def run(self,
circuit: Circuit,
shots: int,
fit_to_constraints=True,
seed: int = None) -> np.ndarray:
"""Run a circuit on Qiskit Aer Qasm simulator.
:param circuit: The circuit to run
:type circuit: Circuit
:param shots: Number of shots (repeats) to run
:type shots: int
:param fit_to_constraints: Compile the circuit to meet the constraints of the backend, defaults to True
:type fit_to_constraints: bool, optional
:param seed: random seed to for simulator
:type seed: int
:return: Table of shot results, each row is a shot, columns are ordered by qubit ordering. Values are 0 or 1, corresponding to qubit basis states.
:rtype: numpy.ndarray
"""
c = circuit.copy()
if fit_to_constraints:
Transform.RebaseToQiskit().apply(c)
dag = tk_to_dagcircuit(c)
qc = dag_to_circuit(dag)
qobj = assemble(qc, shots=shots, seed_simulator=seed, memory=True)
job = self._backend.run(qobj, noise_model=self.noise_model)
shot_list = job.result().get_memory(qc)
return np.asarray([_convert_bin_str(shot) for shot in shot_list])
def _routed_ibmq_circuit(circuit: Circuit,
arc: Architecture) -> QuantumCircuit:
c = circuit.copy()
Transform.RebaseToQiskit().apply(c)
physical_c = route(c, arc)
physical_c.decompose_SWAP_to_CX()
physical_c.redirect_CX_gates(arc)
Transform.OptimisePostRouting().apply(physical_c)
qc = tk_to_qiskit(physical_c)
return qc
def get_state(self, circuit, fit_to_constraints=True) :
"""
Calculate the statevector for a circuit.
:param circuit: circuit to calculate
:return: complex numpy array of statevector
"""
c = circuit.copy()
if fit_to_constraints :
Transform.RebaseToQiskit().apply(c)
qc = tk_to_qiskit(c)
qobj = assemble(qc)
job = self._backend.run(qobj)
return np.asarray(job.result().get_statevector(qc, decimals=16))
def get_unitary(self, circuit, fit_to_constraints=True) :
"""
Obtains the unitary for a given quantum circuit
:param circuit: The circuit to inspect
:type circuit: Circuit
:param fit_to_constraints: Forces the circuit to be decomposed into the correct gate set, defaults to True
:type fit_to_constraints: bool, optional
:return: The unitary of the circuit. Qubits are ordered with qubit 0 as the least significant qubit
"""
c = circuit.copy()
if fit_to_constraints :
Transform.RebaseToQiskit().apply(c)
qc = tk_to_qiskit(c)
qobj = assemble(qc)
job = self._backend.run(qobj)
return job.result().get_unitary(qc)
def get_counts(self, circuit, shots, fit_to_constraints=True, seed=None) :
"""
Run the circuit on the backend and accumulate the results into a summary of counts
:param circuit: The circuit to run
:param shots: Number of shots (repeats) to run
:param fit_to_constraints: Compile the circuit to meet the constraints of the backend, defaults to True
:param seed: Random seed to for simulator
:return: Dictionary mapping bitvectors of results to number of times that result was observed (zero counts are omitted)
"""
c = circuit.copy()
if fit_to_constraints :
Transform.RebaseToQiskit().apply(c)
qc = tk_to_qiskit(c)
qobj = assemble(qc, shots=shots, seed_simulator=seed)
job = self._backend.run(qobj, noise_model=self.noise_model)
counts = job.result().get_counts(qc)
return {tuple(_convert_bin_str(b)) : c for b, c in counts.items()}