + 1 l1 = l + pos vi = SMatrix{8, 2}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l1], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7]) @fastmath p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l1], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7] = vi * mat end end total_itr = div(L, 16) # n_threads = Threads.nthreads() # if (total_itr >= MIN_SIZE) && (n_threads > 1) # # println(""2*****************************"") # nave, resi, jobs = partition_jobs(total_itr, n_threads) # Threads.@threads for s in 1:n_threads # ist = jobs[s] # ifn = jobs[s+1] - 1 # f(ist, ifn, sizek, mask0, mask1, U, v) # end # else # # println(""1*****************************"") # f(0, total_itr-1, sizek, mask0, mask1, U, v) # end parallel_run(total_itr, Threads.nthreads(), f, sizek, mask0, mask1, U, v) end """""" applys when key <= 3, U is the transposed op """""" function _apply_onebody_gate_L!(key::Int, U::AbstractMatrix, v::AbstractVector) L = length(v) f1(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = 16 * i + 1 vi = SMatrix{2, 8}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l+9], p[l+10], p[l+11], p[l+12], p[l+13], p[l+14], p[l+15]) @fastmath p[l:(l+15)]= mat * vi end end f2(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = 16 * i + 1 vi = SMatrix{2, 8}(p[l], p[l+2], p[l+1], p[l+3], p[l+4], p[l+6], p[l+5], p[l+7], p[l+8], p[l+10], p[l+9], p[l+11], p[l+12], p[l+14], p[l+13], p[l+15]) @fastmath p[l], p[l+2], p[l+1], p[l+3], p[l+4], p[l+6], p[l+5], p[l+7], p[l+8], p[l+10], p[l+9], p[l+11], p[l+12], p[l+14], p[l+13], p[l+15] = mat * vi end end f3(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = 16 * i + 1 vi = SMatrix{2, 8}(p[l], p[l+4], p[l+1], p[l+5], p[l+2], p[l+6], p[l+3], p[l+7], p[l+8], p[l+12], p[l+9], p[l+13], p[l+10], p[l+14], p[l+11], p[l+15]) @fastmath p[l], p[l+4], p[l+1], p[l+5], p[l+2], p[l+6], p[l+3], p[l+7], p[l+8], p[l+12], p[l+9], p[l+13], p[l+10], p[l+14], p[l+11], p[l+15] = mat * vi end end if key == 1 f = f1 elseif key == 2 f = f2 elseif key == 3 f = f3 else error(""qubit position $key not allowed for L."") end total_itr = div(L, 16) # n_threads = Threads.nthreads() # if (total_itr >= MIN_SIZE) && (n_threads > 1) # # println(""2*****************************"") # nave, resi, jobs = partition_jobs(total_itr, n_threads) # Threads.@threads for s in 1:n_threads # ist = jobs[s] # ifn = jobs[s+1] - 1 # f(ist, ifn, U, v) # end # else # # println(""1*****************************"") # f(0, total_itr-1, U, v) # end parallel_run(total_itr, Threads.nthreads(), f, U, v) end function _apply_gate_threaded2!(q0::Int, U::AbstractMatrix, v::AbstractVector) if q0 > 3 return _apply_onebody_gate_H!(q0, SMatrix{2,2, eltype(v)}(transpose(U)), v) else return _apply_onebody_gate_L!(q0, SMatrix{2,2, eltype(v)}(U), v) end end _apply_gate_threaded2!(q0::Tuple{Int}, U::AbstractMatrix, v::AbstractVector) = _apply_gate_threaded2!(q0[1], U, v) """""" applys when both keys > 3, U is the transposed op """""" function _apply_twobody_gate_HH!(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2 = key pos1, pos2 = 1 << (q1-1), 1 << (q2-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(L - 1, 2 * pos2 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") total_itr = div(L, 32) f(ist::Int, ifn::Int, posa::Int, posb::Int, m1::Int, m2::Int, m3::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) + 1 # l = div(l, 2) + 1 l1 = l + posa l2 = l + posb l3 = l2 + posa # println(""l0=$l, l1=$l1, l2=$l2, l3=$l3"") vi = SMatrix{8, 4}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l1], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7], p[l2], p[l2+1], p[l2+2], p[l2+3], p[l2+4], p[l2+5], p[l2+6], p[l2+7], p[l3], p[l3+1], p[l3+2], p[l3+3], p[l3+4], p[l3+5], p[l3+6], p[l3+7]) @fastmath p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l1], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7], p[l2], p[l2+1], p[l2+2], p[l2+3], p[l2+4], p[l2+5], p[l2+6], p[l2+7], p[l3], p[l3+1], p[l3+2], p[l3+3], p[l3+4], p[l3+5], p[l3+6], p[l3+7] = vi * mat end end # n_threads = Threads.nthreads() # if (total_itr >= MIN_SIZE) && (n_threads > 1) # # println(""2*****************************"") # nave, resi, jobs = partition_jobs(total_itr, n_threads) # Threads.@threads for s in 1:n_threads # ist = jobs[s] # ifn = jobs[s+1] - 1 # f(ist, ifn, pos1, pos2, mask0, mask1, mask2, U, v) # end # else # # println(""1*****************************"") # f(0, total_itr-1, pos1, pos2, mask0, mask1, mask2, U, v) # end parallel_run(total_itr, Threads.nthreads(), f, pos1, pos2, mask0, mask1, mask2, U, v) end """""" applys when q1 <= 3 and q2 > 4, U is the transposed op """""" function _apply_twobody_gate_LH!(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2 = key sizej = 1 << (q2-1) mask0 = sizej - 1 mask1 = xor(L - 1, 2 * sizej - 1) f1H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{8, 4}(p[l+1], p[l+3], p[l+5], p[l+7], p[l+9], p[l+11], p[l+13], p[l+15], p[l+2], p[l+4], p[l+6], p[l+8], p[l+10], p[l+12], p[l+14], p[l+16], p[l1+1], p[l1+3], p[l1+5], p[l1+7], p[l1+9], p[l1+11], p[l1+13], p[l1+15], p[l1+2], p[l1+4], p[l1+6], p[l1+8], p[l1+10], p[l1+12], p[l1+14], p[l1+16]) @fastmath p[l+1], p[l+3], p[l+5], p[l+7], p[l+9], p[l+11], p[l+13], p[l+15], p[l+2], p[l+4], p[l+6], p[l+8], p[l+10], p[l+12], p[l+14], p[l+16], p[l1+1], p[l1+3], p[l1+5], p[l1+7], p[l1+9], p[l1+11], p[l1+13], p[l1+15], p[l1+2], p[l1+4], p[l1+6], p[l1+8], p[l1+10], p[l1+12], p[l1+14], p[l1+16] = vi * mat end end f2H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+5], p[l+6], p[l+9], p[l+10], p[l+13], p[l+14], p[l+3], p[l+4], p[l+7], p[l+8], p[l+11], p[l+12], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+5], p[l1+6], p[l1+9], p[l1+10], p[l1+13], p[l1+14], p[l1+3], p[l1+4], p[l1+7], p[l1+8], p[l1+11], p[l1+12], p[l1+15], p[l1+16]) @fastmath p[l+1], p[l+2], p[l+5], p[l+6], p[l+9], p[l+10], p[l+13], p[l+14], p[l+3], p[l+4], p[l+7], p[l+8], p[l+11], p[l+12], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+5], p[l1+6], p[l1+9], p[l1+10], p[l1+13], p[l1+14], p[l1+3], p[l1+4], p[l1+7], p[l1+8], p[l1+11], p[l1+12], p[l1+15], p[l1+16] = vi * mat end end f3H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+3], p[l+4], p[l+9], p[l+10], p[l+11], p[l+12], p[l+5], p[l+6], p[l+7], p[l+8], p[l+13], p[l+14], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+9], p[l1+10], p[l1+11], p[l1+12], p[l1+5], p[l1+6], p[l1+7], p[l1+8], p[l1+13], p[l1+14], p[l1+15], p[l1+16]) @fastmath p[l+1], p[l+2], p[l+3], p[l+4], p[l+9], p[l+10], p[l+11], p[l+12], p[l+5], p[l+6], p[l+7], p[l+8], p[l+13], p[l+14], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+9], p[l1+10], p[l1+11], p[l1+12], p[l1+5], p[l1+6], p[l1+7], p[l1+8], p[l1+13], p[l1+14], p[l1+15], p[l1+16] = vi * mat end end if q1 == 1 f = f1H elseif q1 == 2 f = f2H elseif q1 == 3 f = f3H else error(""qubit position $q1 not allowed for LH."") end total_itr = div(L, 32) # n_threads = Threads.nthreads() # if (total_itr >= MIN_SIZE) && (n_threads > 1) # # println(""2*****************************"") # nave, resi, jobs = partition_jobs(total_itr, n_threads) # Threads.@threads for s in 1:n_threads # ist = jobs[s] # ifn = jobs[s+1] - 1 # f(ist, ifn, sizej, mask0, mask1, U, v) # end # else # # println(""1*****************************"") # f(0, total_itr-1, sizej, mask0, mask1, U, v) # end parallel_run(total_itr, Threads.nthreads(), f, sizej, mask0, mask1, U, v) end """""" applys when both keys <= 4 """""" function _apply_twobody_gate_LL!(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2 = key f12(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{4, 8}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l+9], p[l+10], p[l+11], p[l+12], p[l+13], p[l+14], p[l+15], p[l+16], p[l+17], p[l+18], p[l+19], p[l+20], p[l+21], p[l+22], p[l+23], p[l+24], p[l+25], p[l+26], p[l+27], p[l+28], p[l+29], p[l+30], p[l+31]) @fastmath p[l:(l+31)]= mat * vi end end f13(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{4, 8}(p[l], p[l+1], p[l+4], p[l+5], p[l+2], p[l+3], p[l+6], p[l+7], p[l+8], p[l+9], p[l+12], p[l+13], p[l+10], p[l+11], p[l+14], p[l+15], p[l+16], p[l+17], p[l+20], p[l+21], p[l+18], p[l+19], p[l+22], p[l+23], p[l+24], p[l+25], p[l+28], p[l+29], p[l+26], p[l+27], p[l+30], p[l+31]) @fastmath p[l], p[l+1], p[l+4], p[l+5], p[l+2], p[l+3], p[l+6], p[l+7], p[l+8], p[l+9], p[l+12], p[l+13], p[l+10], p[l+11], p[l+14], p[l+15], p[l+16], p[l+17], p[l+20], p[l+21], p[l+18], p[l+19], p[l+22], p[l+23], p[l+24], p[l+25], p[l+28], p[l+29], p[l+26], p[l+27], p[l+30], p[l+31] = mat * vi end end f14(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+9], p[l+10], p[l+3], p[l+4], p[l+11], p[l+12], p[l+5], p[l+6], p[l+13], p[l+14], p[l+7], p[l+8], p[l+15], p[l+16], p[l+17], p[l+18], p[l+25], p[l+26], p[l+19], p[l+20], p[l+27], p[l+28], p[l+21], p[l+22], p[l+29], p[l+30], p[l+23], p[l+24], p[l+31], p[l+32]) @fastmath p[l+1], p[l+2], p[l+9], p[l+10], p[l+3], p[l+4], p[l+11], p[l+12], p[l+5], p[l+6], p[l+13], p[l+14], p[l+7], p[l+8], p[l+15], p[l+16], p[l+17], p[l+18], p[l+25], p[l+26], p[l+19], p[l+20], p[l+27], p[l+28], p[l+21], p[l+22], p[l+29], p[l+30], p[l+23], p[l+24], p[l+31], p[l+32] = mat * vi end end f23(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{4, 8}(p[l], p[l+2], p[l+4], p[l+6], p[l+1], p[l+3], p[l+5], p[l+7], p[l+8], p[l+10], p[l+12], p[l+14], p[l+9], p[l+11], p[l+13], p[l+15], p[l+16], p[l+18], p[l+20], p[l+22], p[l+17], p[l+19], p[l+21], p[l+23], p[l+24], p[l+26], p[l+28], p[l+30], p[l+25], p[l+27], p[l+29], p[l+31]) @fastmath p[l], p[l+2], p[l+4], p[l+6], p[l+1], p[l+3], p[l+5], p[l+7], p[l+8], p[l+10], p[l+12], p[l+14], p[l+9], p[l+11], p[l+13], p[l+15], p[l+16], p[l+18], p[l+20], p[l+22], p[l+17], p[l+19], p[l+21], p[l+23], p[l+24], p[l+26], p[l+28], p[l+30], p[l+25], p[l+27], p[l+29], p[l+31] = mat * vi end end f24(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{4, 8}(p[l+1], p[l+3], p[l+9], p[l+11], p[l+2], p[l+4], p[l+10], p[l+12], p[l+5], p[l+7], p[l+13], p[l+15], p[l+6], p[l+8], p[l+14], p[l+16], p[l+17], p[l+19], p[l+25], p[l+27], p[l+18], p[l+20], p[l+26], p[l+28], p[l+21], p[l+23], p[l+29], p[l+31], p[l+22], p[l+24], p[l+30], p[l+32]) @fastmath p[l+1], p[l+3], p[l+9], p[l+11], p[l+2], p[l+4], p[l+10], p[l+12], p[l+5], p[l+7], p[l+13], p[l+15], p[l+6], p[l+8], p[l+14], p[l+16], p[l+17], p[l+19], p[l+25], p[l+27], p[l+18], p[l+20], p[l+26], p[l+28], p[l+21], p[l+23], p[l+29], p[l+31], p[l+22], p[l+24], p[l+30], p[l+32] = mat * vi end end f34(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{4, 8}(p[l+1], p[l+5], p[l+9], p[l+13], p[l+2], p[l+6], p[l+10], p[l+14], p[l+3], p[l+7], p[l+11], p[l+15], p[l+4], p[l+8], p[l+12], p[l+16], p[l+17], p[l+21], p[l+25], p[l+29], p[l+18], p[l+22], p[l+26], p[l+30], p[l+19], p[l+23], p[l+27], p[l+31], p[l+20], p[l+24], p[l+28], p[l+32]) @fastmath p[l+1], p[l+5], p[l+9], p[l+13], p[l+2], p[l+6], p[l+10], p[l+14], p[l+3], p[l+7], p[l+11], p[l+15], p[l+4], p[l+8], p[l+12], p[l+16], p[l+17], p[l+21], p[l+25], p[l+29], p[l+18], p[l+22], p[l+26], p[l+30], p[l+19], p[l+23], p[l+27], p[l+31], p[l+20], p[l+24], p[l+28], p[l+32] = mat * vi end end if q1==1 && q2 == 2 f = f12 elseif q1==1 && q2 == 3 f = f13 elseif q1==1 && q2 == 4 f = f14 elseif q1==2 && q2 == 3 f = f23 elseif q1==2 && q2 == 4 f = f24 elseif q1==3 && q2 == 4 f = f34 else error(""qubit position $q1 and $q2 not allowed for LL."") end total_itr = div(L, 32) # n_threads = Threads.nthreads() # if (total_itr >= MIN_SIZE) && (n_threads > 1) # nave, resi, jobs = partition_jobs(total_itr, n_threads) # Threads.