def test_integration(self, C):
"""Test expected serialization for a random circuit"""
with qml.tape.QuantumTape() as tape:
qml.RX(0.4, wires=0)
qml.RY(0.6, wires=1).inv().inv()
qml.CNOT(wires=[0, 1])
qml.QubitUnitary(np.eye(4), wires=[0, 1])
qml.templates.QFT(wires=[0, 1, 2]).inv()
qml.DoubleExcitation(0.555, wires=[3, 2, 1, 0])
qml.DoubleExcitationMinus(0.555, wires=[0, 1, 2, 3])
qml.DoubleExcitationPlus(0.555, wires=[0, 1, 2, 3])
s = _serialize_ops(tape, self.wires_dict)
dtype = np.complex64 if C else np.complex128
s_expected = (
(
[
"RX",
"RY",
"CNOT",
"QubitUnitary",
"QFT",
"DoubleExcitation",
"DoubleExcitationMinus",
"DoubleExcitationPlus",
],
[[0.4], [0.6], [], [], [], [0.555], [0.555], [0.555]],
[[0], [1], [0, 1], [0, 1], [0, 1, 2], [3, 2, 1, 0], [0, 1, 2, 3], [0, 1, 2, 3]],
[False, False, False, False, False, False, False, False],
[
[],
[],
[],
qml.matrix(qml.QubitUnitary(np.eye(4, dtype=dtype), wires=[0, 1])),
qml.matrix(qml.templates.QFT(wires=[0, 1, 2]).inv()),
[],
[],
[],
],
),
False,
)
assert s[0][0] == s_expected[0][0]
assert s[0][1] == s_expected[0][1]
assert s[0][2] == s_expected[0][2]
assert s[0][3] == s_expected[0][3]
assert s[1] == s_expected[1]
assert all(np.allclose(s1, s2) for s1, s2 in zip(s[0][4], s_expected[0][4]))
def _serialize_ops(
tape: QuantumTape, wires_map: dict
) -> Tuple[List[List[str]], List[np.ndarray], List[List[int]], List[bool], List[np.ndarray]]:
"""Serializes the operations of an input tape.
The state preparation operations are not included.
Args:
tape (QuantumTape): the input quantum tape
wires_map (dict): a dictionary mapping input wires to the device's backend wires
Returns:
Tuple[list, list, list, list, list]: A serialization of the operations, containing a list
of operation names, a list of operation parameters, a list of observable wires, a list of
inverses, and a list of matrices for the operations that do not have a dedicated kernel.
"""
names = []
params = []
wires = []
inverses = []
mats = []
uses_stateprep = False
for o in tape.operations:
if isinstance(o, (BasisState, QubitStateVector)):
uses_stateprep = True
continue
elif isinstance(o, Rot):
op_list = o.expand().operations
else:
op_list = [o]
for single_op in op_list:
is_inverse = single_op.inverse
name = single_op.name if not is_inverse else single_op.name[:-4]
names.append(name)
if not hasattr(StateVectorC128, name):
params.append([])
mats.append(qml.matrix(single_op))
if is_inverse:
is_inverse = False
else:
params.append(single_op.parameters)
mats.append([])
wires_list = single_op.wires.tolist()
wires.append([wires_map[w] for w in wires_list])
inverses.append(is_inverse)
return (names, params, wires, inverses, mats), uses_stateprep
def apply_lightning(self, state, operations):
"""Apply a list of operations to the state tensor.
Args:
state (array[complex]): the input state tensor
operations (list[~pennylane.operation.Operation]): operations to apply
dtype (type): Type of numpy ``complex`` to be used. Can be important
to specify for large systems for memory allocation purposes.
Returns:
array[complex]: the output state tensor
"""
state_vector = np.ravel(state)
if self.use_csingle:
# use_csingle
sim = StateVectorC64(state_vector)
else:
# self.C_DTYPE is np.complex128 by default
sim = StateVectorC128(state_vector)
