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gate ch a b { h b ; sdg b ; cx a b ; h b ; t b ; cx a b ; t b ; h b ; s b ; x b ; s a ; }
def _define(self): """ gate ch a,b { h b; sdg b; cx a,b; h b; t b; cx a,b; t b; h b; s b; x b; s a;} """ definition = [] q = QuantumRegister(2, "q") rule = [ (HGate(), [q[1]], []), (SdgGate(), [q[1]], []), (CnotGate(), [q[0], q[1]], []), (HGate(), [q[1]], []), (TGate(), [q[1]], []), (CnotGate(), [q[0], q[1]], []), (TGate(), [q[1]], []), (HGate(), [q[1]], []), (SGate(), [q[1]], []), (XGate(), [q[1]], []), (SGate(), [q[0]], []) ] for inst in rule: definition.append(inst) self.definition = definition
The backend configuration widget.
def config_tab(backend): """The backend configuration widget. Args: backend (IBMQbackend): The backend. Returns: grid: A GridBox widget. """ status = backend.status().to_dict() config = backend.configuration().to_dict() config_dict = {**status, **config} upper_list = ['n_qubits', 'operational', 'status_msg', 'pending_jobs', 'basis_gates', 'local', 'simulator'] lower_list = list(set(config_dict.keys()).difference(upper_list)) # Remove gates because they are in a different tab lower_list.remove('gates') upper_str = "<table>" upper_str += """<style> table { border-collapse: collapse; width: auto; } th, td { text-align: left; padding: 8px; } tr:nth-child(even) {background-color: #f6f6f6;} </style>""" footer = "</table>" # Upper HBox widget data upper_str += "<tr><th>Property</th><th>Value</th></tr>" for key in upper_list: upper_str += "<tr><td><font style='font-weight:bold'>%s</font></td><td>%s</td></tr>" % ( key, config_dict[key]) upper_str += footer upper_table = widgets.HTML( value=upper_str, layout=widgets.Layout(width='100%', grid_area='left')) image_widget = widgets.Output( layout=widgets.Layout(display='flex-inline', grid_area='right', padding='10px 10px 10px 10px', width='auto', max_height='300px', align_items='center')) if not config['simulator']: with image_widget: gate_map = plot_gate_map(backend) display(gate_map) plt.close(gate_map) lower_str = "<table>" lower_str += """<style> table { border-collapse: collapse; width: auto; } th, td { text-align: left; padding: 8px; } tr:nth-child(even) {background-color: #f6f6f6;} </style>""" lower_str += "<tr><th></th><th></th></tr>" for key in lower_list: if key != 'name': lower_str += "<tr><td>%s</td><td>%s</td></tr>" % ( key, config_dict[key]) lower_str += footer lower_table = widgets.HTML(value=lower_str, layout=widgets.Layout( width='auto', grid_area='bottom')) grid = widgets.GridBox(children=[upper_table, image_widget, lower_table], layout=widgets.Layout( grid_template_rows='auto auto', grid_template_columns='25% 25% 25% 25%', grid_template_areas=''' "left right right right" "bottom bottom bottom bottom" ''', grid_gap='0px 0px')) return grid
The qubits properties widget
def qubits_tab(backend): """The qubits properties widget Args: backend (IBMQbackend): The backend. Returns: VBox: A VBox widget. """ props = backend.properties().to_dict() header_html = "<div><font style='font-weight:bold'>{key}</font>: {value}</div>" header_html = header_html.format(key='last_update_date', value=props['last_update_date']) update_date_widget = widgets.HTML(value=header_html) qubit_html = "<table>" qubit_html += """<style> table { border-collapse: collapse; width: auto; } th, td { text-align: left; padding: 8px; } tr:nth-child(even) {background-color: #f6f6f6;} </style>""" qubit_html += "<tr><th></th><th>Frequency</th><th>T1</th><th>T2</th>" qubit_html += "<th>U1 gate error</th><th>U2 gate error</th><th>U3 gate error</th>" qubit_html += "<th>Readout error</th></tr>" qubit_footer = "</table>" for qub in range(len(props['qubits'])): name = 'Q%s' % qub qubit_data = props['qubits'][qub] gate_data = props['gates'][3*qub:3*qub+3] t1_info = qubit_data[0] t2_info = qubit_data[1] freq_info = qubit_data[2] readout_info = qubit_data[3] freq = str(round(freq_info['value'], 5))+' '+freq_info['unit'] T1 = str(round(t1_info['value'], # pylint: disable=invalid-name 5))+' ' + t1_info['unit'] T2 = str(round(t2_info['value'], # pylint: disable=invalid-name 5))+' ' + t2_info['unit'] # pylint: disable=invalid-name U1 = str(round(gate_data[0]['parameters'][0]['value'], 5)) # pylint: disable=invalid-name U2 = str(round(gate_data[1]['parameters'][0]['value'], 5)) # pylint: disable=invalid-name U3 = str(round(gate_data[2]['parameters'][0]['value'], 5)) readout_error = round(readout_info['value'], 5) qubit_html += "<tr><td><font style='font-weight:bold'>%s</font></td><td>%s</td>" qubit_html += "<td>%s</td><td>%s</td><td>%s</td><td>%s</td><td>%s</td><td>%s</td></tr>" qubit_html = qubit_html % (name, freq, T1, T2, U1, U2, U3, readout_error) qubit_html += qubit_footer qubit_widget = widgets.HTML(value=qubit_html) out = widgets.VBox([update_date_widget, qubit_widget]) return out
The multiple qubit gate error widget.
def gates_tab(backend): """The multiple qubit gate error widget. Args: backend (IBMQbackend): The backend. Returns: VBox: A VBox widget. """ config = backend.configuration().to_dict() props = backend.properties().to_dict() multi_qubit_gates = props['gates'][3*config['n_qubits']:] header_html = "<div><font style='font-weight:bold'>{key}</font>: {value}</div>" header_html = header_html.format(key='last_update_date', value=props['last_update_date']) update_date_widget = widgets.HTML(value=header_html, layout=widgets.Layout(grid_area='top')) gate_html = "<table>" gate_html += """<style> table { border-collapse: collapse; width: auto; } th, td { text-align: left; padding: 8px; } tr:nth-child(even) {background-color: #f6f6f6;}; </style>""" gate_html += "<tr><th></th><th>Type</th><th>Gate error</th></tr>" gate_footer = "</table>" # Split gates into two columns left_num = math.ceil(len(multi_qubit_gates)/3) mid_num = math.ceil((len(multi_qubit_gates)-left_num)/2) left_table = gate_html for qub in range(left_num): gate = multi_qubit_gates[qub] name = gate['name'] ttype = gate['gate'] error = round(gate['parameters'][0]['value'], 5) left_table += "<tr><td><font style='font-weight:bold'>%s</font>" left_table += "</td><td>%s</td><td>%s</td></tr>" left_table = left_table % (name, ttype, error) left_table += gate_footer middle_table = gate_html for qub in range(left_num, left_num+mid_num): gate = multi_qubit_gates[qub] name = gate['name'] ttype = gate['gate'] error = round(gate['parameters'][0]['value'], 5) middle_table += "<tr><td><font style='font-weight:bold'>%s</font>" middle_table += "</td><td>%s</td><td>%s</td></tr>" middle_table = middle_table % (name, ttype, error) middle_table += gate_footer right_table = gate_html for qub in range(left_num+mid_num, len(multi_qubit_gates)): gate = multi_qubit_gates[qub] name = gate['name'] ttype = gate['gate'] error = round(gate['parameters'][0]['value'], 5) right_table += "<tr><td><font style='font-weight:bold'>%s</font>" right_table += "</td><td>%s</td><td>%s</td></tr>" right_table = right_table % (name, ttype, error) right_table += gate_footer left_table_widget = widgets.HTML(value=left_table, layout=widgets.Layout(grid_area='left')) middle_table_widget = widgets.HTML(value=middle_table, layout=widgets.Layout(grid_area='middle')) right_table_widget = widgets.HTML(value=right_table, layout=widgets.Layout(grid_area='right')) grid = widgets.GridBox(children=[update_date_widget, left_table_widget, middle_table_widget, right_table_widget], layout=widgets.Layout( grid_template_rows='auto auto', grid_template_columns='33% 33% 33%', grid_template_areas=''' "top top top" "left middle right" ''', grid_gap='0px 0px')) return grid
Widget for displaying detailed noise map.
def detailed_map(backend): """Widget for displaying detailed noise map. Args: backend (IBMQbackend): The backend. Returns: GridBox: Widget holding noise map images. """ props = backend.properties().to_dict() config = backend.configuration().to_dict() single_gate_errors = [q['parameters'][0]['value'] for q in props['gates'][2:3*config['n_qubits']:3]] single_norm = matplotlib.colors.Normalize( vmin=min(single_gate_errors), vmax=max(single_gate_errors)) q_colors = [cm.viridis(single_norm(err)) for err in single_gate_errors] cmap = config['coupling_map'] cx_errors = [] for line in cmap: for item in props['gates'][3*config['n_qubits']:]: if item['qubits'] == line: cx_errors.append(item['parameters'][0]['value']) break else: continue cx_norm = matplotlib.colors.Normalize( vmin=min(cx_errors), vmax=max(cx_errors)) line_colors = [cm.viridis(cx_norm(err)) for err in cx_errors] single_widget = widgets.Output(layout=widgets.Layout(display='flex-inline', grid_area='left', align_items='center')) cmap_widget = widgets.Output(layout=widgets.Layout(display='flex-inline', grid_area='top', width='auto', height='auto', align_items='center')) cx_widget = widgets.Output(layout=widgets.Layout(display='flex-inline', grid_area='right', align_items='center')) tick_locator = mpl.ticker.MaxNLocator(nbins=5) with cmap_widget: noise_map = plot_gate_map(backend, qubit_color=q_colors, line_color=line_colors, qubit_size=28, plot_directed=True) width, height = noise_map.get_size_inches() noise_map.set_size_inches(1.25*width, 1.25*height) display(noise_map) plt.close(noise_map) with single_widget: cbl_fig = plt.figure(figsize=(3, 1)) ax1 = cbl_fig.add_axes([0.05, 0.80, 0.9, 0.15]) single_cb = mpl.colorbar.ColorbarBase(ax1, cmap=cm.viridis, norm=single_norm, orientation='horizontal') single_cb.locator = tick_locator single_cb.update_ticks() ax1.set_title('Single-qubit U3 error rate') display(cbl_fig) plt.close(cbl_fig) with cx_widget: cx_fig = plt.figure(figsize=(3, 1)) ax2 = cx_fig.add_axes([0.05, 0.80, 0.9, 0.15]) cx_cb = mpl.colorbar.ColorbarBase(ax2, cmap=cm.viridis, norm=cx_norm, orientation='horizontal') cx_cb.locator = tick_locator cx_cb.update_ticks() ax2.set_title('CNOT error rate') display(cx_fig) plt.close(cx_fig) out_box = widgets.GridBox([single_widget, cmap_widget, cx_widget], layout=widgets.Layout( grid_template_rows='auto auto', grid_template_columns='33% 33% 33%', grid_template_areas=''' "top top top" "left . right" ''', grid_gap='0px 0px')) return out_box
Widget for displaying job history
def job_history(backend): """Widget for displaying job history Args: backend (IBMQbackend): The backend. Returns: Tab: A tab widget for history images. """ year = widgets.Output(layout=widgets.Layout(display='flex-inline', align_items='center', min_height='400px')) month = widgets.Output(layout=widgets.Layout(display='flex-inline', align_items='center', min_height='400px')) week = widgets.Output(layout=widgets.Layout(display='flex-inline', align_items='center', min_height='400px')) tabs = widgets.Tab(layout=widgets.Layout(max_height='620px')) tabs.children = [year, month, week] tabs.set_title(0, 'Year') tabs.set_title(1, 'Month') tabs.set_title(2, 'Week') tabs.selected_index = 1 _build_job_history(tabs, backend) return tabs
Plots the job history of the user from the given list of jobs.