@threads for s in 1:n_threads # ist = jobs[s] # ifn = jobs[s+1] - 1 # f(ist, ifn, U, v) # end # else # f(0, total_itr-1, U, v) # end parallel_run(total_itr, Threads.nthreads(), f, U, v) end function _apply_gate_threaded2!(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector) q0, q1 = key if q0 > 3 return _apply_twobody_gate_HH!(key, SMatrix{4,4, eltype(v)}(transpose(U)), v) elseif q1 > 4 return _apply_twobody_gate_LH!(key, SMatrix{4,4, eltype(v)}(transpose(U)), v) else return _apply_twobody_gate_LL!(key, SMatrix{4,4, eltype(v)}(U), v) end end """""" applys when both keys > 2, U is assumed to be transposed """""" function _apply_threebody_gate_HHH!(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2, q3 = key pos1, pos2, pos3 = 1 << (q1-1), 1 << (q2-1), 1 << (q3-1) # stride2, stride3 = pos1 << 1, pos2 << 1 mask0 = pos1 - 1 mask1 = xor(pos2 - 1, 2 * pos1 - 1) mask2 = xor(pos3 - 1, 2 * pos2 - 1) mask3 = xor(L - 1, 2 * pos3 - 1) # println(""pos1=$pos1, pos2=$pos2, m0=$mask0, m1=$mask1, m2=$mask2"") total_itr = div(L, 32) f(ist::Int, ifn::Int, posa::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, m4::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l000 = (32 * i & m4) | (16 * i & m3) | (8 * i & m2) | (4 * i & m1) + 1 l100 = l000 + posa l010 = l000 + posb l110 = l010 + posa l001 = l000 + posc l101 = l001 + posa l011 = l001 + posb l111 = l011 + posa # println(""$l000, $l100, $l010, $l110, $l001, $l101, $l011, $l111"") vi = SMatrix{4, 8}(p[l000], p[l000+1], p[l000+2], p[l000+3], p[l100], p[l100+1], p[l100+2], p[l100+3], p[l010], p[l010+1], p[l010+2], p[l010+3], p[l110], p[l110+1], p[l110+2], p[l110+3], p[l001], p[l001+1], p[l001+2], p[l001+3], p[l101], p[l101+1], p[l101+2], p[l101+3], p[l011], p[l011+1], p[l011+2], p[l011+3], p[l111], p[l111+1], p[l111+2], p[l111+3]) @fastmath p[l000], p[l000+1], p[l000+2], p[l000+3], p[l100], p[l100+1], p[l100+2], p[l100+3], p[l010], p[l010+1], p[l010+2], p[l010+3], p[l110], p[l110+1], p[l110+2], p[l110+3], p[l001], p[l001+1], p[l001+2], p[l001+3], p[l101], p[l101+1], p[l101+2], p[l101+3], p[l011], p[l011+1], p[l011+2], p[l011+3], p[l111], p[l111+1], p[l111+2], p[l111+3] = vi * mat end end # n_threads = Threads.nthreads() # if (total_itr >= MIN_SIZE) && (n_threads > 1) # # println(""2*****************************"") # nave, resi, jobs = partition_jobs(total_itr, n_threads) # Threads.@threads for s in 1:n_threads # ist = jobs[s] # ifn = jobs[s+1] - 1 # f(ist, ifn, pos1, pos2, pos3, mask0, mask1, mask2, mask3, U, v) # end # else # # println(""1*****************************"") # f(0, total_itr-1, pos1, pos2, pos3, mask0, mask1, mask2, mask3, U, v) # end parallel_run(total_itr, Threads.nthreads(), f, pos1, pos2, pos3, mask0, mask1, mask2, mask3, U, v) end """""" applys when q1 <= 2 and q2 > 3, U is the transposed op """""" function _apply_threebody_gate_LHH!(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2, q3 = key sizej, sizel = 1 << (q2-1), 1 << (q3-1) mask0 = sizej - 1 mask1 = xor(sizel - 1, 2 * sizej - 1) mask2 = xor(L-1, 2 * sizel - 1) f1H(ist::Int, ifn::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) l1 = l + posb l2 = l + posc l3 = l2 + posb # println(""$l, $l1, $l2, $l3"") vi = SMatrix{4, 8}(p[l+1], p[l+3], p[l+5], p[l+7], p[l+2], p[l+4], p[l+6], p[l+8], p[l1+1], p[l1+3], p[l1+5], p[l1+7], p[l1+2], p[l1+4], p[l1+6], p[l1+8], p[l2+1], p[l2+3], p[l2+5], p[l2+7], p[l2+2], p[l2+4], p[l2+6], p[l2+8], p[l3+1], p[l3+3], p[l3+5], p[l3+7], p[l3+2], p[l3+4], p[l3+6], p[l3+8]) @fastmath p[l+1], p[l+3], p[l+5], p[l+7], p[l+2], p[l+4], p[l+6], p[l+8], p[l1+1], p[l1+3], p[l1+5], p[l1+7], p[l1+2], p[l1+4], p[l1+6], p[l1+8], p[l2+1], p[l2+3], p[l2+5], p[l2+7], p[l2+2], p[l2+4], p[l2+6], p[l2+8], p[l3+1], p[l3+3], p[l3+5], p[l3+7], p[l3+2], p[l3+4], p[l3+6], p[l3+8] = vi * mat end end f2H(ist::Int, ifn::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) l1 = l + posb l2 = l + posc l3 = l2 + posb vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+5], p[l+6], p[l+3], p[l+4], p[l+7], p[l+8], p[l1+1], p[l1+2], p[l1+5], p[l1+6], p[l1+3], p[l1+4], p[l1+7], p[l1+8], p[l2+1], p[l2+2], p[l2+5], p[l2+6], p[l2+3], p[l2+4], p[l2+7], p[l2+8], p[l3+1], p[l3+2], p[l3+5], p[l3+6], p[l3+3], p[l3+4], p[l3+7], p[l3+8]) @fastmath p[l+1], p[l+2], p[l+5], p[l+6], p[l+3], p[l+4], p[l+7], p[l+8], p[l1+1], p[l1+2], p[l1+5], p[l1+6], p[l1+3], p[l1+4], p[l1+7], p[l1+8], p[l2+1], p[l2+2], p[l2+5], p[l2+6], p[l2+3], p[l2+4], p[l2+7], p[l2+8], p[l3+1], p[l3+2], p[l3+5], p[l3+6], p[l3+3], p[l3+4], p[l3+7], p[l3+8] = vi * mat end end f3H(ist::Int, ifn::Int, posb::Int, posc::Int, m1::Int, m2::Int, m3::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m3) | (16 * i & m2) | (8 * i & m1) l1 = l + posb l2 = l + posc l3 = l2 + posb vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7], p[l1+8], p[l2+1], p[l2+2], p[l2+3], p[l2+4], p[l2+5], p[l2+6], p[l2+7], p[l2+8], p[l3+1], p[l3+2], p[l3+3], p[l3+4], p[l3+5], p[l3+6], p[l3+7], p[l3+8]) @fastmath p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l1+1], p[l1+2], p[l1+3], p[l1+4], p[l1+5], p[l1+6], p[l1+7], p[l1+8], p[l2+1], p[l2+2], p[l2+3], p[l2+4], p[l2+5], p[l2+6], p[l2+7], p[l2+8], p[l3+1], p[l3+2], p[l3+3], p[l3+4], p[l3+5], p[l3+6], p[l3+7], p[l3+8] = vi * mat end end if q1 == 1 f = f1H elseif q1 == 2 f = f2H elseif q1 == 3 f = f3H else error(""qubit position $q1 not allowed for LHH."") end (q2 > 3) || error(""qubit 2 position $q2 not allowed for LHH."") total_itr = div(L, 32) # n_threads = Threads.nthreads() # if (total_itr >= MIN_SIZE) && (n_threads > 1) # # println(""2*****************************"") # nave, resi, jobs = partition_jobs(total_itr, n_threads) # Threads.@threads for s in 1:n_threads # ist = jobs[s] # ifn = jobs[s+1] - 1 # f(ist, ifn, sizej, sizel, mask0, mask1, mask2, U, v) # end # else # # println(""1*****************************"") # f(0, total_itr-1, sizej, sizel, mask0, mask1, mask2, U, v) # end parallel_run(total_itr, Threads.nthreads(), f, sizej, sizel, mask0, mask1, mask2, U, v) end """""" applys when q1, q2 <= 3 and q3 > 4, U is the transposed op """""" function _apply_threebody_gate_LLH!(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2, q3 = key sizej = 1 << (q3-1) mask0 = sizej - 1 mask1 = xor(L - 1, 2 * sizej - 1) f12H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{4, 8}(p[l+1], p[l+5], p[l+9], p[l+13], p[l+2], p[l+6], p[l+10], p[l+14], p[l+3], p[l+7], p[l+11], p[l+15], p[l+4], p[l+8], p[l+12], p[l+16], p[l1+1], p[l1+5], p[l1+9], p[l1+13], p[l1+2], p[l1+6], p[l1+10], p[l1+14], p[l1+3], p[l1+7], p[l1+11], p[l1+15], p[l1+4], p[l1+8], p[l1+12], p[l1+16]) @fastmath p[l+1], p[l+5], p[l+9], p[l+13], p[l+2], p[l+6], p[l+10], p[l+14], p[l+3], p[l+7], p[l+11], p[l+15], p[l+4], p[l+8], p[l+12], p[l+16], p[l1+1], p[l1+5], p[l1+9], p[l1+13], p[l1+2], p[l1+6], p[l1+10], p[l1+14], p[l1+3], p[l1+7], p[l1+11], p[l1+15], p[l1+4], p[l1+8], p[l1+12], p[l1+16] = vi * mat end end f13H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{4, 8}(p[l+1], p[l+3], p[l+9], p[l+11], p[l+2], p[l+4], p[l+10], p[l+12], p[l+5], p[l+7], p[l+13], p[l+15], p[l+6], p[l+8], p[l+14], p[l+16], p[l1+1], p[l1+3], p[l1+9], p[l1+11], p[l1+2], p[l1+4], p[l1+10], p[l1+12], p[l1+5], p[l1+7], p[l1+13], p[l1+15], p[l1+6], p[l1+8], p[l1+14], p[l1+16]) @fastmath p[l+1], p[l+3], p[l+9], p[l+11], p[l+2], p[l+4], p[l+10], p[l+12], p[l+5], p[l+7], p[l+13], p[l+15], p[l+6], p[l+8], p[l+14], p[l+16], p[l1+1], p[l1+3], p[l1+9], p[l1+11], p[l1+2], p[l1+4], p[l1+10], p[l1+12], p[l1+5], p[l1+7], p[l1+13], p[l1+15], p[l1+6], p[l1+8], p[l1+14], p[l1+16] = vi * mat end end f23H(ist::Int, ifn::Int, posb::Int, m1::Int, m2::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = (32 * i & m2) | (16 * i & m1) l1 = l + posb # println(""l=$l, l1=$l1"") vi = SMatrix{4, 8}(p[l+1], p[l+2], p[l+9], p[l+10], p[l+3], p[l+4], p[l+11], p[l+12], p[l+5], p[l+6], p[l+13], p[l+14], p[l+7], p[l+8], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+9], p[l1+10], p[l1+3], p[l1+4], p[l1+11], p[l1+12], p[l1+5], p[l1+6], p[l1+13], p[l1+14], p[l1+7], p[l1+8], p[l1+15], p[l1+16]) @fastmath p[l+1], p[l+2], p[l+9], p[l+10], p[l+3], p[l+4], p[l+11], p[l+12], p[l+5], p[l+6], p[l+13], p[l+14], p[l+7], p[l+8], p[l+15], p[l+16], p[l1+1], p[l1+2], p[l1+9], p[l1+10], p[l1+3], p[l1+4], p[l1+11], p[l1+12], p[l1+5], p[l1+6], p[l1+13], p[l1+14], p[l1+7], p[l1+8], p[l1+15], p[l1+16] = vi * mat end end if q1 == 1 && q2 == 2 f = f12H elseif q1 == 1 && q2 == 3 f = f13H elseif q1 == 2 && q2 == 3 f = f23H else error(""qubit position $q1 not allowed for LH."") end total_itr = div(L, 32) # n_threads = Threads.nthreads() # if (total_itr >= MIN_SIZE) && (n_threads > 1) # # println(""2*****************************"") # nave, resi, jobs = partition_jobs(total_itr, n_threads) # Threads.@threads for s in 1:n_threads # ist = jobs[s] # ifn = jobs[s+1] - 1 # f(ist, ifn, sizej, mask0, mask1, U, v) # end # else # # println(""1*****************************"") # f(0, total_itr-1, sizej, mask0, mask1, U, v) # end parallel_run(total_itr, Threads.nthreads(), f, sizej, mask0, mask1, U, v) end """""" applys when both keys <= 4 """""" function _apply_threebody_gate_LLL!