def test_tensor_product_dm(self):
num_qubit = 4
dm1 = qulacs.DensityMatrix(num_qubit)
dm2 = qulacs.DensityMatrix(num_qubit)
dm1.set_Haar_random_state(seed=0)
dm2.set_Haar_random_state(seed=1)
dm3 = qulacs.state.tensor_product(dm1, dm2)
dm3_test = np.kron(dm1.get_matrix(), dm2.get_matrix())
self.assertTrue(np.allclose(dm3_test, dm3.get_matrix()), msg="check density matrix tensor product")
del dm1
del dm2
del dm3
def test_permutate_qubit_dm(self):
num_qubit = 3
dm = qulacs.DensityMatrix(num_qubit)
dm.set_Haar_random_state(seed=0)
order = np.arange(num_qubit)
np.random.shuffle(order)
arr = []
for ind in range(2**num_qubit):
s = format(ind, "0{}b".format(num_qubit))
s = np.array(list(s[::-1]))
v = np.array(["*"] * num_qubit)
for ind in range(len(s)):
v[order[ind]] = s[ind]
s = ("".join(v))[::-1]
arr.append(int(s, 2))
dm_perm = qulacs.state.permutate_qubit(dm, order)
dm_perm_test = dm.get_matrix()
dm_perm_test = dm_perm_test[arr, :]
dm_perm_test = dm_perm_test[:, arr]
self.assertTrue(np.allclose(dm_perm_test, dm_perm.get_matrix()),
msg="check density matrix permutation")
del dm_perm
del dm
def _base_iterator(self,
circuit: circuits.Circuit,
qubit_order: ops.QubitOrderOrList,
initial_state: Union[int, np.ndarray],
perform_measurements: bool = True) -> Iterator:
qubits = ops.QubitOrder.as_qubit_order(qubit_order).order_for(
circuit.all_qubits())
num_qubits = len(qubits)
qubit_map = {q: i for i, q in enumerate(qubits)}
matrix = to_valid_density_matrix(initial_state,
num_qubits,
dtype=self._dtype)
if len(circuit) == 0:
yield DensityMatrixStepResult(matrix, {},
qubit_map,
dtype=self._dtype)
matrix = np.reshape(matrix, (2**num_qubits, 2**num_qubits))
noisy_moments = self.noise.noisy_moments(circuit,
sorted(circuit.all_qubits()))
state = qulacs.DensityMatrix(num_qubits)
state.load(matrix)
for moment in noisy_moments:
measurements = collections.defaultdict(
list) # type: Dict[str, List[bool]]
operations = moment.operations
for op in operations:
indices = [
num_qubits - 1 - qubit_map[qubit] for qubit in op.qubits
]
indices.reverse()
if isinstance(op, ops.MeasurementGate):
# Not implemented
raise NotImplementedError(
"Measurement is not supported in qulacs simulator")
else:
gate = cast(ops.GateOperation, op).gate
channel = protocols.channel(gate)
qulacs_gates = []
for krauss in channel:
krauss = krauss.astype(np.complex128)
qulacs_gate = qulacs.gate.DenseMatrix(indices, krauss)
qulacs_gates.append(qulacs_gate)
qulacs_cptp_map = qulacs.gate.CPTP(qulacs_gates)
qulacs_cptp_map.update_quantum_state(state)
matrix = state.get_matrix()
matrix = np.reshape(matrix, (2, ) * num_qubits * 2)
yield DensityMatrixStepResult(density_matrix=matrix,
measurements=measurements,
qubit_map=qubit_map,
dtype=self._dtype)
def test_density_matrix(self):
num_qubit = 5
sv = qulacs.StateVector(num_qubit)
dm = qulacs.DensityMatrix(num_qubit)
sv.set_Haar_random_state(seed=0)
dm.load(sv)
svv = np.atleast_2d(sv.get_vector()).T
mat = np.dot(svv, svv.T.conj())
self.assertTrue(np.allclose(dm.get_matrix(), mat), msg="check pure matrix to density matrix")
def test_partial_trace_dm(self):
num_qubit = 5