def plot_job_history(jobs, interval='year'): """Plots the job history of the user from the given list of jobs. Args: jobs (list): A list of jobs with type IBMQjob. interval (str): Interval over which to examine. Returns: fig: A Matplotlib figure instance. """ def get_date(job): """Returns a datetime object from a IBMQJob instance. Args: job (IBMQJob): A job. Returns: dt: A datetime object. """ return datetime.datetime.strptime(job.creation_date(), '%Y-%m-%dT%H:%M:%S.%fZ') current_time = datetime.datetime.now() if interval == 'year': bins = [(current_time - datetime.timedelta(days=k*365/12)) for k in range(12)] elif interval == 'month': bins = [(current_time - datetime.timedelta(days=k)) for k in range(30)] elif interval == 'week': bins = [(current_time - datetime.timedelta(days=k)) for k in range(7)] binned_jobs = [0]*len(bins) if interval == 'year': for job in jobs: for ind, dat in enumerate(bins): date = get_date(job) if date.month == dat.month: binned_jobs[ind] += 1 break else: continue else: for job in jobs: for ind, dat in enumerate(bins): date = get_date(job) if date.day == dat.day and date.month == dat.month: binned_jobs[ind] += 1 break else: continue nz_bins = [] nz_idx = [] for ind, val in enumerate(binned_jobs): if val != 0: nz_idx.append(ind) nz_bins.append(val) total_jobs = sum(binned_jobs) colors = ['#003f5c', '#ffa600', '#374c80', '#ff764a', '#7a5195', '#ef5675', '#bc5090'] if interval == 'year': labels = ['{}-{}'.format(str(bins[b].year)[2:], bins[b].month) for b in nz_idx] else: labels = ['{}-{}'.format(bins[b].month, bins[b].day) for b in nz_idx] fig, ax = plt.subplots(1, 1, figsize=(5, 5)) # pylint: disable=invalid-name ax.pie(nz_bins[::-1], labels=labels, colors=colors, textprops={'fontsize': 14}, rotatelabels=True, counterclock=False) ax.add_artist(Circle((0, 0), 0.7, color='white', zorder=1)) ax.text(0, 0, total_jobs, horizontalalignment='center', verticalalignment='center', fontsize=26) fig.tight_layout() return fig
Return a new circuit that has been optimized.
def run(self, dag): """Return a new circuit that has been optimized.""" resets = dag.op_nodes(Reset) for reset in resets: predecessor = next(dag.predecessors(reset)) if predecessor.type == 'in': dag.remove_op_node(reset) return dag
Plot the interpolated envelope of pulse.
def draw(self, **kwargs): """Plot the interpolated envelope of pulse. Keyword Args: dt (float): Time interval of samples. interp_method (str): Method of interpolation (set `None` for turn off the interpolation). filename (str): Name required to save pulse image. interactive (bool): When set true show the circuit in a new window (this depends on the matplotlib backend being used supporting this). dpi (int): Resolution of saved image. nop (int): Data points for interpolation. size (tuple): Size of figure. """ from qiskit.tools.visualization import pulse_drawer return pulse_drawer(self._samples, self.duration, **kwargs)
Apply cu3 from ctl to tgt with angle theta phi lam.
def cu3(self, theta, phi, lam, ctl, tgt): """Apply cu3 from ctl to tgt with angle theta, phi, lam.""" return self.append(Cu3Gate(theta, phi, lam), [ctl, tgt], [])
gate cu3 ( theta phi lambda ) c t { u1 (( lambda - phi )/ 2 ) t ; cx c t ; u3 ( - theta/ 2 0 - ( phi + lambda )/ 2 ) t ; cx c t ; u3 ( theta/ 2 phi 0 ) t ; }
def _define(self): """ gate cu3(theta,phi,lambda) c, t { u1((lambda-phi)/2) t; cx c,t; u3(-theta/2,0,-(phi+lambda)/2) t; cx c,t; u3(theta/2,phi,0) t; } """ definition = [] q = QuantumRegister(2, "q") rule = [ (U1Gate((self.params[2] - self.params[1]) / 2), [q[1]], []), (CnotGate(), [q[0], q[1]], []), (U3Gate(-self.params[0] / 2, 0, -(self.params[1] + self.params[2]) / 2), [q[1]], []), (CnotGate(), [q[0], q[1]], []), (U3Gate(self.params[0] / 2, self.params[1], 0), [q[1]], []) ] for inst in rule: definition.append(inst) self.definition = definition
Returns a circuit putting 2 qubits in the Bell state.
def build_bell_circuit(): """Returns a circuit putting 2 qubits in the Bell state.""" q = QuantumRegister(2) c = ClassicalRegister(2) qc = QuantumCircuit(q, c) qc.h(q[0]) qc.cx(q[0], q[1]) qc.measure(q, c) return qc
transpile one or more circuits according to some desired transpilation targets.
def transpile(circuits, backend=None, basis_gates=None, coupling_map=None, backend_properties=None, initial_layout=None, seed_transpiler=None, optimization_level=None, pass_manager=None, seed_mapper=None): # deprecated """transpile one or more circuits, according to some desired transpilation targets. All arguments may be given as either singleton or list. In case of list, the length must be equal to the number of circuits being transpiled. Transpilation is done in parallel using multiprocessing. Args: circuits (QuantumCircuit or list[QuantumCircuit]): Circuit(s) to transpile backend (BaseBackend): If set, transpiler options are automatically grabbed from backend.configuration() and backend.properties(). If any other option is explicitly set (e.g. coupling_map), it will override the backend's. Note: the backend arg is purely for convenience. The resulting circuit may be run on any backend as long as it is compatible. basis_gates (list[str]): List of basis gate names to unroll to. e.g: ['u1', 'u2', 'u3', 'cx'] If None, do not unroll. coupling_map (CouplingMap or list): Coupling map (perhaps custom) to target in mapping. Multiple formats are supported: a. CouplingMap instance b. list Must be given as an adjacency matrix, where each entry specifies all two-qubit interactions supported by backend e.g: [[0, 1], [0, 3], [1, 2], [1, 5], [2, 5], [4, 1], [5, 3]] backend_properties (BackendProperties): properties returned by a backend, including information on gate errors, readout errors, qubit coherence times, etc. For a backend that provides this information, it can be obtained with: ``backend.properties()`` initial_layout (Layout or dict or list): Initial position of virtual qubits on physical qubits. If this layout makes the circuit compatible with the coupling_map constraints, it will be used. The final layout is not guaranteed to be the same, as the transpiler may permute qubits through swaps or other means. Multiple formats are supported: a. Layout instance b. dict virtual to physical: {qr[0]: 0, qr[1]: 3, qr[2]: 5} physical to virtual: {0: qr[0], 3: qr[1], 5: qr[2]} c. list virtual to physical: [0, 3, 5] # virtual qubits are ordered (in addition to named) physical to virtual: [qr[0], None, None, qr[1], None, qr[2]] seed_transpiler (int): sets random seed for the stochastic parts of the transpiler optimization_level (int): How much optimization to perform on the circuits. Higher levels generate more optimized circuits, at the expense of longer transpilation time. 0: no optimization 1: light optimization 2: heavy optimization pass_manager (PassManager): The pass manager to use for a custom pipeline of transpiler passes. If this arg is present, all other args will be ignored and the pass manager will be used directly (Qiskit will not attempt to auto-select a pass manager based on transpile options). seed_mapper (int): DEPRECATED in 0.8: use ``seed_transpiler`` kwarg instead Returns: QuantumCircuit or list[QuantumCircuit]: transpiled circuit(s). Raises: TranspilerError: in case of bad inputs to transpiler or errors in passes """ # Deprecation matter if seed_mapper: warnings.warn("seed_mapper has been deprecated and will be removed in the " "0.9 release. Instead use seed_transpiler to set the seed " "for all stochastic parts of the.", DeprecationWarning) seed_transpiler = seed_mapper # transpiling schedules is not supported yet. if isinstance(circuits, Schedule) or \ (isinstance(circuits, list) and all(isinstance(c, Schedule) for c in circuits)): return circuits # Get TranspileConfig(s) to configure the circuit transpilation job(s) circuits = circuits if isinstance(circuits, list) else [circuits] transpile_configs = _parse_transpile_args(circuits, backend, basis_gates, coupling_map, backend_properties, initial_layout, seed_transpiler, optimization_level, pass_manager) # Transpile circuits in parallel circuits = parallel_map(_transpile_circuit, list(zip(circuits, transpile_configs))) if len(circuits) == 1: return circuits[0] return circuits
Select a PassManager and run a single circuit through it.
def _transpile_circuit(circuit_config_tuple): """Select a PassManager and run a single circuit through it. Args: circuit_config_tuple (tuple): circuit (QuantumCircuit): circuit to transpile transpile_config (TranspileConfig): configuration dictating how to transpile Returns: QuantumCircuit: transpiled circuit """ circuit, transpile_config = circuit_config_tuple # if the pass manager is not already selected, choose an appropriate one. if transpile_config.pass_manager: pass_manager = transpile_config.pass_manager elif transpile_config.coupling_map: pass_manager = default_pass_manager(transpile_config.basis_gates, transpile_config.coupling_map, transpile_config.initial_layout, transpile_config.seed_transpiler) else: pass_manager = default_pass_manager_simulator(transpile_config.basis_gates) return pass_manager.run(circuit)
Resolve the various types of args allowed to the transpile () function through duck typing overriding args etc. Refer to the transpile () docstring for details on what types of inputs are allowed.