(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2, q3 = key f123(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i + 1 vi = SMatrix{8, 4}(p[l], p[l+1], p[l+2], p[l+3], p[l+4], p[l+5], p[l+6], p[l+7], p[l+8], p[l+9], p[l+10], p[l+11], p[l+12], p[l+13], p[l+14], p[l+15], p[l+16], p[l+17], p[l+18], p[l+19], p[l+20], p[l+21], p[l+22], p[l+23], p[l+24], p[l+25], p[l+26], p[l+27], p[l+28], p[l+29], p[l+30], p[l+31]) @fastmath p[l:(l+31)]= mat * vi end end f124(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+3], p[l+4], p[l+9], p[l+10], p[l+11], p[l+12], p[l+5], p[l+6], p[l+7], p[l+8], p[l+13], p[l+14], p[l+15], p[l+16], p[l+17], p[l+18], p[l+19], p[l+20], p[l+25], p[l+26], p[l+27], p[l+28], p[l+21], p[l+22], p[l+23], p[l+24], p[l+29], p[l+30], p[l+31], p[l+32]) @fastmath p[l+1], p[l+2], p[l+3], p[l+4], p[l+9], p[l+10], p[l+11], p[l+12], p[l+5], p[l+6], p[l+7], p[l+8], p[l+13], p[l+14], p[l+15], p[l+16], p[l+17], p[l+18], p[l+19], p[l+20], p[l+25], p[l+26], p[l+27], p[l+28], p[l+21], p[l+22], p[l+23], p[l+24], p[l+29], p[l+30], p[l+31], p[l+32] = mat * vi end end f134(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{8, 4}(p[l+1], p[l+2], p[l+5], p[l+6], p[l+9], p[l+10], p[l+13], p[l+14], p[l+3], p[l+4], p[l+7], p[l+8], p[l+11], p[l+12], p[l+15], p[l+16], p[l+17], p[l+18], p[l+21], p[l+22], p[l+25], p[l+26], p[l+29], p[l+30], p[l+19], p[l+20], p[l+23], p[l+24], p[l+27], p[l+28], p[l+31], p[l+32]) @fastmath p[l+1], p[l+2], p[l+5], p[l+6], p[l+9], p[l+10], p[l+13], p[l+14], p[l+3], p[l+4], p[l+7], p[l+8], p[l+11], p[l+12], p[l+15], p[l+16], p[l+17], p[l+18], p[l+21], p[l+22], p[l+25], p[l+26], p[l+29], p[l+30], p[l+19], p[l+20], p[l+23], p[l+24], p[l+27], p[l+28], p[l+31], p[l+32] = mat * vi end end f234(ist::Int, ifn::Int, mat::AbstractMatrix, p::AbstractVector) = begin @inbounds for i in ist:ifn l = 32 * i vi = SMatrix{8, 4}(p[l+1], p[l+3], p[l+5], p[l+7], p[l+9], p[l+11], p[l+13], p[l+15], p[l+2], p[l+4], p[l+6], p[l+8], p[l+10], p[l+12], p[l+14], p[l+16], p[l+17], p[l+19], p[l+21], p[l+23], p[l+25], p[l+27], p[l+29], p[l+31], p[l+18], p[l+20], p[l+22], p[l+24], p[l+26], p[l+28], p[l+30], p[l+32]) @fastmath p[l+1], p[l+3], p[l+5], p[l+7], p[l+9], p[l+11], p[l+13], p[l+15], p[l+2], p[l+4], p[l+6], p[l+8], p[l+10], p[l+12], p[l+14], p[l+16], p[l+17], p[l+19], p[l+21], p[l+23], p[l+25], p[l+27], p[l+29], p[l+31], p[l+18], p[l+20], p[l+22], p[l+24], p[l+26], p[l+28], p[l+30], p[l+32] = mat * vi end end if q1==1 && q2 == 2 && q3 == 3 f = f123 elseif q1==1 && q2 == 2 && q3 == 4 f = f124 elseif q1==1 && q2 == 3 && q3 == 4 f = f134 elseif q1==2 && q2 == 3 && q3 == 4 f = f234 else error(""qubit position $q1 and $q2 not allowed for LL."") end total_itr = div(L, 32) # n_threads = Threads.nthreads() # if (total_itr >= MIN_SIZE) && (n_threads > 1) # nave, resi, jobs = partition_jobs(total_itr, n_threads) # Threads.@threads for s in 1:n_threads # ist = jobs[s] # ifn = jobs[s+1] - 1 # f(ist, ifn, U, v) # end # else # f(0, total_itr-1, U, v) # end parallel_run(total_itr, Threads.nthreads(), f, U, v) end function _apply_gate_threaded2!(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) q0, q1, q2 = key if q0 > 2 return _apply_threebody_gate_HHH!(key, SMatrix{8,8, eltype(v)}(transpose(U)), v) elseif q1 > 3 return _apply_threebody_gate_LHH!(key, SMatrix{8,8, eltype(v)}(transpose(U)), v) elseif q2 > 4 return _apply_threebody_gate_LLH!(key, SMatrix{8,8, eltype(v)}(transpose(U)), v) else return _apply_threebody_gate_LLL!(key, SMatrix{8,8, eltype(v)}(U), v) end end ","Julia" "Conjugate","guochu/VQC.jl","src/applygates/generic/serial_short_range.jl",".jl","2549","75"," function _apply_gate_2_impl!(key::Int, U::AbstractMatrix, v::AbstractVector) L = length(v) pos = 2^(key-1) strid = pos * 2 for i in 0:strid:(L-1) @inbounds for j in 0:(pos-1) l = i + j + 1 vi1 = v[l] vi2 = v[l + pos] vo1 = U[1,1] * vi1 + U[1,2] * vi2 vo2 = U[2,1] * vi1 + U[2,2] * vi2 v[l] = vo1 v[l + pos] = vo2 end end end _apply_gate_2!(key::Int, U::AbstractMatrix, v::AbstractVector) = _apply_gate_2_impl!( key, SMatrix{2,2, eltype(v)}(U), v) _apply_gate_2!(key::Tuple{Int}, U::AbstractMatrix, v::AbstractVector) = _apply_gate_2!(key[1], U, v) function _apply_gate_2_impl!(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector) # U = Matrix(transpose(reshape(U, 4, 4))) L = length(v) q1, q2 = key pos1, pos2 = 2^(q1-1), 2^(q2-1) stride1, stride2 = 2 * pos1, 2 * pos2 for i in 0:stride2:(L-1) for j in 0:stride1:(pos2-1) @inbounds for k in 0:(pos1-1) l = i + j + k + 1 vi = SVector(v[l], v[l + pos1], v[l + pos2], v[l + pos1 + pos2]) v[l], v[l + pos1], v[l + pos2], v[l + pos1 + pos2] = U * vi end end end end function _apply_gate_2_impl!(key::Tuple{Int, Int, Int}, m::AbstractMatrix, v::AbstractVector) L = length(v) q1, q2, q3 = key pos1, pos2, pos3 = 2^(q1-1), 2^(q2-1), 2^(q3-1) stride1, stride2, stride3 = 2 * pos1, 2 * pos2, 2 * pos3 for h in 0:stride3:(L-1) for i in 0:stride2:(pos3-1) for j in 0:stride1:(pos2-1) @inbounds for k in 0:(pos1-1) l000 = h + i + j + k + 1 l100 = l000 + pos1 l010 = l000 + pos2 l110 = l010 + pos1 l001 = l000 + pos3 l101 = l001 + pos1 l011 = l001 + pos2 l111 = l011 + pos1 vi = SVector(v[l000], v[l100], v[l010], v[l110], v[l001], v[l101], v[l011], v[l111]) @fastmath v[l000], v[l100], v[l010], v[l110], v[l001], v[l101], v[l011], v[l111] = m * vi end end end end end _apply_gate_2!(key::Tuple{Int, Int}, U::AbstractMatrix, v::AbstractVector) = _apply_gate_2_impl!( key, SMatrix{4,4, eltype(v)}(U), v) _apply_gate_2!(key::Tuple{Int, Int, Int}, U::AbstractMatrix, v::AbstractVector) = _apply_gate_2_impl!( key, SMatrix{8,8, eltype(v)}(U), v) ","Julia" "Conjugate","guochu/VQC.jl","src/applygates/generic/generic.jl",".jl","1867","65"," include(""serial_short_range.jl"") include(""threaded_short_range.jl"") include(""threaded_long_range.jl"") function apply!(x::Gate, state::StateVector) @assert _check_pos_range(x, nqubits(state)) T = eltype(state) if (eltype(x) <: Complex) && (T <: Real) state = convert(StateVector{Complex{T}}, state) end apply_threaded!(x, storage(state)) return state end function apply!(x::Gate, state::DensityMatrix) @assert _check_pos_range(x, nqubits(state)) T = eltype(state) if (eltype(x) <: Complex) && (T <: Real) state = convert(DensityMatrix{Complex{T}}, state) end _dm_apply_threaded!(x, state.data, nqubits(state)) return state end function apply!(circuit::QCircuit, state::Union{StateVector, DensityMatrix}) for gate in circuit state = apply!(gate, state) end return state end Base.:*(circuit::QCircuit, state::Union{StateVector, DensityMatrix}) = apply!(circuit, copy(state)) function _check_pos_range(x, n::Int) pos = ordered_positions(x) (length(pos) > 5) && throw(""only implement 5-qubit gates and less currently."") return (pos[1] >= 1) && (pos[end] <= n) end apply_serial!(x::Gate, s::AbstractVector) = _apply_gate_2!(ordered_positions(x), ordered_mat(x), s) apply_serial!(x::Gate, state::StateVector) = (apply_serial!(x, storage(state)); state) """""" currently support mostly 5-qubit gate """""" apply_threaded!(x::Gate, s::AbstractVector) = (length(s) >= 32) ? _apply_gate_threaded2!(ordered_positions(x), ordered_mat(x), s) : apply_serial!(x, s) # unitary gate operation on density matrix function _dm_apply_threaded!(x::Gate{N}, s::AbstractVector, n::Int) where N pos = ordered_positions(x) m = ordered_mat(x) if length(s) >= 32 _apply_gate_threaded2!(pos, m, s) _apply_gate_threaded2!(ntuple(i->pos[i]+n, N), conj(m), s) else _apply_gate_2!(pos, m, s) _apply_gate_2!(ntuple(i->pos[i]+n, N), conj(m), s) end end ","Julia" "Conjugate","guochu/VQC.jl","test/check_high_qubit_gate.jl",".jl","8640","208"," function check_fourbody_single(::Type{T}, L::Int, j::Int, k::Int, l::Int, m::Int) where T state1 = rand_state(T, L) m1 = random_unitary(1) m2 = random_unitary(1) m3 = random_unitary(1) m4 = random_unitary(1) gate1 = from_external((j, k, l, m), kron(m1, m2, m3, m4)) h = QubitsTerm(j=>m1, k=>m2, l=>m3, m=>m4) state2 = matrix(L, h) * state1 apply!(gate1, state1) return maximum(abs.(storage(state1 - state2)) ) end function check_fourbody(::Type{T}, L::Int, i::Int, j::Int, k::Int, l::Int) where T errs = [] push!(errs, check_fourbody_single(ComplexF64, L, i,j,k,l)) push!(errs, check_fourbody_single(ComplexF64, L, i,j,l,k)) push!(errs, check_fourbody_single(ComplexF64, L, j,i,k,l)) push!(errs, check_fourbody_single(ComplexF64, L, j,i,l,k)) push!(errs, check_fourbody_single(ComplexF64, L, l,k,j,i)) push!(errs, check_fourbody_single(ComplexF64, L, k,i,l,j)) return all(errs .< 1.0e-6) end function check_fivebody_single(::Type{T}, L::Int, j::Int, k::Int, l::Int, m::Int, n::Int) where T state1 = rand_state(T, L) m1 = random_unitary(1) m2 = random_unitary(1) m3 = random_unitary(1) m4 = random_unitary(1) m5 = random_unitary(1) gate1 = from_external((j, k, l, m, n), kron(m1, m2, m3, m4, m5)) h = QubitsTerm(j=>m1, k=>m2, l=>m3, m=>m4, n=>m5) state2 = matrix(L, h) * state1 apply!(gate1, state1) return maximum(abs.(storage(state1 - state2)) ) end function check_fivebody(::Type{T}, L::Int, i::Int, j::Int, k::Int, l::Int, n::Int) where T errs = [] push!(errs, check_fivebody_single(ComplexF64, L, i,j,k,l,n)) push!(errs, check_fivebody_single(ComplexF64, L, i,j,l,n,k)) push!(errs, check_fivebody_single(ComplexF64, L, j,i,n,k,l)) push!(errs, check_fivebody_single(ComplexF64, L, j,n,i,l,k)) push!(errs, check_fivebody_single(ComplexF64, L, l,k,j,n,i)) push!(errs, check_fivebody_single(ComplexF64, L, n,k,i,l,j)) return all(errs .< 1.0e-6) end function check_qham_fourbody_single(::Type{T}, L::Int, j::Int, k::Int, l::Int, m::Int) where T state1 = rand_state(T, L) m1 = random_unitary(1) m2 = random_unitary(1) m3 = random_unitary(1) m4 = random_unitary(1) gate1 = from_external((j, k, l, m), kron(m1, m2, m3, m4)) h = QubitsTerm(j=>m1, k=>m2, l=>m3, m=>m4) state2 = h * state1 apply!(gate1, state1) return maximum(abs.(storage(state1 - state2)) ) end function check_qham_fourbody(::Type{T}, L::Int, i::Int, j::Int, k::Int, l::Int) where T errs = [] push!(errs, check_qham_fourbody_single(ComplexF64, L, i,j,k,l)) push!(errs, check_qham_fourbody_single(ComplexF64, L, i,j,l,k)) push!(errs, check_qham_fourbody_single(ComplexF64, L, j,i,k,l)) push!(errs, check_qham_fourbody_single(ComplexF64, L, j,i,l,k)) push!(errs, check_qham_fourbody_single(ComplexF64, L, l,k,j,i)) push!(errs, check_qham_fourbody_single(ComplexF64, L, k,i,l,j)) return all(errs .< 1.0e-6) end function check_qham_fivebody_single(::Type{T}, L::Int, j::Int, k::Int, l::Int, m::Int, n::Int) where T state1 = rand_state(T, L) m1 = random_unitary(1) m2 = random_unitary(1) m3 = random_unitary(1) m4 = random_unitary(1) m5 = random_unitary(1) gate1 = from_external((j, k, l, m, n), kron(m1, m2, m3, m4, m5)) h = QubitsTerm(j=>m1, k=>m2, l=>m3, m=>m4, n=>m5) state2 = h * state1 apply!(gate1, state1) return maximum(abs.