num_traceout = 2
dm = qulacs.DensityMatrix(num_qubit)
dm.set_Haar_random_state(seed=0)
mat = dm.get_matrix()
target = np.arange(num_qubit)
np.random.shuffle(target)
target = target[:num_traceout]
target_cor = [num_qubit-1-i for i in target]
target_cor.sort()
dmt = mat.reshape([2,2]*num_qubit)
for cnt,val in enumerate(target_cor):
ofs = num_qubit - cnt
dmt = np.trace(dmt, axis1=val-cnt, axis2=ofs+val-cnt)
dmt = dmt.reshape([2**(num_qubit-num_traceout),2**(num_qubit-num_traceout)])
pdm = qulacs.state.partial_trace(dm, target)
self.assertTrue(np.allclose(pdm.get_matrix(), dmt), msg="check density matrix partial trace")
del dm,pdm
def _base_iterator(self,
circuit: circuits.Circuit,
qubit_order: ops.QubitOrderOrList,
initial_state: Union[int, np.ndarray],
perform_measurements: bool = True) -> Iterator:
qubits = ops.QubitOrder.as_qubit_order(qubit_order).order_for(
circuit.all_qubits())
num_qubits = len(qubits)
qubit_map = {q: i for i, q in enumerate(qubits)}
matrix = density_matrix_utils.to_valid_density_matrix(
initial_state, num_qubits, self._dtype)
if len(circuit) == 0:
yield DensityMatrixStepResult(matrix, {}, qubit_map, self._dtype)
def on_stuck(bad_op: ops.Operation):
return TypeError(
"Can't simulate operations that don't implement "
"SupportsUnitary, SupportsApplyUnitary, SupportsMixture, "
"SupportsChannel or is a measurement: {!r}".format(bad_op))
def keep(potential_op: ops.Operation) -> bool:
return (protocols.has_channel(potential_op)
or (ops.op_gate_of_type(potential_op, ops.MeasurementGate)
is not None)
or isinstance(potential_op,
(ops.SamplesDisplay, ops.WaveFunctionDisplay,
ops.DensityMatrixDisplay)))
matrix = np.reshape(matrix, (2**num_qubits, 2**num_qubits))
noisy_moments = self.noise.noisy_moments(circuit,
sorted(circuit.all_qubits()))
state = qulacs.DensityMatrix(num_qubits)
state.load(matrix)
for moment in noisy_moments:
measurements = collections.defaultdict(
list) # type: Dict[str, List[bool]]
channel_ops_and_measurements = protocols.decompose(
moment, keep=keep, on_stuck_raise=on_stuck)
for op in channel_ops_and_measurements:
#indices = [qubit_map[qubit] for qubit in op.qubits]
indices = [
num_qubits - 1 - qubit_map[qubit] for qubit in op.qubits
]
indices.reverse()
if isinstance(op, (ops.SamplesDisplay, ops.WaveFunctionDisplay,
ops.DensityMatrixDisplay)):
continue
# TODO: support more general measurements.
meas = ops.op_gate_of_type(op, ops.MeasurementGate)
if meas:
# Not implemented
raise NotImplementedError(
"Measurement is not supported in qulacs simulator")
else:
# TODO: Use apply_channel similar to apply_unitary.
gate = cast(ops.GateOperation, op).gate
channel = protocols.channel(gate)
qulacs_gates = []
for krauss in channel:
krauss = krauss.astype(np.complex128)
qulacs_gate = qulacs.gate.DenseMatrix(indices, krauss)
qulacs_gates.append(qulacs_gate)
qulacs_cptp_map = qulacs.gate.CPTP(qulacs_gates)
qulacs_cptp_map.update_quantum_state(state)
matrix = state.get_matrix()
matrix = np.reshape(matrix, (2, ) * num_qubits * 2)
yield DensityMatrixStepResult(density_matrix=matrix,
measurements=measurements,
qubit_map=qubit_map,
dtype=self._dtype)