def _parse_transpile_args(circuits, backend, basis_gates, coupling_map, backend_properties, initial_layout, seed_transpiler, optimization_level, pass_manager): """Resolve the various types of args allowed to the transpile() function through duck typing, overriding args, etc. Refer to the transpile() docstring for details on what types of inputs are allowed. Here the args are resolved by converting them to standard instances, and prioritizing them in case a transpile option is passed through multiple args (explicitly setting an arg has more priority than the arg set by backend) Returns: list[TranspileConfig]: a transpile config for each circuit, which is a standardized object that configures the transpiler and determines the pass manager to use. """ # Each arg could be single or a list. If list, it must be the same size as # number of circuits. If single, duplicate to create a list of that size. num_circuits = len(circuits) basis_gates = _parse_basis_gates(basis_gates, backend, circuits) coupling_map = _parse_coupling_map(coupling_map, backend, num_circuits) backend_properties = _parse_backend_properties(backend_properties, backend, num_circuits) initial_layout = _parse_initial_layout(initial_layout, circuits) seed_transpiler = _parse_seed_transpiler(seed_transpiler, num_circuits) optimization_level = _parse_optimization_level(optimization_level, num_circuits) pass_manager = _parse_pass_manager(pass_manager, num_circuits) transpile_configs = [] for args in zip(basis_gates, coupling_map, backend_properties, initial_layout, seed_transpiler, optimization_level, pass_manager): transpile_config = TranspileConfig(basis_gates=args[0], coupling_map=args[1], backend_properties=args[2], initial_layout=args[3], seed_transpiler=args[4], optimization_level=args[5], pass_manager=args[6]) transpile_configs.append(transpile_config) return transpile_configs
Execute a list of circuits or pulse schedules on a backend.
def execute(experiments, backend, basis_gates=None, coupling_map=None, # circuit transpile options backend_properties=None, initial_layout=None, seed_transpiler=None, optimization_level=None, pass_manager=None, qobj_id=None, qobj_header=None, shots=1024, # common run options memory=False, max_credits=10, seed_simulator=None, default_qubit_los=None, default_meas_los=None, # schedule run options schedule_los=None, meas_level=2, meas_return='avg', memory_slots=None, memory_slot_size=100, rep_time=None, parameter_binds=None, seed=None, seed_mapper=None, # deprecated config=None, circuits=None, **run_config): """Execute a list of circuits or pulse schedules on a backend. The execution is asynchronous, and a handle to a job instance is returned. Args: experiments (QuantumCircuit or list[QuantumCircuit] or Schedule or list[Schedule]): Circuit(s) or pulse schedule(s) to execute backend (BaseBackend): Backend to execute circuits on. Transpiler options are automatically grabbed from backend.configuration() and backend.properties(). If any other option is explicitly set (e.g. coupling_map), it will override the backend's. basis_gates (list[str]): List of basis gate names to unroll to. e.g: ['u1', 'u2', 'u3', 'cx'] If None, do not unroll. coupling_map (CouplingMap or list): Coupling map (perhaps custom) to target in mapping. Multiple formats are supported: a. CouplingMap instance b. list Must be given as an adjacency matrix, where each entry specifies all two-qubit interactions supported by backend e.g: [[0, 1], [0, 3], [1, 2], [1, 5], [2, 5], [4, 1], [5, 3]] backend_properties (BackendProperties): Properties returned by a backend, including information on gate errors, readout errors, qubit coherence times, etc. For a backend that provides this information, it can be obtained with: ``backend.properties()`` initial_layout (Layout or dict or list): Initial position of virtual qubits on physical qubits. If this layout makes the circuit compatible with the coupling_map constraints, it will be used. The final layout is not guaranteed to be the same, as the transpiler may permute qubits through swaps or other means. Multiple formats are supported: a. Layout instance b. dict virtual to physical: {qr[0]: 0, qr[1]: 3, qr[2]: 5} physical to virtual: {0: qr[0], 3: qr[1], 5: qr[2]} c. list virtual to physical: [0, 3, 5] # virtual qubits are ordered (in addition to named) physical to virtual: [qr[0], None, None, qr[1], None, qr[2]] seed_transpiler (int): Sets random seed for the stochastic parts of the transpiler optimization_level (int): How much optimization to perform on the circuits. Higher levels generate more optimized circuits, at the expense of longer transpilation time. 0: no optimization 1: light optimization 2: heavy optimization pass_manager (PassManager): The pass manager to use during transpilation. If this arg is present, auto-selection of pass manager based on the transpile options will be turned off and this pass manager will be used directly. qobj_id (str): String identifier to annotate the Qobj qobj_header (QobjHeader or dict): User input that will be inserted in Qobj header, and will also be copied to the corresponding Result header. Headers do not affect the run. shots (int): Number of repetitions of each circuit, for sampling. Default: 2014 memory (bool): If True, per-shot measurement bitstrings are returned as well (provided the backend supports it). For OpenPulse jobs, only measurement level 2 supports this option. Default: False max_credits (int): Maximum credits to spend on job. Default: 10 seed_simulator (int): Random seed to control sampling, for when backend is a simulator default_qubit_los (list): List of default qubit lo frequencies default_meas_los (list): List of default meas lo frequencies schedule_los (None or list[Union[Dict[PulseChannel, float], LoConfig]] or Union[Dict[PulseChannel, float], LoConfig]): Experiment LO configurations meas_level (int): Set the appropriate level of the measurement output for pulse experiments. meas_return (str): Level of measurement data for the backend to return For `meas_level` 0 and 1: "single" returns information from every shot. "avg" returns average measurement output (averaged over number of shots). memory_slots (int): Number of classical memory slots used in this job. memory_slot_size (int): Size of each memory slot if the output is Level 0. rep_time (int): repetition time of the experiment in μs. The delay between experiments will be rep_time. Must be from the list provided by the device. parameter_binds (list[dict{Parameter: Value}]): List of Parameter bindings over which the set of experiments will be executed. Each list element (bind) should be of the form {Parameter1: value1, Parameter2: value2, ...}. All binds will be executed across all experiments, e.g. if parameter_binds is a length-n list, and there are m experiments, a total of m x n experiments will be run (one for each experiment/bind pair). seed (int): DEPRECATED in 0.8: use ``seed_simulator`` kwarg instead seed_mapper (int): DEPRECATED in 0.8: use ``seed_transpiler`` kwarg instead config (dict): DEPRECATED in 0.8: use run_config instead circuits (QuantumCircuit or list[QuantumCircuit]): DEPRECATED in 0.8: use ``experiments`` kwarg instead. run_config (dict): Extra arguments used to configure the run (e.g. for Aer configurable backends) Refer to the backend documentation for details on these arguments Note: for now, these keyword arguments will both be copied to the Qobj config, and passed to backend.run() Returns: BaseJob: returns job instance derived from BaseJob Raises: QiskitError: if the execution cannot be interpreted as either circuits or schedules """ if circuits is not None: experiments = circuits warnings.warn("the `circuits` arg in `execute()` has been deprecated. " "please use `experiments`, which can handle both circuit " "and pulse Schedules", DeprecationWarning) # transpiling the circuits using given transpile options experiments = transpile(experiments, basis_gates=basis_gates, coupling_map=coupling_map, backend_properties=backend_properties, initial_layout=initial_layout, seed_transpiler=seed_transpiler, optimization_level=optimization_level, backend=backend, pass_manager=pass_manager, seed_mapper=seed_mapper, # deprecated ) # assembling the circuits into a qobj to be run on the backend qobj = assemble(experiments, qobj_id=qobj_id, qobj_header=qobj_header, shots=shots, memory=memory, max_credits=max_credits, seed_simulator=seed_simulator, default_qubit_los=default_qubit_los, default_meas_los=default_meas_los, schedule_los=schedule_los, meas_level=meas_level, meas_return=meas_return, memory_slots=memory_slots, memory_slot_size=memory_slot_size, rep_time=rep_time, parameter_binds=parameter_binds, backend=backend, config=config, # deprecated seed=seed, # deprecated run_config=run_config ) # executing the circuits on the backend and returning the job return backend.run(qobj, **run_config)
Return the primary drive channel of this qubit.
def drive(self) -> DriveChannel: """Return the primary drive channel of this qubit.""" if self._drives: return self._drives[0] else: raise PulseError("No drive channels in q[%d]" % self._index)
Return the primary control channel of this qubit.
def control(self) -> ControlChannel: """Return the primary control channel of this qubit.""" if self._controls: return self._controls[0] else: raise PulseError("No control channels in q[%d]" % self._index)
Return the primary measure channel of this qubit.
def measure(self) -> MeasureChannel: """Return the primary measure channel of this qubit.""" if self._measures: return self._measures[0] else: raise PulseError("No measurement channels in q[%d]" % self._index)
Return the primary acquire channel of this qubit.
def acquire(self) -> AcquireChannel: """Return the primary acquire channel of this qubit.""" if self._acquires: return self._acquires[0] else: raise PulseError("No acquire channels in q[%d]" % self._index)
n - qubit input state for QFT that produces output 1.
def input_state(circ, q, n): """n-qubit input state for QFT that produces output 1.""" for j in range(n): circ.h(q[j]) circ.u1(math.pi/float(2**(j)), q[j]).inverse()
Assembles a list of circuits into a qobj which can be run on the backend.