(storage(state1 - state2)) ) end function check_qham_fivebody(::Type{T}, L::Int, i::Int, j::Int, k::Int, l::Int, n::Int) where T errs = [] push!(errs, check_qham_fivebody_single(ComplexF64, L, i,j,k,l,n)) push!(errs, check_qham_fivebody_single(ComplexF64, L, i,j,l,n,k)) push!(errs, check_qham_fivebody_single(ComplexF64, L, j,i,n,k,l)) push!(errs, check_qham_fivebody_single(ComplexF64, L, j,n,i,l,k)) push!(errs, check_qham_fivebody_single(ComplexF64, L, l,k,j,n,i)) push!(errs, check_qham_fivebody_single(ComplexF64, L, n,k,i,l,j)) return all(errs .< 1.0e-6) end function check_expec_fourbody_single(::Type{T}, L::Int, j::Int, k::Int, l::Int, m::Int) where T state = rand_state(T, L) m = QubitsTerm(j=>random_unitary(1), k=>random_unitary(1), l=>random_unitary(1), m=>random_unitary(1), coeff=0.9) return abs(expectation(m, state) - expectation(matrix(L, m), state)) end function check_expec_fourbody(::Type{T}, L::Int, i::Int, j::Int, k::Int, l::Int) where T errs = [] push!(errs, check_expec_fourbody_single(T, L, i,j,k,l)) push!(errs, check_expec_fourbody_single(T, L, i,j,l,k)) push!(errs, check_expec_fourbody_single(T, L, j,i,k,l)) push!(errs, check_expec_fourbody_single(T, L, j,i,l,k)) push!(errs, check_expec_fourbody_single(T, L, l,k,j,i)) push!(errs, check_expec_fourbody_single(T, L, k,i,l,j)) return all(errs .< 1.0e-6) end function check_expec_fourbody_single_2(::Type{T}, L::Int, j::Int, k::Int, l::Int, m::Int) where T state1 = rand_state(T, L) state2 = rand_state(T, L) m = QubitsTerm(j=>random_unitary(1), k=>random_unitary(1), l=>random_unitary(1), m=>random_unitary(1), coeff=0.7) return abs(expectation(state2, m, state1) - expectation(state2, matrix(L, m), state1)) end function check_expec_fourbody_2(::Type{T}, L::Int, i::Int, j::Int, k::Int, l::Int) where T errs = [] push!(errs, check_expec_fourbody_single_2(T, L, i,j,k,l)) push!(errs, check_expec_fourbody_single_2(T, L, i,j,l,k)) push!(errs, check_expec_fourbody_single_2(T, L, j,i,k,l)) push!(errs, check_expec_fourbody_single_2(T, L, j,i,l,k)) push!(errs, check_expec_fourbody_single_2(T, L, l,k,j,i)) push!(errs, check_expec_fourbody_single_2(T, L, k,i,l,j)) return all(errs .< 1.0e-6) end function check_expec_fivebody_single(::Type{T}, L::Int, j::Int, k::Int, l::Int, m::Int, n::Int) where T state = rand_state(T, L) m = QubitsTerm(j=>random_unitary(1), k=>random_unitary(1), l=>random_unitary(1), m=>random_unitary(1), n=>random_unitary(1), coeff=0.77) return abs(expectation(m, state) - expectation(matrix(L, m), state)) end function check_expec_fivebody_single_2(::Type{T}, L::Int, j::Int, k::Int, l::Int, m::Int, n::Int) where T state1 = rand_state(T, L) state2 = rand_state(T, L) m = QubitsTerm(j=>random_unitary(1), k=>random_unitary(1), l=>random_unitary(1), m=>random_unitary(1), n=>random_unitary(1), coeff=1.23) return abs(expectation(state2, m, state1) - expectation(state2, matrix(L, m), state1)) end function check_expec_fivebody(::Type{T}, L::Int, i::Int, j::Int, k::Int, l::Int, n::Int) where T errs = [] push!(errs, check_expec_fivebody_single(T, L, j,i,n,k,l)) push!(errs, check_expec_fivebody_single(T, L, j,n,i,l,k)) push!(errs, check_expec_fivebody_single(T, L, j,n,i,k,l)) push!(errs, check_expec_fivebody_single(T, L, l,k,j,n,i)) push!(errs, check_expec_fivebody_single(T, L, n,k,i,l,j)) push!(errs, check_expec_fivebody_single(T, L, i,j,k,l,n)) return all(errs .< 1.0e-6) end function check_expec_fivebody_2(::Type{T}, L::Int, i::Int, j::Int, k::Int, l::Int, n::Int) where T errs = [] push!(errs, check_expec_fivebody_single_2(T, L, j,i,n,k,l)) push!(errs, check_expec_fivebody_single_2(T, L, j,n,i,l,k)) push!(errs, check_expec_fivebody_single_2(T, L, j,n,i,k,l)) push!(errs, check_expec_fivebody_single_2(T, L, l,k,j,n,i)) push!(errs, check_expec_fivebody_single_2(T, L, n,k,i,l,j)) push!(errs, check_expec_fivebody_single_2(T, L, i,j,k,l,n)) return all(errs .< 1.0e-6) end @testset ""check high-qubit gate operations"" begin @test check_fourbody(ComplexF32, 4,1,2,3,4) @test check_fourbody(ComplexF64, 10,10,7,1,4) @test check_fivebody(ComplexF32, 5,1,2,3,5,4) @test check_fivebody(ComplexF32, 10,9,7,10,1,4) end @testset ""check high-qubit hamiltonian term operations"" begin @test check_qham_fourbody(ComplexF32, 4,1,2,3,4) @test check_qham_fourbody(ComplexF64, 10,6,7,1,4) @test check_qham_fivebody(ComplexF32, 5,1,2,3,5,4) @test check_qham_fivebody(ComplexF32, 11,9,11,10,1,4) end @testset ""check hamiltonion high-qubit term expectation value"" begin @test check_expec_fourbody(ComplexF64, 4, 1,2,3,4) @test check_expec_fourbody(ComplexF64, 9, 7,8,1,5) @test check_expec_fivebody(ComplexF64, 5, 1,2,3,5,4) @test check_expec_fivebody(ComplexF64, 10, 7,10,2,5,8) @test check_expec_fourbody_2(ComplexF32, 4, 1,2,3,4) @test check_expec_fourbody_2(ComplexF64, 10, 7,10,1,5) @test check_expec_fivebody_2(ComplexF64, 5, 1,2,3,5,4) @test check_expec_fivebody_2(ComplexF32, 10, 7,10,2,5,8) end ","Julia" "Conjugate","guochu/VQC.jl","test/check_state_init.jl",".jl","2164","48"," function check_statevector_init_1() a0 = storage(StateVector(1)) == Gates.ZERO a1 = storage(onehot_encoding([1])) == Gates.ONE a2 = storage(onehot_encoding([0])) == Gates.ZERO a3 = storage(onehot_encoding(2)) == kron(Gates.ZERO, Gates.ZERO) a4 = storage(onehot_encoding([1, 0])) == kron(Gates.ZERO, Gates.ONE) a5 = storage(onehot_encoding([0, 1])) == kron(Gates.ONE, Gates.ZERO) a6 = storage(onehot_encoding([1, 1])) == kron(Gates.ONE, Gates.ONE) a7 = storage(onehot_encoding([1,0,0])) == kron(Gates.ZERO, Gates.ZERO, Gates.ONE) a8 = storage(reset_onehot!(onehot_encoding([1, 1]), [0, 1])) == kron(Gates.ONE, Gates.ZERO) a9 = storage(reset_onehot!(onehot_encoding([1,0,1]), [0,0,1])) == kron(Gates.ONE, Gates.ZERO, Gates.ZERO) return a0 && a1 && a2 && a3 && a4 && a5 && a6 && a7 && a8 && a9 end function check_statevector_init_2() v = [sqrt(2)/2, sqrt(2)/2] a0 = isapprox(onehot_encoding([0]), qubit_encoding([0.]) ) a1 = isapprox(onehot_encoding([1]), qubit_encoding([1.])) a2 = isapprox(onehot_encoding([1,0]), qubit_encoding([1.,0.])) a3 = isapprox(onehot_encoding([1,1]), qubit_encoding([1.,1.])) a4 = isapprox(storage(qubit_encoding([0.5])), v) a5 = isapprox(storage(qubit_encoding([0.5, 1])), kron(Gates.ONE, v)) a6 = isapprox(storage(reset_qubit!(onehot_encoding([0, 1]), [0, 0.5])), kron(v, Gates.ZERO)) a7 = isapprox(storage(reset_qubit!(onehot_encoding([1,1,1]), [0, 0.5, 0.5])), kron(v, v, Gates.ZERO)) a8 = isapprox(storage(reset_qubit!(onehot_encoding([1,1,1,0,1]), [0, 0.5, 0.5, 1, 0])), kron(Gates.ZERO, Gates.ONE, v, v, Gates.ZERO)) return a0 && a1 && a2 && a3 && a4 && a5 && a6 && a7 && a8 end function check_statevector_init_3(L::Int) v = randn(L) a0 = isapprox(StateVector(qubit_encoding(v)), qubit_encoding(v), atol=1.0e-8) v = rand(0:1, L) a2 = isapprox(StateVector(onehot_encoding(v)), onehot_encoding(v), atol=1.0e-8) return a0 && a2 end @testset ""check qubit encoding initialization of quantum state"" begin @test check_statevector_init_1() @test check_statevector_init_2() for L in [3,4] @test check_statevector_init_3(L) end end ","Julia" "Conjugate","guochu/VQC.jl","test/check_measure.jl",".jl","1765","76"," function check_measure_1() state = rand_state(Float64, 3) i, p = measure!(state, 1, auto_reset=true) tmp, i1, p1 = measure(state, 1) return i1 == 0 && isapprox(p1, 1, atol=1.0e-10) end function check_measure_2() state = rand_state(ComplexF64, 3) i, p = measure!(state, 2, auto_reset=false) tmp, i1, p1 = measure(state, 2) return i1 == i && isapprox(p1, 1, atol=1.0e-10) end function check_select_1() state = rand_state(Float64, 3) post_select!(state, 2, 0) tmp, i1, p1 = measure(state, 2) return i1 == 0 && isapprox(p1, 1, atol=1.0e-10) end function check_select_2() state = rand_state(Float64, 3) post_select!(state, 3, 1) tmp, i1, p1 = measure(state, 3) return i1 == 1 && isapprox(p1, 1, atol=1.0e-10) end function check_select_3() state = (sqrt(2)/2) * (qubit_encoding([0, 0]) + qubit_encoding([1, 1])) r, p = post_select(state, 1, 0) return isapprox(storage(r), Gates.ZERO) end function check_select_4() state = (sqrt(2)/2) * (qubit_encoding([0, 0]) + qubit_encoding([1, 1])) r, p = post_select(state, 1, 1) return isapprox(storage(r), Gates.ONE) end function check_select_grad() initial_state = qubit_encoding([0, 1]) function loss(s) r, p = post_select(s, 2, 1) return distance(r, initial_state) + p^2 end loss_fd(θs) = loss(StateVector(θs)) x = rand_state(ComplexF64, 3) grad1 = storage(gradient(loss, x)[1]) grad2 = fdm_gradient(loss_fd, storage(x)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end @testset ""check quantum measure"" begin @test check_measure_1() @test check_measure_2() end @testset ""check quantum select"" begin @test check_select_1() @test check_select_2() @test check_select_3() @test check_select_4() end @testset ""check quantum select grad"" begin @test check_select_grad() end ","Julia" "Conjugate","guochu/VQC.jl","test/parameter.jl",".jl","1332","55"," function test_parameter(L::Int, depth::Int) circuit = QCircuit() counts = 0 vars = [] for i in 1:L push!(circuit, HGate(i)) end for i in 1:L parameter = randn(Float64) # variable indicate a parameter push!(circuit, RxGate(i, parameter, isparas=true)) counts += 1 push!(vars, parameter) # this is not a parameter push!(circuit, RxGate(i, parameter + 1, isparas=false)) end for d in 1:depth for i in 1:(L-1) push!(circuit, CNOTGate(i, i+1)) end for i in 1:L parameter = randn(Float64) # variable indicate a parameter push!(circuit, RxGate(i, parameter, isparas=true)) counts += 1 push!(vars, parameter) # this is not a parameter push!(circuit, RxGate(i, parameter + 1, isparas=false)) end end check1 = (nparameters(circuit) == counts) check2 = (active_parameters(circuit) == vars) new_vars = randn(Float64, size(vars)...) reset_parameters!