def _create_partial_act_on_args(
self,
initial_state: Union[np.ndarray, 'cirq.STATE_VECTOR_LIKE',
'cirq.ActOnDensityMatrixArgs'],
qubits: Sequence['cirq.Qid'],
classical_data: 'cirq.ClassicalDataStore',
) -> 'cirq.ActOnDensityMatrixArgs':
"""Creates the ActOnDensityMatrixArgs for a circuit.
Args:
initial_state: The initial state for the simulation in the
computational basis.
qubits: Determines the canonical ordering of the qubits. This
is often used in specifying the initial state, i.e. the
ordering of the computational basis states.
classical_data: The shared classical data container for this
simulation.
Returns:
ActOnDensityMatrixArgs for the circuit.
"""
if isinstance(initial_state,
act_on_density_matrix_args.ActOnDensityMatrixArgs):
return initial_state
if self._ignore_measurement_results:
return act_on_density_matrix_args.ActOnDensityMatrixArgs(
qubits=qubits,
prng=self._prng,
classical_data=classical_data,
ignore_measurement_results=self._ignore_measurement_results,
initial_state=initial_state,
dtype=self._dtype,
)
return act_on_density_matrix_args.ActOnDensityMatrixArgs(
qubits=qubits,
prng=self._prng,
classical_data=classical_data,
initial_state=initial_state,
dtype=self._dtype,
)
def _create_partial_act_on_args(
self,
initial_state: Union[np.ndarray, 'cirq.STATE_VECTOR_LIKE',
'cirq.ActOnDensityMatrixArgs'],
qubits: Sequence['cirq.Qid'],
logs: Dict[str, Any],
) -> 'cirq.ActOnDensityMatrixArgs':
"""Creates the ActOnDensityMatrixArgs for a circuit.
Args:
initial_state: The initial state for the simulation in the
computational basis.
qubits: Determines the canonical ordering of the qubits. This
is often used in specifying the initial state, i.e. the
ordering of the computational basis states.
logs: The log of measurement results that is added into.
Returns:
ActOnDensityMatrixArgs for the circuit.
"""
if isinstance(initial_state,
act_on_density_matrix_args.ActOnDensityMatrixArgs):
return initial_state
qid_shape = protocols.qid_shape(qubits)
initial_matrix = qis.to_valid_density_matrix(initial_state,
len(qid_shape),
qid_shape=qid_shape,
dtype=self._dtype)
if np.may_share_memory(initial_matrix, initial_state):
initial_matrix = initial_matrix.copy()
tensor = initial_matrix.reshape(qid_shape * 2)
return act_on_density_matrix_args.ActOnDensityMatrixArgs(
target_tensor=tensor,
available_buffer=[np.empty_like(tensor) for _ in range(3)],
qubits=qubits,
qid_shape=qid_shape,
prng=self._prng,
log_of_measurement_results=logs,
)
def _base_iterator(
self,
circuit: circuits.Circuit,
qubit_order: ops.QubitOrderOrList,
initial_state: Union[np.ndarray, 'cirq.STATE_VECTOR_LIKE'],
all_measurements_are_terminal=False,
is_raw_state=False,
) -> Iterator['DensityMatrixStepResult']:
qubits = ops.QubitOrder.as_qubit_order(qubit_order).order_for(
circuit.all_qubits())
qid_shape = protocols.qid_shape(qubits)
qubit_map = {q: i for i, q in enumerate(qubits)}
initial_matrix = (qis.to_valid_density_matrix(initial_state,
len(qid_shape),
qid_shape=qid_shape,
dtype=self._dtype)
if not is_raw_state else initial_state)
if np.may_share_memory(initial_matrix, initial_state):
initial_matrix = initial_matrix.copy()
if len(circuit) == 0:
yield DensityMatrixStepResult(initial_matrix, {}, qubit_map,
self._dtype)
return
tensor = initial_matrix.reshape(qid_shape * 2)
sim_state = act_on_density_matrix_args.ActOnDensityMatrixArgs(
target_tensor=tensor,
available_buffer=[np.empty_like(tensor) for _ in range(3)],
axes=[],
qid_shape=qid_shape,
prng=self._prng,
log_of_measurement_results={},
)
noisy_moments = self.noise.noisy_moments(circuit,
sorted(circuit.all_qubits()))
measured = collections.defaultdict(
bool) # type: Dict[Tuple[cirq.Qid, ...], bool]
for moment in noisy_moments:
for op in flatten_to_ops(moment):
# TODO: support more general measurements.
# Github issue: https://github.com/quantumlib/Cirq/issues/3566
if all_measurements_are_terminal and measured[op.qubits]:
continue
if protocols.is_measurement(op):
measured[op.qubits] = True
if all_measurements_are_terminal:
continue
if self._ignore_measurement_results:
op = ops.phase_damp(1).on(*op.qubits)
sim_state.axes = tuple(qubit_map[qubit] for qubit in op.qubits)
protocols.act_on(op, sim_state)
yield DensityMatrixStepResult(
density_matrix=sim_state.target_tensor,
measurements=dict(sim_state.log_of_measurement_results),
qubit_map=qubit_map,
dtype=self._dtype,
)
sim_state.log_of_measurement_results.clear()