def assemble_circuits(circuits, qobj_id=None, qobj_header=None, run_config=None): """Assembles a list of circuits into a qobj which can be run on the backend. Args: circuits (list[QuantumCircuits]): circuit(s) to assemble qobj_id (int): identifier for the generated qobj qobj_header (QobjHeader): header to pass to the results run_config (RunConfig): configuration of the runtime environment Returns: QasmQobj: the Qobj to be run on the backends """ qobj_config = QasmQobjConfig() if run_config: qobj_config = QasmQobjConfig(**run_config.to_dict()) # Pack everything into the Qobj experiments = [] max_n_qubits = 0 max_memory_slots = 0 for circuit in circuits: # header stuff n_qubits = 0 memory_slots = 0 qubit_labels = [] clbit_labels = [] qreg_sizes = [] creg_sizes = [] for qreg in circuit.qregs: qreg_sizes.append([qreg.name, qreg.size]) for j in range(qreg.size): qubit_labels.append([qreg.name, j]) n_qubits += qreg.size for creg in circuit.cregs: creg_sizes.append([creg.name, creg.size]) for j in range(creg.size): clbit_labels.append([creg.name, j]) memory_slots += creg.size # TODO: why do we need creq_sizes and qreg_sizes in header # TODO: we need to rethink memory_slots as they are tied to classical bit experimentheader = QobjExperimentHeader(qubit_labels=qubit_labels, n_qubits=n_qubits, qreg_sizes=qreg_sizes, clbit_labels=clbit_labels, memory_slots=memory_slots, creg_sizes=creg_sizes, name=circuit.name) # TODO: why do we need n_qubits and memory_slots in both the header and the config experimentconfig = QasmQobjExperimentConfig(n_qubits=n_qubits, memory_slots=memory_slots) # Convert conditionals from QASM-style (creg ?= int) to qobj-style # (register_bit ?= 1), by assuming device has unlimited register slots # (supported only for simulators). Map all measures to a register matching # their clbit_index, create a new register slot for every conditional gate # and add a bfunc to map the creg=val mask onto the gating register bit. is_conditional_experiment = any(op.control for (op, qargs, cargs) in circuit.data) max_conditional_idx = 0 instructions = [] for op_context in circuit.data: instruction = op_context[0].assemble() # Add register attributes to the instruction qargs = op_context[1] cargs = op_context[2] if qargs: qubit_indices = [qubit_labels.index([qubit[0].name, qubit[1]]) for qubit in qargs] instruction.qubits = qubit_indices if cargs: clbit_indices = [clbit_labels.index([clbit[0].name, clbit[1]]) for clbit in cargs] instruction.memory = clbit_indices # If the experiment has conditional instructions, assume every # measurement result may be needed for a conditional gate. if instruction.name == "measure" and is_conditional_experiment: instruction.register = clbit_indices # To convert to a qobj-style conditional, insert a bfunc prior # to the conditional instruction to map the creg ?= val condition # onto a gating register bit. if hasattr(instruction, '_control'): ctrl_reg, ctrl_val = instruction._control mask = 0 val = 0 for clbit in clbit_labels: if clbit[0] == ctrl_reg.name: mask |= (1 << clbit_labels.index(clbit)) val |= (((ctrl_val >> clbit[1]) & 1) << clbit_labels.index(clbit)) conditional_reg_idx = memory_slots + max_conditional_idx conversion_bfunc = QasmQobjInstruction(name='bfunc', mask="0x%X" % mask, relation='==', val="0x%X" % val, register=conditional_reg_idx) instructions.append(conversion_bfunc) instruction.conditional = conditional_reg_idx max_conditional_idx += 1 # Delete control attribute now that we have replaced it with # the conditional and bfuc del instruction._control instructions.append(instruction) experiments.append(QasmQobjExperiment(instructions=instructions, header=experimentheader, config=experimentconfig)) if n_qubits > max_n_qubits: max_n_qubits = n_qubits if memory_slots > max_memory_slots: max_memory_slots = memory_slots qobj_config.memory_slots = max_memory_slots qobj_config.n_qubits = max_n_qubits return QasmQobj(qobj_id=qobj_id, config=qobj_config, experiments=experiments, header=qobj_header)
Assembles a list of schedules into a qobj which can be run on the backend. Args: schedules ( list [ Schedule ] ): schedules to assemble qobj_id ( int ): identifier for the generated qobj qobj_header ( QobjHeader ): header to pass to the results run_config ( RunConfig ): configuration of the runtime environment Returns: PulseQobj: the Qobj to be run on the backends Raises: QiskitError: when invalid schedules or configs are provided
def assemble_schedules(schedules, qobj_id=None, qobj_header=None, run_config=None): """Assembles a list of schedules into a qobj which can be run on the backend. Args: schedules (list[Schedule]): schedules to assemble qobj_id (int): identifier for the generated qobj qobj_header (QobjHeader): header to pass to the results run_config (RunConfig): configuration of the runtime environment Returns: PulseQobj: the Qobj to be run on the backends Raises: QiskitError: when invalid schedules or configs are provided """ qobj_config = QasmQobjConfig() if run_config: qobj_config = QasmQobjConfig(**run_config.to_dict()) # Get appropriate convertors instruction_converter = PulseQobjConverter instruction_converter = instruction_converter(PulseQobjInstruction, **run_config.to_dict()) lo_converter = LoConfigConverter(PulseQobjExperimentConfig, run_config.qubit_lo_freq, run_config.meas_lo_freq, **run_config.to_dict()) # Pack everything into the Qobj qobj_schedules = [] user_pulselib = set() for idx, schedule in enumerate(schedules): # instructions qobj_instructions = [] # Instructions are returned as tuple of shifted time and instruction for shift, instruction in schedule.instructions: # TODO: support conditional gate qobj_instructions.append(instruction_converter(shift, instruction)) if isinstance(instruction, PulseInstruction): # add samples to pulse library user_pulselib.add(instruction.command) # experiment header qobj_experiment_header = QobjExperimentHeader( name=schedule.name or 'Experiment-%d' % idx ) qobj_schedules.append({ 'header': qobj_experiment_header, 'instructions': qobj_instructions }) # setup pulse_library run_config.pulse_library = [QobjPulseLibrary(name=pulse.name, samples=pulse.samples) for pulse in user_pulselib] # create qob experiment field experiments = [] if len(run_config.schedule_los) == 1: lo_dict = run_config.schedule_los.pop() # update global config q_los = lo_converter.get_qubit_los(lo_dict) if q_los: run_config.qubit_lo_freq = q_los m_los = lo_converter.get_meas_los(lo_dict) if m_los: run_config.meas_lo_freq = m_los if run_config.schedule_los: # multiple frequency setups if len(qobj_schedules) == 1: # frequency sweep for lo_dict in run_config.schedule_los: experiments.append(PulseQobjExperiment( instructions=qobj_schedules[0]['instructions'], experimentheader=qobj_schedules[0]['header'], experimentconfig=lo_converter(lo_dict) )) elif len(qobj_schedules) == len(run_config.schedule_los): # n:n setup for lo_dict, schedule in zip(run_config.schedule_los, qobj_schedules): experiments.append(PulseQobjExperiment( instructions=schedule['instructions'], experimentheader=schedule['header'], experimentconfig=lo_converter(lo_dict) )) else: raise QiskitError('Invalid LO setting is specified. ' 'The LO should be configured for each schedule, or ' 'single setup for all schedules (unique), or ' 'multiple setups for a single schedule (frequency sweep),' 'or no LO configured at all.') else: # unique frequency setup for schedule in qobj_schedules: experiments.append(PulseQobjExperiment( instructions=schedule['instructions'], experimentheader=schedule['header'], )) qobj_config = PulseQobjConfig(**run_config.to_dict()) return PulseQobj(qobj_id=qobj_id, config=qobj_config, experiments=experiments, header=qobj_header)
Assemble a list of circuits or pulse schedules into a Qobj.
def assemble(experiments, backend=None, qobj_id=None, qobj_header=None, # common run options shots=1024, memory=False, max_credits=None, seed_simulator=None, default_qubit_los=None, default_meas_los=None, # schedule run options schedule_los=None, meas_level=2, meas_return='avg', memory_slots=None, memory_slot_size=100, rep_time=None, parameter_binds=None, config=None, seed=None, # deprecated **run_config): """Assemble a list of circuits or pulse schedules into a Qobj. This function serializes the payloads, which could be either circuits or schedules, to create Qobj "experiments". It further annotates the experiment payload with header and configurations. Args: experiments (QuantumCircuit or list[QuantumCircuit] or Schedule or list[Schedule]): Circuit(s) or pulse schedule(s) to execute backend (BaseBackend): If set, some runtime options are automatically grabbed from backend.configuration() and backend.defaults(). If any other option is explicitly set (e.g. rep_rate), it will override the backend's. If any other options is set in the run_config, it will also override the backend's. qobj_id (str): String identifier to annotate the Qobj qobj_header (QobjHeader or dict): User input that will be inserted in Qobj header, and will also be copied to the corresponding Result header. Headers do not affect the run. shots (int): Number of repetitions of each circuit, for sampling. Default: 2014 memory (bool): If True, per-shot measurement bitstrings are returned as well (provided the backend supports it). For OpenPulse jobs, only measurement level 2 supports this option. Default: False max_credits (int): Maximum credits to spend on job. Default: 10 seed_simulator (int): Random seed to control sampling, for when backend is a simulator default_qubit_los (list): List of default qubit lo frequencies default_meas_los (list): List of default meas lo frequencies schedule_los (None or list[Union[Dict[PulseChannel, float], LoConfig]] or Union[Dict[PulseChannel, float], LoConfig]): Experiment LO configurations meas_level (int): Set the appropriate level of the measurement output for pulse experiments. meas_return (str): Level of measurement data for the backend to return For `meas_level` 0 and 1: "single" returns information from every shot. "avg" returns average measurement output (averaged over number of shots). memory_slots (int): Number of classical memory slots used in this job. memory_slot_size (int): Size of each memory slot if the output is Level 0. rep_time (int): repetition time of the experiment in μs. The delay between experiments will be rep_time. Must be from the list provided by the device. parameter_binds (list[dict{Parameter: Value}]): List of Parameter bindings over which the set of experiments will be executed. Each list element (bind) should be of the form {Parameter1: value1, Parameter2: value2, ...}. All binds will be executed across all experiments, e.g. if parameter_binds is a length-n list, and there are m experiments, a total of m x n experiments will be run (one for each experiment/bind pair). seed (int): DEPRECATED in 0.8: use ``seed_simulator`` kwarg instead config (dict): DEPRECATED in 0.8: use run_config instead run_config (dict): extra arguments used to configure the run (e.g. for Aer configurable backends) Refer to the backend documentation for details on these arguments Returns: Qobj: a qobj which can be run on a backend. Depending on the type of input, this will be either a QasmQobj or a PulseQobj. Raises: QiskitError: if the input cannot be interpreted as either circuits or schedules """ # deprecation matter if config: warnings.warn('config is not used anymore. Set all configs in ' 'run_config.', DeprecationWarning) run_config = run_config or config if seed: warnings.warn('seed is deprecated in favor of seed_simulator.', DeprecationWarning) seed_simulator = seed_simulator or seed # Get RunConfig(s) that will be inserted in Qobj to configure the run experiments = experiments if isinstance(experiments, list) else [experiments] qobj_id, qobj_header, run_config = _parse_run_args(backend, qobj_id, qobj_header, shots, memory, max_credits, seed_simulator, default_qubit_los, default_meas_los, schedule_los, meas_level, meas_return, memory_slots, memory_slot_size, rep_time, parameter_binds, **run_config) # assemble either circuits or schedules if all(isinstance(exp, QuantumCircuit) for exp in experiments): # If circuits are parameterized, bind parameters and remove from run_config bound_experiments, run_config = _expand_parameters(circuits=experiments, run_config=run_config) return assemble_circuits(circuits=bound_experiments, qobj_id=qobj_id, qobj_header=qobj_header, run_config=run_config) elif all(isinstance(exp, Schedule) for exp in experiments): return assemble_schedules(schedules=experiments, qobj_id=qobj_id, qobj_header=qobj_header, run_config=run_config) else: raise QiskitError("bad input to assemble() function; " "must be either circuits or schedules")
Resolve the various types of args allowed to the assemble () function through duck typing overriding args etc. Refer to the assemble () docstring for details on what types of inputs are allowed.