(circuit, new_vars) check3 = (nparameters(circuit) == counts) check4 = (active_parameters(circuit) == new_vars) # println(""check1 $check1, check2 $check2, check3 $check3, check4 $check4"") return check1 && check2 && check3 && check4 end @testset ""set the parameters of quantum circuit"" begin for L in 2:10 for depth in 0:7 @test test_parameter(L, depth) end end end ","Julia" "Conjugate","guochu/VQC.jl","test/check_utility.jl",".jl","271","15"," function check_ptrace(sites) a = rand_state(6) b = DensityMatrix(a) return partial_tr(a, sites) ≈ partial_tr(b, sites) end @testset ""check partial trace of quantum state"" begin @test check_ptrace([1,2]) @test check_ptrace([2,5]) @test check_ptrace([6,3]) end ","Julia" "Conjugate","guochu/VQC.jl","test/stategrad.jl",".jl","3059","117"," """""" state gradient with distance loss function """""" function state_grad_dot_real(L::Int, depth::Int) target_state = rand_state(ComplexF64, L) initial_state = rand_state(ComplexF64, L) circuit = variational_circuit_1d(L, depth) loss(x) = real(dot(target_state, circuit * x)) loss_fd(θs) = loss(StateVector(θs)) grad1 = storage(gradient(loss, initial_state)[1]) grad2 = fdm_gradient(loss_fd, amplitudes(initial_state)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end """""" state gradient with distance loss function """""" function state_grad_dot_imag(L::Int, depth::Int) target_state = rand_state(ComplexF64, L) initial_state = rand_state(ComplexF64, L) circuit = variational_circuit_1d(L, depth) loss(x) = imag(dot(target_state, circuit * x)) loss_fd(θs) = loss(StateVector(θs)) grad1 = storage(gradient(loss, initial_state)[1]) grad2 = fdm_gradient(loss_fd, amplitudes(initial_state)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end """""" state gradient with distance loss function """""" function state_grad_dot_abs(L::Int, depth::Int) target_state = rand_state(ComplexF64, L) initial_state = rand_state(ComplexF64, L) circuit = variational_circuit_1d(L, depth) loss(x) = abs(dot(target_state, circuit * x)) loss_fd(θs) = loss(StateVector(θs)) grad1 = storage(gradient(loss, initial_state)[1]) grad2 = fdm_gradient(loss_fd, amplitudes(initial_state)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end """""" state gradient with distance loss function """""" function state_grad_distance(L::Int, depth::Int) target_state = rand_state(ComplexF64, L) initial_state = rand_state(ComplexF64, L) circuit = variational_circuit_1d(L, depth) loss(x) = distance(target_state, circuit * x) loss_fd(θs) = loss(StateVector(θs)) grad1 = storage(gradient(loss, initial_state)[1]) grad2 = fdm_gradient(loss_fd, amplitudes(initial_state)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end function qstate_grad(::Type{T}, L::Int) where {T<:Number} target_state = rand_state(T, L) loss(v) = abs(dot(target_state, qubit_encoding(T, v))) x = randn(L) grad1 = gradient(loss, x)[1] grad2 = fdm_gradient(loss, x) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end @testset ""gradient of quantum state with loss function real(dot(a, circuit*x))"" begin for L in 2:5 for depth in 0:5 @test state_grad_dot_real(L, depth) end end end @testset ""gradient of quantum state with loss function imag(dot(a, circuit*x))"" begin for L in 2:5 for depth in 0:5 @test state_grad_dot_imag(L, depth) end end end @testset ""gradient of quantum state with loss function abs(dot(a, circuit*x))"" begin for L in 2:5 for depth in 0:5 @test state_grad_dot_abs(L, depth) end end end @testset ""gradient of quantum state with loss function distance(a, circuit*x)"" begin for L in 2:5 for depth in 0:5 @test state_grad_distance(L, depth) end end end @testset ""gradient of quantum state initializer qstate"" begin for L in 2:5 for T in [Float64, Complex{Float64}] @test qstate_grad(T, L) end end end ","Julia" "Conjugate","guochu/VQC.jl","test/runtests.jl",".jl","1824","85","push!(LOAD_PATH, ""../src"") include(""util.jl"") using Test using Zygote, LinearAlgebra using QuantumCircuits, QuantumCircuits.Gates using QuantumCircuits: n_qubits_mat_from_external using VQC, VQC.Utilities using VQC: apply_serial! _check_unitary(m::AbstractMatrix) = isapprox(m' * m, LinearAlgebra.I) function from_external(key::NTuple{N, Int}, m::AbstractMatrix; check_unitary::Bool=true) where N (size(m, 1) == 2^N) || error(""wrong input matrix size."") if check_unitary _check_unitary(m) || error(""input matrix is not unitary."") end return QuantumGate(key, n_qubits_mat_from_external(m)) end function random_unitary(n::Int) L = 2^n m = randn(ComplexF64, L, L) return exp(im * (m + m')) end @testset ""test quantum gate operations"" begin include(""check_gateop.jl"") include(""check_high_qubit_gate.jl"") end @testset ""test quantum state initialization"" begin include(""check_state_init.jl"") end @testset ""test qubit hamiltonian operations"" begin include(""check_qubits_ham.jl"") end @testset ""test circuit parameters"" begin include(""parameter.jl"") end @testset ""test measure and select"" begin include(""check_measure.jl"") end @testset ""test quantum algorithm"" begin include(""algs.jl"") end @testset ""test utility"" begin include(""check_utility.jl"") end @testset ""test quantum circuit gradient"" begin include(""circuitgrad.jl"") include(""crxgategrad.jl"") end @testset ""test expectation value gradient"" begin include(""check_ham_expec_diff.jl"") end @testset ""test quantum state gradient (may not variable via a quantum computer)"" begin include(""stategrad.jl"") end @testset ""test density matrix operations"" begin include(""stategrad.jl"") end @testset ""test noisy quantum circuit"" begin include(""check_noisy_grad.jl"") end ","Julia" "Conjugate","guochu/VQC.jl","test/algs.jl",".jl","1954","88"," function to_digits(s::Vector{Int}) r = 0. for i = 1:length(s) r = r + s[i]*(2.)^(-i) end return r end function phase_estimate_circuit(j::Vector{Int}) L = length(j) circuit = QCircuit() phi = to_digits(j) U = [exp(2*pi*im*phi) 0; 0. 1.] for i = 1:L push!(circuit, (i, H)) end tmp = U for i = L:-1:1 push!(circuit, ((i, L+1), Gates.CONTROL(tmp))) tmp = tmp * tmp end push!(circuit, QFT(L)') return circuit end function simple_phase_estimation_1(L::Int, auto_reset::Bool=false) j = rand(0:1, L) state = StateVector(L+1) phi = to_digits(j) circuit = phase_estimate_circuit(j) apply!(circuit, state) res = Int[] for i = 1:(L+1) i, p = measure!(state, i, auto_reset=auto_reset) push!(res, i) end phi_out = to_digits(res) return (phi == phi_out) && (j[1:L] == res[1:L]) end function simple_phase_estimation_1_dm(L::Int, auto_reset::Bool=false) j = rand(0:1, L) state = DensityMatrix(L+1) phi = to_digits(j) circuit = phase_estimate_circuit(j) apply!(circuit, state) res = Int[] for i = 1:(L+1) i, p = measure!(state, i, auto_reset=auto_reset) push!(res, i) end phi_out = to_digits(res) return (phi == phi_out) && (j[1:L] == res[1:L]) end function simple_phase_estimation_2(L::Int) j = rand(0:1, L) state = StateVector(L+1) phi = to_digits(j) circuit = phase_estimate_circuit(j) apply!(circuit, state) res = Int[] for i = 1:(L+1) state, i, p = measure(state, 1) push!(res, i) end phi_out = to_digits(res) return length(storage(state))==1 && isapprox(state[1], 1, atol=1.0e-10) && (phi == phi_out) && (j[1:L] == res[1:L]) end @testset ""simple phase estimation"" begin for L in 2:15 @test simple_phase_estimation_1(L, false) @test simple_phase_estimation_1(L, true) end for L in 2:6 @test simple_phase_estimation_1_dm(L, false) @test simple_phase_estimation_1_dm(L, true) end for L in 2:15 @test simple_phase_estimation_2(L) end end ","Julia" "Conjugate","guochu/VQC.jl","test/check_gateop.jl",".jl","6318","186"," function check_onebody_single(::Type{T}, L::Int, c::Int) where {T<:Number} state1 = rand_state(T, L) state2 = copy(state1) gate = QuantumGate(c, random_unitary(1)) apply_serial!(gate, state1) apply!(gate, state2) return maximum(abs.(storage(state1 - state2)) ) end function check_onebody(::Type{T}, L::Int) where {T<:Number} errs = [] for c in 1:L push!(errs, check_onebody_single(T, L, c)) end # println(""total number of tests $(length(errs))."") return all(errs .< 1.0e-6) end function check_twobody_single(::Type{T}, L::Int, c::Int, t::Int) where {T<:Number} state1 = rand_state(T, L) state2 = copy(state1) gate = QuantumGate((c, t), random_unitary(2)) apply_serial!(gate, state1) apply!(gate, state2) return maximum(abs.(storage(state1 - state2)) ) end function check_twobody(::Type{T}, L::Int) where {T<:Number} errs = [] for c in 1:2:L for t in 2:2:L if c != t push!(errs, check_twobody_single(T, L, c, t)) end end end # println(""total number of tests $(length(errs))."") return all(errs .< 1.0e-6) end function check_threebody_single(::Type{T}, L::Int, a::Int, b::Int, c::Int) where {T<:Number} state1 = rand_state(T, L) state2 = copy(state1) gate = QuantumGate((a, b, c), random_unitary(3)) apply_serial!(gate, state1) apply!(gate, state2) return maximum(abs.(storage(state1 - state2)) ) end function check_threebody(::Type{T}, L::Int) where {T<:Number} errs = [] for a in 1:2:L for b in 2:3:L for c in 3:5:L if a != b && a != c && b != c push!(errs, check_threebody_single(T, L, a, b, c)) end end end end # println(""total number of tests $(length(errs))."") return all(errs .< 1.0e-6) end function check_single_gate(::Type{T}, L::Int, gt) where {T<:Number} state1 = rand_state(T, L) state2 = copy(state1) apply!(gt, state1) apply!(gate(ordered_positions(gt), ordered_mat(gt)), state2) return maximum(abs.(storage(state1 - state2)) ) end function check_specialized_onebody_gates(::Type{T}, L::Int) where {T<:Number} errs = [] for c in 1:L gt = XGate(c) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = YGate(c) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = ZGate(c) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = TGate(c) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = PHASEGate(c, randn()) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) end return all(errs .< 1.0e-6) end function check_specialized_twobody_gates(::Type{T}, L::Int) where {T<:Number} errs = [] for c in 1:2:L for t in 2:2:L if c != t gt = CONTROLGate((c, t), random_unitary(1)) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = CRxGate(c, t, randn()) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = CRyGate(c, t, randn()) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = CRzGate(c, t, randn()) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = CZGate(c, t) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = CNOTGate(c, t) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = CPHASEGate(c, t, randn()) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = SWAPGate(c, t) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = iSWAPGate(c, t) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = FSIMGate(c, t, randn(5)) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) end end end return all(errs .< 1.0e-6) end function check_specialized_threebody_gates(::Type{T}, L::Int) where {T<:Number} errs = [] for a in 1:2:L for b in 2:3:L for c in 3:5:L if a != b && a != c && b != c gt = CONTROLCONTROLGate(a, b, c, random_unitary(1)) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = TOFFOLIGate(a, b, c) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = FREDKINGate(a, b, c) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) gt = CCPHASEGate(a, b, c, randn()) push!