def construct_circuit(self, parameters, q=None):
""" construct circuit """
if not len(parameters) == self.num_parameters:
raise ValueError(
'Incorrect number of angles: expecting {}, but {} given.'.
format(self.num_parameters, len(parameters)))
# initialize circuit, possibly based on given register/initial state
if isinstance(self._initial_state, QuantumCircuit):
circuit_op = CircuitStateFn(self._initial_state)
elif self._initial_state is not None:
circuit_op = CircuitStateFn(
self._initial_state.construct_circuit('circuit'))
else:
circuit_op = (H ^ self._num_qubits)
# iterate over layers
for idx in range(self._p):
# the first [:self._p] parameters are used for the cost operator,
# so we apply them here
circuit_op = (self._cost_operator *
parameters[idx]).exp_i().compose(circuit_op)
if isinstance(self._mixer, OperatorBase):
mixer = cast(OperatorBase, self._mixer)
# we apply beta parameter in case of operator based mixer.
circuit_op = (
mixer *
parameters[idx + self._p]).exp_i().compose(circuit_op)
else:
# mixer as a quantum circuit that can be parameterized
mixer = cast(QuantumCircuit, self._mixer)
num_params = mixer.num_parameters
# the remaining [self._p:] parameters are used for the mixer,
# there may be multiple layers, so parameters are grouped by layers.
param_values = parameters[self._p + num_params * idx:self._p +
num_params * (idx + 1)]
param_dict = dict(zip(mixer.parameters, param_values))
mixer = mixer.assign_parameters(param_dict)
circuit_op = CircuitOp(mixer).compose(circuit_op)
evolution = EvolutionFactory.build(self._cost_operator)
circuit_op = evolution.convert(circuit_op)
return circuit_op.to_circuit()
def _construct_circuit(self, parameters) -> QuantumCircuit:
"""Construct a parameterized circuit."""
if not len(parameters) == self._num_parameters:
raise ValueError(
'Incorrect number of angles: expecting {}, but {} given.'.
format(self._num_parameters, len(parameters)))
# local imports to avoid circular imports
from qiskit.opflow import CircuitStateFn
from qiskit.opflow import CircuitOp, EvolutionFactory
from qiskit.opflow import OperatorBase
circuit_op = CircuitStateFn(self.initial_state)
# iterate over layers
for idx in range(self._reps):
# the first [:self._reps] parameters are used for the cost operator,
# so we apply them here
circuit_op = (self._cost_operator *
parameters[idx]).exp_i().compose(circuit_op)
mixer = self.mixer_operator
if isinstance(mixer, OperatorBase):
mixer = cast(OperatorBase, mixer)
# we apply beta parameter in case of operator based mixer.
circuit_op = (
mixer *
parameters[idx + self._reps]).exp_i().compose(circuit_op)
else:
# mixer as a quantum circuit that can be parameterized
mixer = cast(QuantumCircuit, mixer)
num_params = mixer.num_parameters
# the remaining [self._p:] parameters are used for the mixer,
# there may be multiple layers, so parameters are grouped by layers.
param_values = parameters[self._reps +
num_params * idx:self._reps +
num_params * (idx + 1)]
param_dict = dict(zip(mixer.parameters, param_values))
mixer = mixer.assign_parameters(param_dict)
circuit_op = CircuitOp(mixer).compose(circuit_op)
evolution = EvolutionFactory.build(self._cost_operator)
circuit_op = evolution.convert(circuit_op)
return circuit_op.to_circuit()