def _parse_run_args(backend, qobj_id, qobj_header, shots, memory, max_credits, seed_simulator, default_qubit_los, default_meas_los, schedule_los, meas_level, meas_return, memory_slots, memory_slot_size, rep_time, parameter_binds, **run_config): """Resolve the various types of args allowed to the assemble() function through duck typing, overriding args, etc. Refer to the assemble() docstring for details on what types of inputs are allowed. Here the args are resolved by converting them to standard instances, and prioritizing them in case a run option is passed through multiple args (explicitly setting an arg has more priority than the arg set by backend) Returns: RunConfig: a run config, which is a standardized object that configures the qobj and determines the runtime environment. """ # grab relevant info from backend if it exists backend_config = None backend_default = None if backend: backend_config = backend.configuration() # TODO : Remove usage of config.defaults when backend.defaults() is updated. try: backend_default = backend.defaults() except (ModelValidationError, AttributeError): from collections import namedtuple backend_config_defaults = getattr(backend_config, 'defaults', {}) BackendDefault = namedtuple('BackendDefault', ('qubit_freq_est', 'meas_freq_est')) backend_default = BackendDefault( qubit_freq_est=backend_config_defaults.get('qubit_freq_est'), meas_freq_est=backend_config_defaults.get('meas_freq_est') ) memory_slots = memory_slots or getattr(backend_config, 'memory_slots', None) rep_time = rep_time or getattr(backend_config, 'rep_times', None) if isinstance(rep_time, list): rep_time = rep_time[-1] parameter_binds = parameter_binds or [] # add default empty lo config schedule_los = schedule_los or [] if isinstance(schedule_los, (LoConfig, dict)): schedule_los = [schedule_los] # Convert to LoConfig if lo configuration supplied as dictionary schedule_los = [lo_config if isinstance(lo_config, LoConfig) else LoConfig(lo_config) for lo_config in schedule_los] qubit_lo_freq = default_qubit_los or getattr(backend_default, 'qubit_freq_est', []) meas_lo_freq = default_meas_los or getattr(backend_default, 'meas_freq_est', []) # an identifier for the Qobj qobj_id = qobj_id or str(uuid.uuid4()) # The header that goes at the top of the Qobj (and later Result) # we process it as dict, then write entries that are not None to a QobjHeader object qobj_header = qobj_header or {} if isinstance(qobj_header, QobjHeader): qobj_header = qobj_header.to_dict() backend_name = getattr(backend_config, 'backend_name', None) backend_version = getattr(backend_config, 'backend_version', None) qobj_header = {**dict(backend_name=backend_name, backend_version=backend_version), **qobj_header} qobj_header = QobjHeader(**{k: v for k, v in qobj_header.items() if v is not None}) # create run configuration and populate run_config_dict = dict(shots=shots, memory=memory, max_credits=max_credits, seed_simulator=seed_simulator, seed=seed_simulator, # deprecated qubit_lo_freq=qubit_lo_freq, meas_lo_freq=meas_lo_freq, schedule_los=schedule_los, meas_level=meas_level, meas_return=meas_return, memory_slots=memory_slots, memory_slot_size=memory_slot_size, rep_time=rep_time, parameter_binds=parameter_binds, **run_config) run_config = RunConfig(**{k: v for k, v in run_config_dict.items() if v is not None}) return qobj_id, qobj_header, run_config
Verifies that there is a single common set of parameters shared between all circuits and all parameter binds in the run_config. Returns an expanded list of circuits ( if parameterized ) with all parameters bound and a copy of the run_config with parameter_binds cleared.
def _expand_parameters(circuits, run_config): """Verifies that there is a single common set of parameters shared between all circuits and all parameter binds in the run_config. Returns an expanded list of circuits (if parameterized) with all parameters bound, and a copy of the run_config with parameter_binds cleared. If neither the circuits nor the run_config specify parameters, the two are returned unmodified. Raises: QiskitError: if run_config parameters are not compatible with circuit parameters Returns: Tuple(List[QuantumCircuit], RunConfig): - List of input circuits expanded and with parameters bound - RunConfig with parameter_binds removed """ parameter_binds = run_config.parameter_binds if parameter_binds or \ any(circuit.parameters for circuit in circuits): all_bind_parameters = [bind.keys() for bind in parameter_binds] all_circuit_parameters = [circuit.parameters for circuit in circuits] # Collect set of all unique parameters across all circuits and binds unique_parameters = set(param for param_list in all_bind_parameters + all_circuit_parameters for param in param_list) # Check that all parameters are common to all circuits and binds if not all_bind_parameters \ or not all_circuit_parameters \ or any(unique_parameters != bind_params for bind_params in all_bind_parameters) \ or any(unique_parameters != parameters for parameters in all_circuit_parameters): raise QiskitError( ('Mismatch between run_config.parameter_binds and all circuit parameters. ' + 'Parameter binds: {} ' + 'Circuit parameters: {}').format(all_bind_parameters, all_circuit_parameters)) circuits = [circuit.bind_parameters(binds) for circuit in circuits for binds in parameter_binds] # All parameters have been expanded and bound, so remove from run_config run_config = copy.deepcopy(run_config) run_config.parameter_binds = [] return circuits, run_config
Remove the handlers for the qiskit logger.
def unset_qiskit_logger(): """Remove the handlers for the 'qiskit' logger.""" qiskit_logger = logging.getLogger('qiskit') for handler in qiskit_logger.handlers: qiskit_logger.removeHandler(handler)
Create a hinton representation.
def iplot_state_hinton(rho, figsize=None): """ Create a hinton representation. Graphical representation of the input array using a 2D city style graph (hinton). Args: rho (array): Density matrix figsize (tuple): Figure size in pixels. """ # HTML html_template = Template(""" <p> <div id="hinton_$divNumber"></div> </p> """) # JavaScript javascript_template = Template(""" <script> requirejs.config({ paths: { qVisualization: "https://qvisualization.mybluemix.net/q-visualizations" } }); require(["qVisualization"], function(qVisualizations) { qVisualizations.plotState("hinton_$divNumber", "hinton", $executions, $options); }); </script> """) rho = _validate_input_state(rho) if figsize is None: options = {} else: options = {'width': figsize[0], 'height': figsize[1]} # Process data and execute div_number = str(time.time()) div_number = re.sub('[.]', '', div_number) # Process data and execute real = [] imag = [] for xvalue in rho: row_real = [] col_imag = [] for value_real in xvalue.real: row_real.append(float(value_real)) real.append(row_real) for value_imag in xvalue.imag: col_imag.append(float(value_imag)) imag.append(col_imag) html = html_template.substitute({ 'divNumber': div_number }) javascript = javascript_template.substitute({ 'divNumber': div_number, 'executions': [{'data': real}, {'data': imag}], 'options': options }) display(HTML(html + javascript))
Return the process fidelity between two quantum channels.
def process_fidelity(channel1, channel2, require_cptp=True): """Return the process fidelity between two quantum channels. This is given by F_p(E1, E2) = Tr[S2^dagger.S1])/dim^2 where S1 and S2 are the SuperOp matrices for channels E1 and E2, and dim is the dimension of the input output statespace. Args: channel1 (QuantumChannel or matrix): a quantum channel or unitary matrix. channel2 (QuantumChannel or matrix): a quantum channel or unitary matrix. require_cptp (bool): require input channels to be CPTP [Default: True]. Returns: array_like: The state fidelity F(state1, state2). Raises: QiskitError: if inputs channels do not have the same dimensions, have different input and output dimensions, or are not CPTP with `require_cptp=True`. """ # First we must determine if input is to be interpreted as a unitary matrix # or as a channel. # If input is a raw numpy array we will interpret it as a unitary matrix. is_cptp1 = None is_cptp2 = None if isinstance(channel1, (list, np.ndarray)): channel1 = Operator(channel1) if require_cptp: is_cptp1 = channel1.is_unitary() if isinstance(channel2, (list, np.ndarray)): channel2 = Operator(channel2) if require_cptp: is_cptp2 = channel2.is_unitary() # Next we convert inputs SuperOp objects # This works for objects that also have a `to_operator` or `to_channel` method s1 = SuperOp(channel1) s2 = SuperOp(channel2) # Check inputs are CPTP if require_cptp: # Only check SuperOp if we didn't already check unitary inputs if is_cptp1 is None: is_cptp1 = s1.is_cptp() if not is_cptp1: raise QiskitError('channel1 is not CPTP') if is_cptp2 is None: is_cptp2 = s2.is_cptp() if not is_cptp2: raise QiskitError('channel2 is not CPTP') # Check dimensions match input_dim1, output_dim1 = s1.dim input_dim2, output_dim2 = s2.dim if input_dim1 != output_dim1 or input_dim2 != output_dim2: raise QiskitError('Input channels must have same size input and output dimensions.') if input_dim1 != input_dim2: raise QiskitError('Input channels have different dimensions.') # Compute process fidelity fidelity = np.trace(s1.compose(s2.adjoint()).data) / (input_dim1 ** 2) return fidelity
Set the input text data.
def input(self, data): """Set the input text data.""" self.data = data self.lexer.input(data)
Pop a PLY lexer off the stack.
def pop(self): """Pop a PLY lexer off the stack.""" self.lexer = self.stack.pop() self.filename = self.lexer.qasm_file self.lineno = self.lexer.qasm_line
Push a PLY lexer on the stack to parse filename.
def push(self, filename): """Push a PLY lexer on the stack to parse filename.""" self.lexer.qasm_file = self.filename self.lexer.qasm_line = self.lineno self.stack.append(self.lexer) self.__mklexer__(filename)
include
def t_INCLUDE(self, t): 'include' # # Now eat up the next two tokens which must be # 1 - the name of the include file, and # 2 - a terminating semicolon # # Then push the current lexer onto the stack, create a new one from # the include file, and push it onto the stack. # # When we hit eof (the t_eof) rule, we pop. next_token = self.lexer.token() lineno = next_token.lineno # print('NEXT', next, "next.value", next.value, type(next)) if isinstance(next_token.value, str): incfile = next_token.value.strip('"') else: raise QasmError("Invalid include: must be a quoted string.") if incfile in CORE_LIBS: incfile = os.path.join(CORE_LIBS_PATH, incfile) next_token = self.lexer.token() if next_token is None or next_token.value != ';': raise QasmError('Invalid syntax, missing ";" at line', str(lineno)) if not os.path.exists(incfile): raise QasmError( 'Include file %s cannot be found, line %s, file %s' % (incfile, str(next_token.lineno), self.filename)) self.push(incfile) return self.lexer.token()
r [ a - z ] [ a - zA - Z0 - 9_ ] *
def t_ID(self, t): r'[a-z][a-zA-Z0-9_]*' t.type = self.reserved.get(t.value, 'ID') if t.type == 'ID': t.value = node.Id(t.value, self.lineno, self.filename) return t
r \ n +
def t_newline(self, t): r'\n+' self.lineno += len(t.value) t.lexer.lineno = self.lineno
Create device specification with values in backend configuration. Args: backend ( Backend ): backend configuration Returns: DeviceSpecification: created device specification Raises: PulseError: when an invalid backend is specified
def create_from(cls, backend): """ Create device specification with values in backend configuration. Args: backend(Backend): backend configuration Returns: DeviceSpecification: created device specification Raises: PulseError: when an invalid backend is specified """ backend_config = backend.configuration() # TODO : Remove usage of config.defaults when backend.defaults() is updated. try: backend_default = backend.defaults() except ModelValidationError: from collections import namedtuple BackendDefault = namedtuple('BackendDefault', ('qubit_freq_est', 'meas_freq_est')) backend_default = BackendDefault( qubit_freq_est=backend_config.defaults['qubit_freq_est'], meas_freq_est=backend_config.defaults['meas_freq_est'] ) # system size n_qubits = backend_config.n_qubits n_registers = backend_config.n_registers n_uchannels = backend_config.n_uchannels if n_uchannels > 0 and n_uchannels != n_qubits: raise PulseError("This version assumes no U-channels or #U-cannels==#qubits.") # frequency information qubit_lo_freqs = backend_default.qubit_freq_est qubit_lo_ranges = backend_config.qubit_lo_range meas_lo_freqs = backend_default.meas_freq_est meas_lo_ranges = backend_config.meas_lo_range # generate channels with assuming their numberings are aligned with qubits drives = [ DriveChannel(i, qubit_lo_freqs[i], tuple(qubit_lo_ranges[i])) for i in range(n_qubits) ] measures = [ MeasureChannel(i, meas_lo_freqs[i], tuple(meas_lo_ranges[i])) for i in range(n_qubits) ] acquires = [AcquireChannel(i) for i in range(n_qubits)] controls = [ControlChannel(i) for i in range(n_uchannels)] qubits = [] for i in range(n_qubits): # TODO: get qubits <-> channels relationship from backend qubit = Qubit(i, drive_channels=[drives[i]], control_channels=None if n_uchannels == 0 else controls[i], measure_channels=[measures[i]], acquire_channels=[acquires[i]]) qubits.append(qubit) registers = [RegisterSlot(i) for i in range(n_registers)] # TODO: get #mem_slots from backend mem_slots = [MemorySlot(i) for i in range(len(qubits))] return DeviceSpecification(qubits, registers, mem_slots)
iterate over each block and replace it with an equivalent Unitary on the same wires.