(errs, check_single_gate(T, L, gt)) push!(errs, check_single_gate(T, L, gt')) end end end end return all(errs .< 1.0e-6) end @testset ""check generic gate operations"" begin @test check_onebody(ComplexF32, 16) @test check_onebody(ComplexF64, 15) for L in 5:10:15 @test check_twobody(ComplexF32, L) @test check_twobody(ComplexF64, L) end @test check_threebody(ComplexF32, 16) @test check_threebody(ComplexF64, 15) end @testset ""check specialized gate operations"" begin @test check_specialized_onebody_gates(ComplexF32, 16) @test check_specialized_twobody_gates(ComplexF32, 16) @test check_specialized_threebody_gates(ComplexF64, 15) end ","Julia" "Conjugate","guochu/VQC.jl","test/check_noisy_grad.jl",".jl","1728","60"," function noisy_circuit(L, depth; kwargs...) circuit = variational_circuit_1d(L, depth; kwargs...) for i in 1:L push!(circuit, Depolarizing(i, p=0.1)) end return circuit end function check_noisy_circuit_grad(L, depth) circuit = noisy_circuit(L, depth) initial_state = DensityMatrix(ComplexF64, L) loss(x) = real( sum(storage(x * initial_state)) ) loss_fd(θs) = loss(noisy_circuit(L, depth, θs=θs)) grad1 = gradient(loss, circuit)[1] grad2 = fdm_gradient(loss_fd, active_parameters(circuit)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end function check_noisy_circuit_expec_grad(L, depth) circuit = noisy_circuit(L, depth) m = QubitsTerm(1=>""+"", L-1=>""-"", coeff=0.7) + QubitsTerm(1=>""-"", L-1=>""+"", coeff=0.77) + QubitsTerm(1=>""X"", L=>""Y"", coeff=0.36) initial_state = DensityMatrix(ComplexF64, L) loss(x) = real(expectation(m, x * initial_state)) loss_fd(θs) = loss(noisy_circuit(L, depth, θs=θs)) grad1 = gradient(loss, circuit)[1] grad2 = fdm_gradient(loss_fd, active_parameters(circuit)) # println(""error is $(maximum(abs.(grad1 - grad2)))"") return maximum(abs.(grad1 - grad2)) < 1.0e-6 end function check_ham_term_grad(::Type{T}, L) where T state = rand_densitymatrix(T, L) m = QubitsTerm(1=>""+"", L-1=>""Y"", coeff=0.36) loss(x) = abs(expectation(m, x)) loss_fd(θs) = loss(DensityMatrix(θs)) grad1 = storage(gradient(loss, state)[1]) grad2 = fdm_gradient(loss_fd, storage(state)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end @testset ""gradient of noisy quantum circuit"" begin for L in 2:5 @test check_ham_term_grad(ComplexF64, L) for depth in 0:5 @test check_noisy_circuit_grad(L, depth) @test check_noisy_circuit_expec_grad(L, depth) end end end","Julia" "Conjugate","guochu/VQC.jl","test/check_ham_expec_diff.jl",".jl","2292","78"," function check_ham_term_grad(::Type{T}, L) where T state = rand_state(T, L) m = QubitsTerm(1=>""+"", L-1=>""Y"", coeff=0.36) loss(x) = abs(expectation(m, x)) loss_fd(θs) = loss(StateVector(θs)) grad1 = storage(gradient(loss, state)[1]) grad2 = fdm_gradient(loss_fd, amplitudes(state)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end function check_ham_expec_grad(::Type{T}, L) where T state = rand_state(T, L) m = QubitsTerm(1=>""+"", L-1=>""-"", coeff=0.77) + QubitsTerm(1=>""-"", L-1=>""+"", coeff=0.77) + QubitsTerm(1=>""X"", L=>""Y"", coeff=0.36) loss(x) = abs(expectation(m, x)) loss_fd(θs) = loss(StateVector(θs)) grad1 = storage(gradient(loss, state)[1]) grad2 = fdm_gradient(loss_fd, amplitudes(state)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end function check_qterm_expec_grad_long(::Type{T}, L, n) where T state = rand_state(T, L) m = QubitsTerm(Dict(i=>""X"" for i in 1:n), coeff=0.77) loss(x) = abs(expectation(m, x)) loss_fd(θs) = loss(StateVector(θs)) grad1 = storage(gradient(loss, state)[1]) grad2 = fdm_gradient(loss_fd, amplitudes(state)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end function check_ham_expec_grad_long(::Type{T}, L, n) where T state = rand_state(T, L) m = QubitsTerm(Dict(i=>""X"" for i in 1:n), coeff=0.77) + QubitsTerm(1=>""X"", coeff=1.2) + QubitsTerm(1=>""X"", 2=>""Z"", coeff=0.3) loss(x) = abs(expectation(m, x)) loss_fd(θs) = loss(StateVector(θs)) grad1 = storage(gradient(loss, state)[1]) grad2 = fdm_gradient(loss_fd, amplitudes(state)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end function check_mps_ham_expec_grad(::Type{T}, L::Int) where {T<:Number} observer = QubitsTerm(1=>""Z"", 3=>""Z"") loss(v) = real(expectation(observer, qubit_encoding(T, v))) v = randn(L) grad1 = gradient(loss, v)[1] grad2 = fdm_gradient(loss, v) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end @testset ""gradient of quantum operator expectation value"" begin for L in 3:6 @test check_ham_term_grad(ComplexF64, L) @test check_ham_expec_grad(ComplexF64, L) for n in 1:L @test check_qterm_expec_grad_long(ComplexF64, L, n) @test check_ham_expec_grad_long(ComplexF64, L, n) end end for T in [Float64, ComplexF64] for L in 3:6 @test check_mps_ham_expec_grad(ComplexF64, L) end end end ","Julia" "Conjugate","guochu/VQC.jl","test/util.jl",".jl","2855","110"," using FiniteDifferences fdm_gradient(f, v; kwargs...) = error(""fdm_gradient not implemented for type $(typeof(v))"") fdm_gradient(f, v::Real; order::Int=5, kwargs...) = central_fdm(order, 1; kwargs...)(f, v) fdm_gradient(f, v::Complex; order::Int=5, kwargs...) = begin f_real(vr::Real) = f(complex(vr, imag(v))) f_imag(vi::Real) = f(complex(real(v), vi)) m = central_fdm(order, 1; kwargs...) da = m(f_real, real(v)) db = m(f_imag, imag(v)) return complex(da, db) end fdm_gradient(f, v::AbstractArray; kwargs...) = begin # x = copy(v) tmp = copy(v) r = similar(v) for l in 1:length(v) g(s) = begin tmp[l] = s d = f(tmp) tmp[l] = v[l] return d end r[l] = fdm_gradient(g, v[l]; kwargs...) # tmp[l] = v[l] end return r end function fdm_gradient(f, args...; kwargs...) r = [] v0 = f(args...) # args = [args...] L = length(args) for l in 1:L g(x) = f(args[1:(l-1)]..., x, args[(l+1):L]...) push!(r, fdm_gradient(g, args[l]; kwargs...)) end return (r...,) end # collect_variables_impl!(a::Vector, b::Nothing) = nothing # collect_variables_impl!(a::Vector, b::Number) = push!(a, b) # function collect_variables_impl!(a::Vector, b::AbstractArray) # for item in b # collect_variables_impl!(a, item) # end # end # function collect_variables_impl!(a::Vector, b::AbstractDict) # for (k, v) in b # collect_variables_impl!(a, v) # end # end # function collect_variables_impl!(a::Vector, b::NamedTuple) # for v in b # collect_variables_impl!(a, v) # end # end # function collect_variables_impl!(a::Vector, b::Tuple) # for v in b # collect_variables_impl!(a, v) # end # end # """""" # collect_variables(args...) # Collect variables from args... # """""" # function collect_variables(args...) # a = Number[] # for item in args # collect_variables_impl!(a, item) # end # return a # end # """""" # check_gradient(f, args...; verbosity::Int=0) # Check the gradient of a function f with arguments args... # """""" # function check_gradient(f, args...; verbosity::Int=0) # grad = collect_variables(gradient(f, args...)) # tmpargs = collect(args) # f2(x) = begin # set_parameters!(x, tmpargs) # return f(tmpargs...) # end # grad1 = simple_gradient(f2, collect_variables(tmpargs), dt=dt)[1] # diffmax = maximum(abs.(grad - grad1)) # v = diffmax <= atol # if (!v) && (verbosity > 0) # println(""largest difference is $diffmax."") # println(""auto gradient is $grad."") # println(""---------------------------------------------------------------------"") # println(""finite difference gradient is $grad1"") # end # return v # end","Julia" "Conjugate","guochu/VQC.jl","test/crxgategrad.jl",".jl","3816","150"," function crx_circuit(L::Int, depth::Int) n = 0 circuit = QCircuit() for d in 1:depth for i in 1:L-1 push!(circuit, CNOTGate((i, i+1))) push!(circuit, CRxGate((i, i+1), randn(), isparas=true)) push!(circuit, CNOTGate((i, i+1))) n += 1 end end return circuit, n end """""" circuit gradient with dot loss function """""" function crx_circuit_grad_dot_real(L::Int, depth::Int) target_state = rand_state(ComplexF64, L) initial_state = StateVector(ComplexF64, L) circuit, n = crx_circuit(L, depth) loss(x) = real(dot(target_state, x * initial_state)) loss_fd(θs) = begin reset_parameters!(circuit, θs) return loss(circuit) end grad1 = gradient(loss, circuit)[1] grad2 = fdm_gradient(loss_fd, active_parameters(circuit)) return nparameters(circuit)==n && maximum(abs.(grad1 - grad2)) < 1.0e-6 end function gfsim1_circuit(L::Int, depth::Int) circuit = QCircuit() for i in 1:L push!(circuit, HGate(i)) end for d in 1:depth for i in 1:L-1 push!(circuit, CNOTGate((i, i+1))) push!(circuit, FSIMGate((i, i+1), randn(5), isparas=[true, false, false, false, false])) push!(circuit, CNOTGate((i, i+1))) end end return circuit end function gfsim2_circuit(L::Int, depth::Int) circuit = QCircuit() for i in 1:L push!(circuit, HGate(i)) end for d in 1:depth for i in 1:L-1 push!(circuit, CNOTGate((i, i+1))) push!(circuit, FSIMGate((i, i+1), randn(5), isparas=[true, true, false, false, false])) push!(circuit, CNOTGate((i, i+1))) end end return circuit end function gfsim5_circuit(L::Int, depth::Int) circuit = QCircuit() for i in 1:L push!(circuit, HGate(i)) end for d in 1:depth for i in 1:L-1 push!(circuit, CNOTGate((i, i+1))) push!(circuit, FSIMGate((i, i+1), randn(5), isparas=[true, true, true, true, true])) push!(circuit, CNOTGate((i, i+1))) end end return circuit end function bf_circuit_gfims1_grad_dot_abs(L::Int, depth::Int) target_state = rand_state(ComplexF64, L) initial_state = StateVector(ComplexF64, L) circuit = gfsim1_circuit(L, depth) loss(x) = abs(dot(target_state, x * initial_state)) loss_fd(θs) = begin reset_parameters!(circuit, θs) return loss(circuit) end grad1 = gradient(loss, circuit)[1] grad2 = fdm_gradient(loss_fd, active_parameters(circuit)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end function bf_circuit_gfims2_grad_dot_abs(L::Int, depth::Int) target_state = rand_state(ComplexF64, L) initial_state = StateVector(ComplexF64, L) circuit = gfsim2_circuit(L, depth) loss(x) = abs(dot(target_state, x * initial_state)) loss_fd(θs) = begin reset_parameters!(circuit, θs) return loss(circuit) end grad1 = gradient(loss, circuit)[1] grad2 = fdm_gradient(loss_fd, active_parameters(circuit)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end function bf_circuit_gfims5_grad_dot_abs(L::Int, depth::Int) target_state = rand_state(ComplexF64, L) initial_state = StateVector(ComplexF64, L) circuit = gfsim5_circuit(L, depth) loss(x) = abs(dot(target_state, x * initial_state)) loss_fd(θs) = begin reset_parameters!