def run(self, dag): """iterate over each block and replace it with an equivalent Unitary on the same wires. """ new_dag = DAGCircuit() for qreg in dag.qregs.values(): new_dag.add_qreg(qreg) for creg in dag.cregs.values(): new_dag.add_creg(creg) # compute ordered indices for the global circuit wires global_index_map = {} for wire in dag.wires: if not isinstance(wire[0], QuantumRegister): continue global_qregs = list(dag.qregs.values()) global_index_map[wire] = global_qregs.index(wire[0]) + wire[1] blocks = self.property_set['block_list'] nodes_seen = set() for node in dag.topological_op_nodes(): # skip already-visited nodes or input/output nodes if node in nodes_seen or node.type == 'in' or node.type == 'out': continue # check if the node belongs to the next block if blocks and node in blocks[0]: block = blocks[0] # find the qubits involved in this block block_qargs = set() for nd in block: block_qargs |= set(nd.qargs) # convert block to a sub-circuit, then simulate unitary and add block_width = len(block_qargs) q = QuantumRegister(block_width) subcirc = QuantumCircuit(q) block_index_map = self._block_qargs_to_indices(block_qargs, global_index_map) for nd in block: nodes_seen.add(nd) subcirc.append(nd.op, [q[block_index_map[i]] for i in nd.qargs]) unitary = UnitaryGate(Operator(subcirc)) # simulates the circuit new_dag.apply_operation_back( unitary, sorted(block_qargs, key=lambda x: block_index_map[x])) del blocks[0] else: # the node could belong to some future block, but in that case # we simply skip it. It is guaranteed that we will revisit that # future block, via its other nodes for block in blocks[1:]: if node in block: break # freestanding nodes can just be added else: nodes_seen.add(node) new_dag.apply_operation_back(node.op, node.qargs, node.cargs) return new_dag
Map each qubit in block_qargs to its wire position among the block s wires. Args: block_qargs ( list ): list of qubits that a block acts on global_index_map ( dict ): mapping from each qubit in the circuit to its wire position within that circuit Returns: dict: mapping from qarg to position in block
def _block_qargs_to_indices(self, block_qargs, global_index_map): """ Map each qubit in block_qargs to its wire position among the block's wires. Args: block_qargs (list): list of qubits that a block acts on global_index_map (dict): mapping from each qubit in the circuit to its wire position within that circuit Returns: dict: mapping from qarg to position in block """ block_indices = [global_index_map[q] for q in block_qargs] ordered_block_indices = sorted(block_indices) block_positions = {q: ordered_block_indices.index(global_index_map[q]) for q in block_qargs} return block_positions
Get conversion method for instruction.
def get_bound_method(self, instruction): """Get conversion method for instruction.""" try: return self._bound_instructions[type(instruction)] except KeyError: raise PulseError('Qobj conversion method for %s is not found.' % instruction)
Return converted AcquireInstruction.
def convert_acquire(self, shift, instruction): """Return converted `AcquireInstruction`. Args: shift(int): Offset time. instruction (AcquireInstruction): acquire instruction. Returns: dict: Dictionary of required parameters. """ meas_level = self._run_config.get('meas_level', 2) command_dict = { 'name': 'acquire', 't0': shift+instruction.start_time, 'duration': instruction.duration, 'qubits': [q.index for q in instruction.acquires], 'memory_slot': [m.index for m in instruction.mem_slots] } if meas_level == 2: # setup discriminators if instruction.command.discriminator: command_dict.update({ 'discriminators': [ QobjMeasurementOption( name=instruction.command.discriminator.name, params=instruction.command.discriminator.params) ] }) # setup register_slots command_dict.update({ 'register_slot': [regs.index for regs in instruction.reg_slots] }) if meas_level >= 1: # setup kernels if instruction.command.kernel: command_dict.update({ 'kernels': [ QobjMeasurementOption( name=instruction.command.kernel.name, params=instruction.command.kernel.params) ] }) return self._qobj_model(**command_dict)
Return converted FrameChangeInstruction.
def convert_frame_change(self, shift, instruction): """Return converted `FrameChangeInstruction`. Args: shift(int): Offset time. instruction (FrameChangeInstruction): frame change instruction. Returns: dict: Dictionary of required parameters. """ command_dict = { 'name': 'fc', 't0': shift+instruction.start_time, 'ch': instruction.channels[0].name, 'phase': instruction.command.phase } return self._qobj_model(**command_dict)
Return converted PersistentValueInstruction.
def convert_persistent_value(self, shift, instruction): """Return converted `PersistentValueInstruction`. Args: shift(int): Offset time. instruction (PersistentValueInstruction): persistent value instruction. Returns: dict: Dictionary of required parameters. """ command_dict = { 'name': 'pv', 't0': shift+instruction.start_time, 'ch': instruction.channels[0].name, 'val': instruction.command.value } return self._qobj_model(**command_dict)
Return converted PulseInstruction.
def convert_drive(self, shift, instruction): """Return converted `PulseInstruction`. Args: shift(int): Offset time. instruction (PulseInstruction): drive instruction. Returns: dict: Dictionary of required parameters. """ command_dict = { 'name': instruction.command.name, 't0': shift+instruction.start_time, 'ch': instruction.channels[0].name } return self._qobj_model(**command_dict)
Return converted Snapshot.
def convert_snapshot(self, shift, instruction): """Return converted `Snapshot`. Args: shift(int): Offset time. instruction (Snapshot): snapshot instruction. Returns: dict: Dictionary of required parameters. """ command_dict = { 'name': 'snapshot', 't0': shift+instruction.start_time, 'label': instruction.name, 'type': instruction.type } return self._qobj_model(**command_dict)
Update annotations of discretized continuous pulse function with duration.
def _update_annotations(discretized_pulse: Callable) -> Callable: """Update annotations of discretized continuous pulse function with duration. Args: discretized_pulse: Discretized decorated continuous pulse. """ undecorated_annotations = list(discretized_pulse.__annotations__.items()) decorated_annotations = undecorated_annotations[1:] decorated_annotations.insert(0, ('duration', int)) discretized_pulse.__annotations__ = dict(decorated_annotations) return discretized_pulse
Update annotations of discretized continuous pulse function.
def _update_docstring(discretized_pulse: Callable, sampler_inst: Callable) -> Callable: """Update annotations of discretized continuous pulse function. Args: discretized_pulse: Discretized decorated continuous pulse. sampler_inst: Applied sampler. """ wrapped_docstring = pydoc.render_doc(discretized_pulse, '%s') header, body = wrapped_docstring.split('\n', 1) body = textwrap.indent(body, ' ') wrapped_docstring = header+body updated_ds = """ Discretized continuous pulse function: `{continuous_name}` using sampler: `{sampler_name}`. The first argument (time) of the continuous pulse function has been replaced with a discretized `duration` of type (int). Args: duration (int) *args: Remaining arguments of continuous pulse function. See continuous pulse function documentation below. **kwargs: Remaining kwargs of continuous pulse function. See continuous pulse function documentation below. Sampled continuous function: {continuous_doc} """.format(continuous_name=discretized_pulse.__name__, sampler_name=sampler_inst.__name__, continuous_doc=wrapped_docstring) discretized_pulse.__doc__ = updated_ds return discretized_pulse
Sampler decorator base method.
def sampler(sample_function: Callable) -> Callable: """Sampler decorator base method. Samplers are used for converting an continuous function to a discretized pulse. They operate on a function with the signature: `def f(times: np.ndarray, *args, **kwargs) -> np.ndarray` Where `times` is a numpy array of floats with length n_times and the output array is a complex numpy array with length n_times. The output of the decorator is an instance of `FunctionalPulse` with signature: `def g(duration: int, *args, **kwargs) -> SamplePulse` Note if your continuous pulse function outputs a `complex` scalar rather than a `np.ndarray`, you should first vectorize it before applying a sampler. This class implements the sampler boilerplate for the sampler. Args: sample_function: A sampler function to be decorated. """ def generate_sampler(continuous_pulse: Callable) -> Callable: """Return a decorated sampler function.""" @functools.wraps(continuous_pulse) def call_sampler(duration: int, *args, **kwargs) -> commands.SamplePulse: """Replace the call to the continuous function with a call to the sampler applied to the anlytic pulse function.""" sampled_pulse = sample_function(continuous_pulse, duration, *args, **kwargs) return np.asarray(sampled_pulse, dtype=np.complex_) # Update type annotations for wrapped continuous function to be discrete call_sampler = _update_annotations(call_sampler) # Update docstring with that of the sampler and include sampled function documentation. call_sampler = _update_docstring(call_sampler, sample_function) # Unset wrapped to return base sampler signature # but still get rest of benefits of wraps # such as __name__, __qualname__ call_sampler.__dict__.pop('__wrapped__') # wrap with functional pulse return commands.functional_pulse(call_sampler) return generate_sampler
Return the backends matching the specified filtering.
def filter_backends(backends, filters=None, **kwargs): """Return the backends matching the specified filtering. Filter the `backends` list by their `configuration` or `status` attributes, or from a boolean callable. The criteria for filtering can be specified via `**kwargs` or as a callable via `filters`, and the backends must fulfill all specified conditions. Args: backends (list[BaseBackend]): list of backends. filters (callable): filtering conditions as a callable. **kwargs (dict): dict of criteria. Returns: list[BaseBackend]: a list of backend instances matching the conditions. """ def _match_all(obj, criteria): """Return True if all items in criteria matches items in obj.""" return all(getattr(obj, key_, None) == value_ for key_, value_ in criteria.items()) # Inspect the backends to decide which filters belong to # backend.configuration and which ones to backend.status, as it does # not involve querying the API. configuration_filters = {} status_filters = {} for key, value in kwargs.items(): if all(key in backend.configuration() for backend in backends): configuration_filters[key] = value else: status_filters[key] = value # 1. Apply backend.configuration filtering. if configuration_filters: backends = [b for b in backends if _match_all(b.configuration(), configuration_filters)] # 2. Apply backend.status filtering (it involves one API call for # each backend). if status_filters: backends = [b for b in backends if _match_all(b.status(), status_filters)] # 3. Apply acceptor filter. backends = list(filter(filters, backends)) return backends
Resolve backend name from a deprecated name or an alias.
def resolve_backend_name(name, backends, deprecated, aliased): """Resolve backend name from a deprecated name or an alias. A group will be resolved in order of member priorities, depending on availability. Args: name (str): name of backend to resolve backends (list[BaseBackend]): list of available backends. deprecated (dict[str: str]): dict of deprecated names. aliased (dict[str: list[str]]): dict of aliased names. Returns: str: resolved name (name of an available backend) Raises: LookupError: if name cannot be resolved through regular available names, nor deprecated, nor alias names. """ available = [backend.name() for backend in backends] resolved_name = deprecated.get(name, aliased.get(name, name)) if isinstance(resolved_name, list): resolved_name = next((b for b in resolved_name if b in available), "") if resolved_name not in available: raise LookupError("backend '{}' not found.".format(name)) if name in deprecated: logger.warning("WARNING: '%s' is deprecated. Use '%s'.", name, resolved_name) return resolved_name
Build a QuantumCircuit object from a DAGCircuit.
def dag_to_circuit(dag): """Build a ``QuantumCircuit`` object from a ``DAGCircuit``. Args: dag (DAGCircuit): the input dag. Return: QuantumCircuit: the circuit representing the input dag. """ qregs = collections.OrderedDict() for qreg in dag.qregs.values(): qreg_tmp = QuantumRegister(qreg.size, name=qreg.name) qregs[qreg.name] = qreg_tmp cregs = collections.OrderedDict() for creg in dag.cregs.values(): creg_tmp = ClassicalRegister(creg.size, name=creg.name) cregs[creg.name] = creg_tmp name = dag.name or None circuit = QuantumCircuit(*qregs.values(), *cregs.values(), name=name) for node in dag.topological_op_nodes(): qubits = [] for qubit in node.qargs: qubits.append(qregs[qubit[0].name][qubit[1]]) clbits = [] for clbit in node.cargs: clbits.append(cregs[clbit[0].name][clbit[1]]) # Get arguments for classical control (if any) if node.condition is None: control = None else: control = (node.condition[0], node.condition[1]) inst = node.op.copy() inst.control = control circuit.append(inst, qubits, clbits) return circuit
Convert an observable in matrix form to dictionary form.
def make_dict_observable(matrix_observable): """Convert an observable in matrix form to dictionary form. Takes in a diagonal observable as a matrix and converts it to a dictionary form. Can also handle a list sorted of the diagonal elements. Args: matrix_observable (list): The observable to be converted to dictionary form. Can be a matrix or just an ordered list of observed values Returns: Dict: A dictionary with all observable states as keys, and corresponding values being the observed value for that state """ dict_observable = {} observable = np.array(matrix_observable) observable_size = len(observable) observable_bits = int(np.ceil(np.log2(observable_size))) binary_formater = '0{}b'.format(observable_bits) if observable.ndim == 2: observable = observable.diagonal() for state_no in range(observable_size): state_str = format(state_no, binary_formater) dict_observable[state_str] = observable[state_no] return dict_observable
Update a node in the symbol table.
def update_symtab(self, obj): """Update a node in the symbol table. Everything in the symtab must be a node with these attributes: name - the string name of the object type - the string type of the object line - the source line where the type was first found file - the source file where the type was first found """ if obj.name in self.current_symtab: prev = self.current_symtab[obj.name] raise QasmError("Duplicate declaration for", obj.type + " '" + obj.name + "' at line", str(obj.line) + ', file', obj.file + '.\nPrevious occurrence at line', str(prev.line) + ', file', prev.file) self.current_symtab[obj.name] = obj
Verify a qubit id against the gate prototype.
def verify_declared_bit(self, obj): """Verify a qubit id against the gate prototype.""" # We are verifying gate args against the formal parameters of a # gate prototype. if obj.name not in self.current_symtab: raise QasmError("Cannot find symbol '" + obj.name + "' in argument list for gate, line", str(obj.line), 'file', obj.file) # This insures the thing is from the bitlist and not from the # argument list. sym = self.current_symtab[obj.name] if not (sym.type == 'id' and sym.is_bit): raise QasmError("Bit", obj.name, 'is not declared as a bit in the gate.')
Verify each expression in a list.
def verify_exp_list(self, obj): """Verify each expression in a list.""" # A tad harder. This is a list of expressions each of which could be # the head of a tree. We need to recursively walk each of these and # ensure that any Id elements resolve to the current stack. # # I believe we only have to look at the current symtab. if obj.children is not None: for children in obj.children: if isinstance(children, node.Id): if children.name in self.external_functions: continue if children.name not in self.current_symtab: raise QasmError("Argument '" + children.name + "' in expression cannot be " + "found, line", str(children.line), "file", children.file) else: if hasattr(children, "children"): self.verify_exp_list(children)
Verify a user defined gate call.
def verify_as_gate(self, obj, bitlist, arglist=None): """Verify a user defined gate call.""" if obj.name not in self.global_symtab: raise QasmError("Cannot find gate definition for '" + obj.name + "', line", str(obj.line), 'file', obj.file) g_sym = self.global_symtab[obj.name] if not (g_sym.type == 'gate' or g_sym.type == 'opaque'): raise QasmError("'" + obj.name + "' is used as a gate " + "or opaque call but the symbol is neither;" + " it is a '" + g_sym.type + "' line", str(obj.line), 'file', obj.file) if g_sym.n_bits() != bitlist.size(): raise QasmError("Gate or opaque call to '" + obj.name + "' uses", str(bitlist.size()), "qubits but is declared for", str(g_sym.n_bits()), "qubits", "line", str(obj.line), 'file', obj.file) if arglist: if g_sym.n_args() != arglist.size(): raise QasmError("Gate or opaque call to '" + obj.name + "' uses", str(arglist.size()), "qubits but is declared for", str(g_sym.n_args()), "qubits", "line", str(obj.line), 'file', obj.file) else: if g_sym.n_args() > 0: raise QasmError("Gate or opaque call to '" + obj.name + "' has no arguments but is declared for", str(g_sym.n_args()), "qubits", "line", str(obj.line), 'file', obj.file)
Verify a register.
def verify_reg(self, obj, object_type): """Verify a register.""" # How to verify: # types must match # indexes must be checked if obj.name not in self.global_symtab: raise QasmError('Cannot find definition for', object_type, "'" + obj.name + "'", 'at line', str(obj.line), 'file', obj.file) g_sym = self.global_symtab[obj.name] if g_sym.type != object_type: raise QasmError("Type for '" + g_sym.name + "' should be '" + object_type + "' but was found to be '" + g_sym.type + "'", "line", str(obj.line), "file", obj.file) if obj.type == 'indexed_id': bound = g_sym.index ndx = obj.index if ndx < 0 or ndx >= bound: raise QasmError("Register index for '" + g_sym.name + "' out of bounds. Index is", str(ndx), "bound is 0 <= index <", str(bound), "at line", str(obj.line), "file", obj.file)
Verify a list of registers.
def verify_reg_list(self, obj, object_type): """Verify a list of registers.""" # We expect the object to be a bitlist or an idlist, we don't care. # We will iterate it and ensure everything in it is declared as a bit, # and throw if not. for children in obj.children: self.verify_reg(children, object_type)
Return a list of ( name index ) tuples for this id node.
def id_tuple_list(self, id_node): """Return a list of (name, index) tuples for this id node.""" if id_node.type != "id": raise QasmError("internal error, id_tuple_list") bit_list = [] try: g_sym = self.current_symtab[id_node.name] except KeyError: g_sym = self.global_symtab[id_node.name] if g_sym.type == "qreg" or g_sym.type == "creg": # Return list of (name, idx) for reg ids for idx in range(g_sym.index): bit_list.append((id_node.name, idx)) else: # Return (name, -1) for other ids bit_list.append((id_node.name, -1)) return bit_list
Check that objects in list_of_nodes represent distinct ( qu ) bits.