(circuit, θs) return loss(circuit) end grad1 = gradient(loss, circuit)[1] grad2 = fdm_gradient(loss_fd, active_parameters(circuit)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end @testset ""gradient of variable quantum circuit with parameterized controled rotational gate"" begin for L in 2:5 for depth in 1:5 @test crx_circuit_grad_dot_real(L, depth) end end end @testset ""gradient of brute force quantum circuit with FSIM gate"" begin for L in 2:5 for depth in 1:3 @test bf_circuit_gfims1_grad_dot_abs(L, depth) @test bf_circuit_gfims2_grad_dot_abs(L, depth) @test bf_circuit_gfims5_grad_dot_abs(L, depth) end end end ","Julia" "Conjugate","guochu/VQC.jl","test/check_dm.jl",".jl","1038","61"," function check_dm_expec_1() psi = rand_state(ComplexF64, 7) rho = DensityMatrix(psi) h = QubitsTerm(1=>""X"") a1 = expectation(h, psi) a2 = expectation(h, rho) return abs(a1 - a2) < 1.0e-6 end function check_dm_expec_2() psi = rand_state(ComplexF64, 7) rho = DensityMatrix(psi) h = QubitsTerm(1=>""X"", 2=>""+"") a1 = expectation(h, psi) a2 = expectation(h, rho) return abs(a1 - a2) < 1.0e-6 end function check_dm_expec_3() psi = rand_state(ComplexF64, 7) rho = DensityMatrix(psi) h = QubitsTerm(1=>""X"", 2=>""+"", 4=>""-"") a1 = expectation(h, psi) a2 = expectation(h, rho) return abs(a1 - a2) < 1.0e-6 end function check_dm_expec_4() psi = rand_state(ComplexF64, 8) rho = DensityMatrix(psi) h = QubitsTerm(1=>""X"", 2=>""+"", 4=>""-"", 8=>""Z"") a1 = expectation(h, psi) a2 = expectation(h, rho) return abs(a1 - a2) < 1.0e-6 end @testset ""check density matrix expectation value"" begin @test check_dm_expec_1() @test check_dm_expec_2() @test check_dm_expec_3() @test check_dm_expec_4() end ","Julia" "Conjugate","guochu/VQC.jl","test/check_qubits_ham.jl",".jl","8612","265"," function check_qham_onebody_single(::Type{T}, L::Int, j::Int) where T state1 = rand_state(T, L) m = random_unitary(1) gate1 = QuantumGate(j, m) h = QubitsOperator(QubitsTerm(j=>m)) state2 = h * state1 apply!(gate1, state1) return maximum(abs.(storage(state1 - state2)) ) end function check_qham_onebody(::Type{T}, L::Int) where {T<:Number} errs = [] for c in 1:L push!(errs, check_qham_onebody_single(T, L, c)) end # println(""total number of tests $(length(errs))."") return all(errs .< 1.0e-6) end function check_qham_twobody_single(::Type{T}, L::Int, j::Int, k::Int) where T state1 = rand_state(T, L) m1 = random_unitary(1) m2 = random_unitary(1) gate1 = QuantumGate((j, k), kron(m1, m2)) h = QubitsOperator(QubitsTerm(j=>m2, k=>m1)) state2 = h * state1 apply!(gate1, state1) return maximum(abs.(storage(state1 - state2)) ) end function check_qham_twobody(::Type{T}, L::Int) where {T<:Number} errs = [] for c in 1:2:L for t in 2:2:L if c != t push!(errs, check_qham_twobody_single(T, L, c, t)) end end end # println(""total number of tests $(length(errs))."") return all(errs .< 1.0e-6) end function check_qham_threebody_single(::Type{T}, L::Int, a::Int, b::Int, c::Int) where {T<:Number} state1 = rand_state(T, L) m1 = random_unitary(1) m2 = random_unitary(1) m3 = random_unitary(1) gate1 = QuantumGate((a, b, c), kron(m1, m2, m3)) h = QubitsOperator(QubitsTerm(a=>m3, b=>m2, c=>m1)) state2 = h * state1 apply!(gate1, state1) return maximum(abs.(storage(state1 - state2)) ) end function check_qham_threebody(::Type{T}, L::Int) where {T<:Number} errs = [] for a in 1:2:L for b in 2:3:L for c in 3:5:L if a != b && a != c && b != c push!(errs, check_qham_threebody_single(T, L, a, b, c)) end end end end # println(""total number of tests $(length(errs))."") return all(errs .< 1.0e-6) end function check_term_matrix(L::Int) state = rand_state(ComplexF64, L) m = QubitsTerm(1=>""+"", L-1=>""-"", coeff=0.77) return maximum(abs.(storage(m * state - matrix(L, m) * state))) < 1.0e-6 end function check_ham_matrix(L::Int) state = rand_state(ComplexF64, L) m = QubitsTerm(1=>""+"", L-1=>""-"", coeff=0.77) + QubitsTerm(1=>""-"", L-1=>""+"", coeff=0.77) + QubitsTerm(1=>""X"", L=>""Y"", coeff=0.36) return maximum(abs.(storage(m * state - matrix(L, m) * state))) < 1.0e-6 end function check_term_expec(L::Int) state = rand_state(ComplexF64, L) m = QubitsTerm(1=>""+"", L-1=>""-"", coeff=0.77) return abs(expectation(m, state) - expectation(matrix(L, m), state)) < 1.0e-6 end function check_ham_expec(L::Int) state = rand_state(ComplexF64, L) m = QubitsTerm(1=>""+"", 2=>""-"", coeff=0.77) + QubitsTerm(1=>""-"", 2=>""+"", coeff=0.77) + QubitsTerm(1=>""X"", L-1=>""Y"", coeff=0.36) return abs(expectation(m, state) - expectation(matrix(L, m), state)) < 1.0e-6 end function check_ham_expec_long(L::Int, n::Int) state = rand_state(ComplexF64, L) m = QubitsTerm(Dict(i=>""X"" for i in 1:n), coeff=0.77) + QubitsTerm(1=>""X"", coeff=1.2) + QubitsTerm(1=>""X"", 2=>""Z"", coeff=0.3) return abs(expectation(m, state) - expectation(matrix(L, m), state)) < 1.0e-6 end function check_expec_onebody_single(::Type{T}, L::Int, j::Int) where T state = rand_state(T, L) m = QubitsTerm(j=>random_unitary(1)) return abs(expectation(m, state) - expectation(matrix(L, m), state)) end function check_expec_onebody(::Type{T}, L::Int) where {T<:Number} errs = [] for c in 1:L push!(errs, check_expec_onebody_single(T, L, c)) end return all(errs .< 1.0e-6) end function check_expec_twobody_single(::Type{T}, L::Int, j::Int, k::Int) where T state = rand_state(T, L) m = QubitsTerm(j=>random_unitary(1), k=>random_unitary(1), coeff=0.73) return abs(expectation(m, state) - expectation(matrix(L, m), state)) end function check_expec_twobody(::Type{T}, L::Int) where {T<:Number} errs = [] for c in 1:2:L for t in 2:2:L if c != t push!(errs, check_expec_twobody_single(T, L, c, t)) end end end # println(""total number of tests $(length(errs))."") return all(errs .< 1.0e-6) end function check_expec_threebody_single(::Type{T}, L::Int, j::Int, k::Int, l::Int) where T state = rand_state(T, L) m = QubitsTerm(j=>random_unitary(1), k=>random_unitary(1), l=>random_unitary(1), coeff=0.9) return abs(expectation(m, state) - expectation(matrix(L, m), state)) end function check_expec_threebody(::Type{T}, L::Int) where {T<:Number} errs = [] for a in 1:L for b in 1:L for c in 1:L if a != b && a != c && b != c push!(errs, check_expec_threebody_single(T, L, a, b, c)) end end end end # println(""total number of tests $(length(errs))."") return all(errs .< 1.0e-6) end function check_expec_onebody_single_2(::Type{T}, L::Int, j::Int) where T state1 = rand_state(T, L) state2 = rand_state(T, L) m = QubitsTerm(j=>random_unitary(1)) return abs(expectation(state2, m, state1) - expectation(state2, matrix(L, m), state1)) end function check_expec_onebody_2(::Type{T}, L::Int) where {T<:Number} errs = [] for c in 1:L push!(errs, check_expec_onebody_single_2(T, L, c)) end return all(errs .< 1.0e-6) end function check_expec_twobody_single_2(::Type{T}, L::Int, j::Int, k::Int) where T state1 = rand_state(T, L) state2 = rand_state(T, L) m = QubitsTerm(j=>random_unitary(1), k=>random_unitary(1), coeff=0.73) return abs(expectation(state2, m, state1) - expectation(state2, matrix(L, m), state1)) end function check_expec_twobody_2(::Type{T}, L::Int) where {T<:Number} errs = [] for c in 1:2:L for t in 2:2:L if c != t push!(errs, check_expec_twobody_single_2(T, L, c, t)) end end end # println(""total number of tests $(length(errs))."") return all(errs .< 1.0e-6) end function check_expec_threebody_single_2(::Type{T}, L::Int, j::Int, k::Int, l::Int) where T state1 = rand_state(T, L) state2 = rand_state(T, L) m = QubitsTerm(j=>random_unitary(1), k=>random_unitary(1), l=>random_unitary(1), coeff=0.9) return abs(expectation(state2, m, state1) - expectation(state2, matrix(L, m), state1)) end function check_expec_threebody_2(::Type{T}, L::Int) where {T<:Number} errs = [] for a in 1:L for b in 1:L for c in 1:L if a != b && a != c && b != c push!(errs, check_expec_threebody_single_2(T, L, a, b, c)) end end end end # println(""total number of tests $(length(errs))."") return all(errs .< 1.0e-6) end @testset ""check hamiltonion term expectation value"" begin @test check_term_matrix(16) @test check_term_matrix(15) @test check_ham_matrix(6) @test check_ham_matrix(3) @test check_term_expec(16) @test check_term_expec(15) @test check_ham_expec(6) @test check_ham_expec(3) @test check_ham_expec_long(6, 5) @test check_ham_expec_long(6, 6) @test check_ham_expec_long(8, 8) end @testset ""check generic hamiltonion term operations"" begin @test check_qham_onebody(ComplexF32, 16) @test check_qham_onebody(ComplexF64, 15) for L in 5:10:15 @test check_qham_twobody(ComplexF32, L) @test check_qham_twobody(ComplexF64, L) end @test check_qham_threebody(ComplexF32, 16) @test check_qham_threebody(ComplexF64, 15) @test (check_qham_onebody_single(ComplexF64, 2,2) < 1.0e-6) @test (check_qham_onebody_single(ComplexF64, 4,2) < 1.0e-6) @test (check_qham_twobody_single(ComplexF64, 2,2,1) < 1.0e-6) @test (check_qham_twobody_single(ComplexF64, 3,1,3) < 1.0e-6) @test (check_qham_threebody_single(ComplexF64, 3, 3,1,2) < 1.0e-6) @test (check_qham_threebody_single(ComplexF64, 4, 3,4,1) < 1.0e-6) end @testset ""check generic hamiltonion expectation value"" begin for L in 5:10:15 @test check_expec_onebody(ComplexF64, L) @test check_expec_twobody(ComplexF64, L) @test check_expec_threebody(ComplexF64, L) @test check_expec_onebody_2(ComplexF64, L) @test check_expec_twobody_2(ComplexF64, L) @test check_expec_threebody_2(ComplexF64, L) end end ","Julia" "Conjugate","guochu/VQC.jl","test/circuitgrad.jl",".jl","3423","130"," """""" circuit gradient with dot loss function """""" function circuit_grad_dot_real(L::Int, depth::Int) target_state = rand_state(ComplexF64, L) initial_state = StateVector(ComplexF64, L) circuit = variational_circuit_1d(L, depth) loss(x) = real(dot(target_state, x * initial_state)) loss_fd(θs) = loss(variational_circuit_1d(L, depth, θs=θs)) grad1 = gradient(loss, circuit)[1] grad2 = fdm_gradient(loss_fd, active_parameters(circuit)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end """""" circuit gradient with dot loss function """""" function circuit_grad_dot_imag(L::Int, depth::Int) target_state = rand_state(ComplexF64, L) initial_state = StateVector(ComplexF64, L) circuit = variational_circuit_1d(L, depth) loss(x) = imag(dot(target_state, x * initial_state)) loss_fd(θs) = loss(variational_circuit_1d(L, depth, θs=θs)) grad1 = gradient(loss, circuit)[1] grad2 = fdm_gradient(loss_fd, active_parameters(circuit)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end """""" circuit gradient with dot loss function """""" function circuit_grad_dot_abs(L::Int, depth::Int) target_state = rand_state(ComplexF64, L) initial_state = StateVector(ComplexF64, L) circuit = variational_circuit_1d(L, depth) loss(x) = abs(dot(target_state, x * initial_state)) loss_fd(θs) = loss(variational_circuit_1d(L, depth, θs=θs)) grad1 = gradient(loss, circuit)[1] grad2 = fdm_gradient(loss_fd, active_parameters(circuit)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end """""" circuit gradient with dot loss function """""" function circuit_grad_dot_abs2(L::Int, depth::Int) target_state = rand_state(ComplexF64, L) initial_state = StateVector(ComplexF64, L) circuit = variational_circuit_1d(L, depth) loss(x) = abs2(dot(target_state, x * initial_state)) loss_fd(θs) = loss(variational_circuit_1d(L, depth, θs=θs)) grad1 = gradient(loss, circuit)[1] grad2 = fdm_gradient(loss_fd, active_parameters(circuit)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end """""" circuit gradient with distance loss function """""" function circuit_grad_distance(L::Int, depth::Int) target_state = rand_state(ComplexF64, L) initial_state = StateVector(ComplexF64, L) circuit = variational_circuit_1d(L, depth) loss(x) = distance(target_state, x * initial_state) loss_fd(θs) = loss(variational_circuit_1d(L, depth, θs=θs)) grad1 = gradient(loss, circuit)[1] grad2 = fdm_gradient(loss_fd, active_parameters(circuit)) return maximum(abs.