def verify_distinct(self, list_of_nodes): """Check that objects in list_of_nodes represent distinct (qu)bits. list_of_nodes is a list containing nodes of type id, indexed_id, primary_list, or id_list. We assume these are all the same type 'qreg' or 'creg'. This method raises an exception if list_of_nodes refers to the same object more than once. """ bit_list = [] line_number = -1 filename = "" for node_ in list_of_nodes: # id node: add all bits in register or (name, -1) for id if node_.type == "id": bit_list.extend(self.id_tuple_list(node_)) line_number = node_.line filename = node_.file # indexed_id: add the bit elif node_.type == "indexed_id": bit_list.append((node_.name, node_.index)) line_number = node_.line filename = node_.file # primary_list: for each id or indexed_id child, add elif node_.type == "primary_list": for child in node_.children: if child.type == "id": bit_list.extend(self.id_tuple_list(child)) else: bit_list.append((child.name, child.index)) line_number = child.line filename = child.file # id_list: for each id, add elif node_.type == "id_list": for child in node_.children: bit_list.extend(self.id_tuple_list(child)) line_number = child.line filename = child.file else: raise QasmError("internal error, verify_distinct") if len(bit_list) != len(set(bit_list)): raise QasmError("duplicate identifiers at line %d file %s" % (line_number, filename))
statement: decl | quantum_op ; | format ; | ignore | quantum_op error | format error
def p_statement(self, program): """ statement : decl | quantum_op ';' | format ';' | ignore | quantum_op error | format error """ if len(program) > 2: if program[2] != ';': raise QasmError("Missing ';' at end of statement; " + "received", str(program[2].value)) program[0] = program[1]
indexed_id: id [ NNINTEGER ] | id [ NNINTEGER error | id [ error
def p_indexed_id(self, program): """ indexed_id : id '[' NNINTEGER ']' | id '[' NNINTEGER error | id '[' error """ if len(program) == 4: raise QasmError("Expecting an integer index; received", str(program[3].value)) if program[4] != ']': raise QasmError("Missing ']' in indexed ID; received", str(program[4].value)) program[0] = node.IndexedId([program[1], node.Int(program[3])])
gate_id_list: id
def p_gate_id_list_0(self, program): """ gate_id_list : id """ program[0] = node.IdList([program[1]]) self.update_symtab(program[1])
gate_id_list: gate_id_list id
def p_gate_id_list_1(self, program): """ gate_id_list : gate_id_list ',' id """ program[0] = program[1] program[0].add_child(program[3]) self.update_symtab(program[3])
bit_list: id
def p_bit_list_0(self, program): """ bit_list : id """ program[0] = node.IdList([program[1]]) program[1].is_bit = True self.update_symtab(program[1])
bit_list: bit_list id
def p_bit_list_1(self, program): """ bit_list : bit_list ',' id """ program[0] = program[1] program[0].add_child(program[3]) program[3].is_bit = True self.update_symtab(program[3])
decl: qreg_decl ; | creg_decl ; | qreg_decl error | creg_decl error | gate_decl
def p_decl(self, program): """ decl : qreg_decl ';' | creg_decl ';' | qreg_decl error | creg_decl error | gate_decl """ if len(program) > 2: if program[2] != ';': raise QasmError("Missing ';' in qreg or creg declaration." " Instead received '" + program[2].value + "'") program[0] = program[1]
qreg_decl: QREG indexed_id
def p_qreg_decl(self, program): """ qreg_decl : QREG indexed_id """ program[0] = node.Qreg([program[2]]) if program[2].name in self.external_functions: raise QasmError("QREG names cannot be reserved words. " + "Received '" + program[2].name + "'") if program[2].index == 0: raise QasmError("QREG size must be positive") self.update_symtab(program[0])
creg_decl: CREG indexed_id
def p_creg_decl(self, program): """ creg_decl : CREG indexed_id """ program[0] = node.Creg([program[2]]) if program[2].name in self.external_functions: raise QasmError("CREG names cannot be reserved words. " + "Received '" + program[2].name + "'") if program[2].index == 0: raise QasmError("CREG size must be positive") self.update_symtab(program[0])
gate_decl: GATE id gate_scope ( ) bit_list gate_body
def p_gate_decl_1(self, program): """ gate_decl : GATE id gate_scope '(' ')' bit_list gate_body """ program[0] = node.Gate([program[2], program[6], program[7]]) if program[2].name in self.external_functions: raise QasmError("GATE names cannot be reserved words. " + "Received '" + program[2].name + "'") self.pop_scope() self.update_symtab(program[0])
gate_body: { }
def p_gate_body_0(self, program): """ gate_body : '{' '}' """ if program[2] != '}': raise QasmError("Missing '}' in gate definition; received'" + str(program[2].value) + "'") program[0] = node.GateBody(None)
unitary_op: U ( exp_list ) primary
def p_unitary_op_0(self, program): """ unitary_op : U '(' exp_list ')' primary """ program[0] = node.UniversalUnitary([program[3], program[5]]) self.verify_reg(program[5], 'qreg') self.verify_exp_list(program[3])
unitary_op: CX primary primary
def p_unitary_op_1(self, program): """ unitary_op : CX primary ',' primary """ program[0] = node.Cnot([program[2], program[4]]) self.verify_reg(program[2], 'qreg') self.verify_reg(program[4], 'qreg') self.verify_distinct([program[2], program[4]])
unitary_op: id primary_list
def p_unitary_op_2(self, program): """ unitary_op : id primary_list """ program[0] = node.CustomUnitary([program[1], program[2]]) self.verify_as_gate(program[1], program[2]) self.verify_reg_list(program[2], 'qreg') self.verify_distinct([program[2]])
unitary_op: id ( ) primary_list
def p_unitary_op_3(self, program): """ unitary_op : id '(' ')' primary_list """ program[0] = node.CustomUnitary([program[1], program[4]]) self.verify_as_gate(program[1], program[4]) self.verify_reg_list(program[4], 'qreg') self.verify_distinct([program[4]])
unitary_op: id ( exp_list ) primary_list
def p_unitary_op_4(self, program): """ unitary_op : id '(' exp_list ')' primary_list """ program[0] = node.CustomUnitary([program[1], program[3], program[5]]) self.verify_as_gate(program[1], program[5], arglist=program[3]) self.verify_reg_list(program[5], 'qreg') self.verify_exp_list(program[3]) self.verify_distinct([program[5]])
gate_op: U ( exp_list ) id ;
def p_gate_op_0(self, program): """ gate_op : U '(' exp_list ')' id ';' """ program[0] = node.UniversalUnitary([program[3], program[5]]) self.verify_declared_bit(program[5]) self.verify_exp_list(program[3])
gate_op: CX id id ;
def p_gate_op_1(self, program): """ gate_op : CX id ',' id ';' """ program[0] = node.Cnot([program[2], program[4]]) self.verify_declared_bit(program[2]) self.verify_declared_bit(program[4]) self.verify_distinct([program[2], program[4]])
gate_op: id id_list ;
def p_gate_op_2(self, program): """ gate_op : id id_list ';' """ program[0] = node.CustomUnitary([program[1], program[2]]) # To verify: # 1. id is declared as a gate in global scope # 2. everything in the id_list is declared as a bit in local scope self.verify_as_gate(program[1], program[2]) self.verify_bit_list(program[2]) self.verify_distinct([program[2]])
gate_op: id ( ) id_list ;
def p_gate_op_3(self, program): """ gate_op : id '(' ')' id_list ';' """ program[0] = node.CustomUnitary([program[1], program[4]]) self.verify_as_gate(program[1], program[4]) self.verify_bit_list(program[4]) self.verify_distinct([program[4]])
gate_op: id ( exp_list ) id_list ;
def p_gate_op_4(self, program): """ gate_op : id '(' exp_list ')' id_list ';' """ program[0] = node.CustomUnitary([program[1], program[3], program[5]]) self.verify_as_gate(program[1], program[5], arglist=program[3]) self.verify_bit_list(program[5]) self.verify_exp_list(program[3]) self.verify_distinct([program[5]])
gate_op: BARRIER id_list ;
def p_gate_op_5(self, program): """ gate_op : BARRIER id_list ';' """ program[0] = node.Barrier([program[2]]) self.verify_bit_list(program[2]) self.verify_distinct([program[2]])
opaque: OPAQUE id gate_scope bit_list
def p_opaque_0(self, program): """ opaque : OPAQUE id gate_scope bit_list """ # TODO: Review Opaque function program[0] = node.Opaque([program[2], program[4]]) if program[2].name in self.external_functions: raise QasmError("OPAQUE names cannot be reserved words. " + "Received '" + program[2].name + "'") self.pop_scope() self.update_symtab(program[0])
opaque: OPAQUE id gate_scope ( ) bit_list
def p_opaque_1(self, program): """ opaque : OPAQUE id gate_scope '(' ')' bit_list """ program[0] = node.Opaque([program[2], program[6]]) self.pop_scope() self.update_symtab(program[0])
measure: MEASURE primary ASSIGN primary
def p_measure(self, program): """ measure : MEASURE primary ASSIGN primary """ program[0] = node.Measure([program[2], program[4]]) self.verify_reg(program[2], 'qreg') self.verify_reg(program[4], 'creg')
barrier: BARRIER primary_list
def p_barrier(self, program): """ barrier : BARRIER primary_list """ program[0] = node.Barrier([program[2]]) self.verify_reg_list(program[2], 'qreg') self.verify_distinct([program[2]])
reset: RESET primary
def p_reset(self, program): """ reset : RESET primary """ program[0] = node.Reset([program[2]]) self.verify_reg(program[2], 'qreg')
if: IF ( id MATCHES NNINTEGER ) quantum_op if: IF ( id error if: IF ( id MATCHES error if: IF ( id MATCHES NNINTEGER error if: IF error
def p_if(self, program): """ if : IF '(' id MATCHES NNINTEGER ')' quantum_op if : IF '(' id error if : IF '(' id MATCHES error if : IF '(' id MATCHES NNINTEGER error if : IF error """ if len(program) == 3: raise QasmError("Ill-formed IF statement. Perhaps a" + " missing '('?") if len(program) == 5: raise QasmError("Ill-formed IF statement. Expected '==', " + "received '" + str(program[4].value)) if len(program) == 6: raise QasmError("Ill-formed IF statement. Expected a number, " + "received '" + str(program[5].value)) if len(program) == 7: raise QasmError("Ill-formed IF statement, unmatched '('") if program[7].type == 'if': raise QasmError("Nested IF statements not allowed") if program[7].type == 'barrier': raise QasmError("barrier not permitted in IF statement") program[0] = node.If([program[3], node.Int(program[5]), program[7]])
unary: id ( expression )
def p_unary_6(self, program): """ unary : id '(' expression ')' """ # note this is a semantic check, not syntactic if program[1].name not in self.external_functions: raise QasmError("Illegal external function call: ", str(program[1].name)) program[0] = node.External([program[1], program[3]])
expression: - expression %prec negative | + expression %prec positive
def p_expression_1(self, program): """ expression : '-' expression %prec negative | '+' expression %prec positive """ program[0] = node.Prefix([node.UnaryOperator(program[1]), program[2]])
expression: expression * expression | expression/ expression | expression + expression | expression - expression | expression ^ expression
def p_expression_0(self, program): """ expression : expression '*' expression | expression '/' expression | expression '+' expression | expression '-' expression | expression '^' expression """ program[0] = node.BinaryOp([node.BinaryOperator(program[2]), program[1], program[3]])
Compute the column.
def find_column(self, input_, token): """Compute the column. Input is the input text string. token is a token instance. """ if token is None: return 0 last_cr = input_.rfind('\n', 0, token.lexpos) if last_cr < 0: last_cr = 0 column = (token.lexpos - last_cr) + 1 return column
Returns a generator of the tokens.
def get_tokens(self): """Returns a generator of the tokens.""" try: while True: token = self.lexer.token() if not token: break yield token except QasmError as e: print('Exception tokenizing qasm file:', e.msg)
Set the parse_deb field.
def parse_debug(self, val): """Set the parse_deb field.""" if val is True: self.parse_deb = True elif val is False: self.parse_deb = False else: raise QasmError("Illegal debug value '" + str(val) + "' must be True or False.")
Parse some data.
def parse(self, data): """Parse some data.""" self.parser.parse(data, lexer=self.lexer, debug=self.parse_deb) if self.qasm is None: raise QasmError("Uncaught exception in parser; " + "see previous messages for details.") return self.qasm
Parser runner.
def run(self, data): """Parser runner. To use this module stand-alone. """ ast = self.parser.parse(data, debug=True) self.parser.parse(data, debug=True) ast.to_string(0)
Returns a generator of the tokens.
def get_tokens(self): """Returns a generator of the tokens.""" if self._filename: with open(self._filename) as ifile: self._data = ifile.read() with QasmParser(self._filename) as qasm_p: return qasm_p.get_tokens()
Parse the data.
def parse(self): """Parse the data.""" if self._filename: with open(self._filename) as ifile: self._data = ifile.read() with QasmParser(self._filename) as qasm_p: qasm_p.parse_debug(False) return qasm_p.parse(self._data)
Apply crz from ctl to tgt with angle theta.
def crz(self, theta, ctl, tgt): """Apply crz from ctl to tgt with angle theta.""" return self.append(CrzGate(theta), [ctl, tgt], [])
Return a basis state ndarray.
def basis_state(str_state, num): """ Return a basis state ndarray. Args: str_state (string): a string representing the state. num (int): the number of qubits Returns: ndarray: state(2**num) a quantum state with basis basis state. Raises: QiskitError: if the dimensions is wrong """ n = int(str_state, 2) if num >= len(str_state): state = np.zeros(1 << num, dtype=complex) state[n] = 1 return state else: raise QiskitError('size of bitstring is greater than num.')
maps a pure state to a state matrix
def projector(state, flatten=False): """ maps a pure state to a state matrix Args: state (ndarray): the number of qubits flatten (bool): determine if state matrix of column work Returns: ndarray: state_mat(2**num, 2**num) if flatten is false ndarray: state_mat(4**num) if flatten is true stacked on by the column """ density_matrix = np.outer(state.conjugate(), state) if flatten: return density_matrix.flatten(order='F') return density_matrix