(grad1 - grad2)) < 1.0e-6 end @testset ""gradient of quantum circuit with loss function real(dot(x, circuit*y))"" begin for L in 2:5 for depth in 0:5 @test circuit_grad_dot_real(L, depth) end end end @testset ""gradient of quantum circuit with loss function imag(dot(x, circuit*y))"" begin for L in 2:5 for depth in 0:5 @test circuit_grad_dot_imag(L, depth) end end end @testset ""gradient of quantum circuit with loss function abs(dot(x, circuit*y))"" begin for L in 2:5 for depth in 0:5 @test circuit_grad_dot_abs(L, depth) end end end @testset ""gradient of quantum circuit with loss function abs2(dot(x, circuit*y))"" begin for L in 2:5 for depth in 0:5 @test circuit_grad_dot_abs2(L, depth) end end end @testset ""gradient of quantum circuit with loss function distance(x, circuit*y)"" begin for L in 2:5 for depth in 0:5 @test circuit_grad_distance(L, depth) end end end ","Julia" "Conjugate","guochu/VQC.jl","docs/make.jl",".jl","294","17","push!(LOAD_PATH, ""../src"") using Documenter using VQC makedocs( sitename=""VQC.jl"", authors = ""Guo Chu"", pages=[""Home"" => ""index.md"", ""gettingstarted.md"", ""variational.md"", ""ham.md"", ""qctrl.md""], format = Documenter.HTML( prettyurls = get(ENV, ""CI"", nothing) == ""true"" ) )","Julia" "Conjugate","guochu/VQC.jl","docs/src/variational.md",".md","2007","80","# Variational Quantum Circuit In this section we will provide a simple pipeline to demonstrate how to use VQC to build variational quantum circuits ## Creating a variational quantum circuit ```@example push!(LOAD_PATH, ""../../src"") using VQC L = 3 depth = 2 circuit = QCircuit() for i in 1:L push!(circuit, RzGate(i, Variable(rand()))) push!(circuit, RyGate(i, Variable(rand()))) push!(circuit, RzGate(i, Variable(rand()))) end for l in 1:depth for i in 1:L-1 push!(circuit, CNOTGate((i, i+1))) end for i in 1:L push!(circuit, RzGate(i, Variable(rand()))) push!(circuit, RyGate(i, Variable(rand()))) push!(circuit, RzGate(i, Variable(rand()))) end end # all the parameters of the circuit paras = parameters(circuit) # reset all the parameters of the circuit new_paras = zeros(length(paras)) set_parameters!(new_paras, circuit) paras = parameters(circuit) # compute the gradient using Zygote target_state = qrandn(L) initial_state = qstate(L) loss(c) = distance(target_state, c * initial_state) grad = gradient(loss, circuit) ``` The above definition has been predefined by the function variational_circuit ```@docs variational_circuit(L::Int, depth::Int, g::Function=rand) ``` ## A simple application of VQC and Flux ```@example using VQC using Zygote using Flux.Optimise circuit = variational_circuit(3, 2) target_state = (sqrt(2)/2) * (qstate([1,1,1]) + qstate([0,0,0])) initial_state = qstate([0,0,0]) loss(c) = distance(target_state, c * initial_state) opt = ADAM() epoches = 10 x0 = parameters(circuit) for i in 1:epoches grad = collect_variables(gradient(loss, circuit)) Optimise.update!(opt, x0, grad) set_parameters!(x0, circuit) println(""loss value at $i-th iteration is $(loss(circuit))."") end ``` ## Some utility functions ```@docs collect_variables(args...) parameters(args...) set_parameters!(coeff::AbstractVector{<:Number}, args...) simple_gradient(f, args...; dt::Real=1.0e-6) check_gradient(f, args...; dt::Real=1.0e-6, atol::Real=1.0e-4, verbose::Int=0) ``` ","Markdown" "Conjugate","guochu/VQC.jl","docs/src/qctrl.md",".md","645","35","# Quantum Control VQC support variational hamiltonian evolutions. ```@docs ctrlham(a::AbstractMatrix, b::Vector{<:AbstractMatrix}, nparas::Int) ``` The variational hamiltonian object can be used in the same way as a variational quantum circuit ```@example push!(LOAD_PATH, ""../../src"") using VQC using Zygote random_hermitian(n) = begin a = randn(n, n) return a + a' end H0 = random_hermitian(2) H1 = [random_hermitian(2) for i in 1:2] h = ctrlham(H0, H1, 5) initial_state = [1, 0] target_state = randn(2) loss(c) = distance(target_state, c * initial_state) grad = gradient(loss, h) # Check the gradient check_gradient(loss, h) ```","Markdown" "Conjugate","guochu/VQC.jl","docs/src/index.md",".md","1780","87"," Variational quantum circuit simulator in julia # VQC.jl's documentation VQC is a julia library for variational quantum circuit simulations. VQC aims to supprot automatic differentiation and allow users to easily build hybrid quantum-classical algorithms. Current VQC also has a basic support for variational Hamiltonian simulation. A simple code snippet to create a two-qubit bell state ```@example push!(LOAD_PATH, ""../../src"") using VQC state = qstate(2) circuit = QCircuit() push!(circuit, (1, H)) push!(circuit, ((1, 2), CNOT)) apply!(circuit, state) amplitudes(state) # Perform quantum measurement i, prob = measure!(state, 1) println(""probability of the 1-th qubit in state $i is $prob."") # Obtain a particular amplitude p = amplitude(state, [0, 1]) ``` Build a variational quantum circuit is as simple as a normal quantum state ```@example using VQC using Zygote L = 3 state = qstate(L) circuit = QCircuit() for i in 1:L push!(circuit, RzGate(i, Variable(rand()))) push!(circuit, RyGate(i, Variable(rand()))) push!(circuit, RzGate(i, Variable(rand()))) end for depth in 1:2 for i in 1:L-1 push!(circuit, CNOTGate((i, i+1))) end for i in 1:L push!(circuit, RzGate(i, Variable(rand()))) push!(circuit, RxGate(i, Variable(rand()))) push!(circuit, RzGate(i, Variable(rand()))) end end # Create a random quantum state of 3 qubits target_state = qrandn(L) loss(c) = distance(target_state, c * state) v = loss(circuit) grad = gradient(loss, circuit) check_gradient(loss, circuit) ``` Start to use Meteor.jl from ""Getting Started"" section. ```@contents Pages = [""gettingstarted.md""] Depth = 2 ``` ```@contents Pages = [""variational.md""] Depth = 2 ``` ```@contents Pages = [""ham.md""] Depth = 2 ``` ```@contents Pages = [""qctrl.md""] Depth = 2 ``` ","Markdown" "Conjugate","guochu/VQC.jl","docs/src/ham.md",".md","683","30","# Hamiltonian VQC also has preliminary suport for hamiltonian evolution. ## A simple hamiltonian simulation ```@example push!(LOAD_PATH, ""../../src"") using VQC ps = spin_half() pb = boson(d=4) ham = Hamiltonian([ps, pb]) add!(ham, (1,2), (""sp"", ""a""), coeff=1) add!(ham, (1,2), (""sm"", ""adag""), coeff=1) add!(ham, (1,), (""sz"",), coeff=0.5) add!(ham, (2,), (""n"",), coeff=2) state = kron(spin_half_state(0), fock_state(4, 2)) # unitary evolution state = apply(ham, 0.5, state) # Create an observer observer = Observers(ham) add!(observer, (1,), (""sz"",), name=""z"") add!(observer, (2,), (""n"",), name=""n"") add!(observer, (1,2), (""sp"", ""a""), name=""j"") obs = apply(observer, state) ```","Markdown" "Conjugate","guochu/VQC.jl","docs/src/gettingstarted.md",".md","2585","109","# Getting Started In this section we will provide a simple pipeline to demonstrate how to use VQC to build quantum computing applications Pipeline for quantum circuit simulation ## Initialize a quantum state Definition of function qstate ```@docs qstate(::Type{T}, thetas::AbstractVector{<:Real}) where {T <: Number} qstate(thetas::AbstractVector{<:Real}) qstate(::Type{T}, n::Int) where {T <: Number} qstate(n::Int) ``` Extract amplitudes from quantum state ```@docs amplitude(s::AbstractVector, i::AbstractVector{Int}) amplitudes(s::AbstractVector) ``` Examples ```@example push!(LOAD_PATH, ""../../src"") using VQC state = qstate(2) state = qstate([1, 0]) state = qstate([0.5, 0.7]) ``` ## Quantum gate Predefined elementary gates ""X, Y, Z, S, H, sqrtX, sqrtY, T, Rx, Ry, Rz, CONTROL, CZ, CNOT, CX, SWAP, iSWAP, XGate, YGate, ZGate, HGate, SGate, TGate, SqrtXGate, SqrtYGate, RxGate, RyGate, RzGate, CZGate, CNOTGate, SWAPGate, iSWAPGate, CRxGate, CRyGate, CRzGate, TOFFOLIGate"" ```@example using VQC circuit = QCircuit() # standard one-qubit gate push!(circuit, (1, H)) empty!(circuit) push!(circuit, HGate(1)) empty!(circuit) push!(circuit, gate(1, H)) empty!(circuit) # standard two-qubit gate push!(circuit, ((1, 2), CZ)) empty!(circuit) push!(circuit, CZGate((1, 2))) empty!(circuit) push!(circuit, gate((1,2), CZ)) empty!(circuit) # a parameteric one-qubit gate push!(circuit, RxGate(1, Variable(0.5))) empty!(circuit) # a parameteric two-qubit gate push!(circuit, CRxGate((1,2), Variable(0.5))) empty!(circuit) # This will create a non-parameteric gate instead push!(circuit, RxGate(1, 0.5)) ``` ## Quantum circuit Adding new gates ```@docs add!(x::AbstractCircuit, s) Base.push!(x::AbstractCircuit, s::AbstractGate) Base.append!(x::AbstractCircuit, y::AbstractCircuit) Base.append!(x::AbstractCircuit, y::Vector{T}) where {T<:AbstractGate} ``` Circuit manipulations ```@example using VQC circuit = QCircuit() push!(circuit, (1, H)) push!(circuit, ((1, 2), CZ)) c1 = transpose(circuit) c2 = conj(circuit) c3 = circuit' ``` ## Apply quantum circuit to state ```@docs apply!(circuit::AbstractCircuit, v::Vector) *(circuit::AbstractCircuit, v::AbstractVector) *(v::AbstractVector, circuit::AbstractCircuit) ``` ## Quantum measurement Measure and collapse a quantum state ```@docs measure(qstate::AbstractVector, pos::Int) measure!(qstate::AbstractVector, pos::Int; auto_reset::Bool=true) ``` Postselection ```@docs post_select!(qstate::AbstractVector, key::Int, state::Int=0) post_select(qstate::AbstractVector, key::Int, state::Int=0; keep::Bool=false) ``` ","Markdown"