# Skip over identity operations instead of performing
# matrix multiplication with the identity.
skipped_ops = ["Identity"]
for o in operations:
if o.base_name in skipped_ops:
continue
name = o.name.split(".")[
0] # The split is because inverse gates have .inv appended
method = getattr(sim, name, None)
wires = self.wires.indices(o.wires)
if method is None:
# Inverse can be set to False since qml.matrix(o) is already in inverted form
method = getattr(sim, "applyMatrix")
try:
method(qml.matrix(o), wires, False)
except AttributeError: # pragma: no cover
# To support older versions of PL
method(o.matrix, wires, False)
else:
inv = o.inverse
param = o.parameters
method(wires, inv, param)
return np.reshape(state_vector, state.shape)
def _assert_decomposition(pl_op, params=None):
num_wires = pl_op.num_wires
dimension = 2**num_wires
num_indices = 2 * num_wires
wires = list(range(num_wires))
contraction_parameters = [
np.reshape(np.eye(dimension), [2] * num_indices),
list(range(num_indices)),
]
index_substitutions = {i: i + num_wires for i in range(num_wires)}
next_index = num_indices
# get decomposed gates
decomposed_op = (pl_op.compute_decomposition(*params, wires=wires)
if params else pl_op.compute_decomposition(wires=wires))
# Heterogeneous matrix chain multiplication using tensor contraction
for gate in reversed(decomposed_op):
gate_wires = gate.wires.tolist()
# Upper indices, which will be traced out
contravariant = [index_substitutions[i] for i in gate_wires]
# Lower indices, which will replace the contracted indices in the matrix
covariant = list(range(next_index, next_index + len(gate_wires)))
indices = contravariant + covariant
# `qml.matrix(gate)` as type-(len(contravariant), len(covariant)) tensor
gate_tensor = np.reshape(qml.matrix(gate), [2] * len(indices))
contraction_parameters += [gate_tensor, indices]
next_index += len(gate_wires)
index_substitutions.update(
{gate_wires[i]: covariant[i]
for i in range(len(gate_wires))})
# Ensure matrix is in the correct order
new_indices = wires + [index_substitutions[i] for i in range(num_wires)]
contraction_parameters.append(new_indices)
actual_matrix = np.reshape(np.einsum(*contraction_parameters),
[dimension, dimension])
pl_op_matrix = pl_op.compute_matrix(
*params) if params else pl_op.compute_matrix()
assert np.allclose(actual_matrix, pl_op_matrix)
def _serialize_named_hermitian_ob(o, wires_map: dict, use_csingle: bool):
"""Serializes an observable (Named or Hermitian)"""
assert not isinstance(o, Tensor)
if use_csingle:
ctype = np.complex64
named_obs = NamedObsC64
hermitian_obs = HermitianObsC64
else:
ctype = np.complex128
named_obs = NamedObsC128
hermitian_obs = HermitianObsC128
wires_list = o.wires.tolist()
wires = [wires_map[w] for w in wires_list]
if _obs_has_kernel(o):
return named_obs(o.name, wires)
return hermitian_obs(qml.matrix(o).ravel().astype(ctype), wires)
def test_gate_unitary_correct(op, op_name):
"""Test if lightning.qubit correctly applies gates by reconstructing the unitary matrix and
comparing to the expected version"""
if op_name in ("BasisState", "QubitStateVector"):
pytest.skip("Skipping operation because it is a state preparation")
if op_name in (
"ControlledQubitUnitary",
"QubitUnitary",
"MultiControlledX",
"DiagonalQubitUnitary",
):
pytest.skip("Skipping operation.") # These are tested in the device test-suite
if op == None:
pytest.skip("Skipping operation.")
wires = op.num_wires
if wires == -1: # This occurs for operations that do not have a predefined number of wires
wires = 4
dev = qml.device("lightning.qubit", wires=wires)
num_params = op.num_params
p = [0.1] * num_params
op = getattr(qml, op_name)
@qml.qnode(dev)
def output(input):
qml.BasisState(input, wires=range(wires))
op(*p, wires=range(wires))
return qml.state()
unitary = np.zeros((2**wires, 2**wires), dtype=np.complex128)
for i, input in enumerate(itertools.product([0, 1], repeat=wires)):
out = output(np.array(input))
unitary[:, i] = out
unitary_expected = qml.matrix(op(*p, wires=range(wires)))
assert np.allclose(unitary, unitary_expected)
def test_gate_generator(pl_op, braket_gate, angle):
op = pl_op(angle, wires=[0, 1])
if op.name != "PSWAP":
assert np.allclose(
qml.matrix(op),
scipy.linalg.expm(1j * angle * qml.matrix(op.generator())))
def test_gate_adjoint_non_parametrized(pl_op, braket_gate):
op = pl_op(wires=[0, 1])
assert np.allclose(
np.dot(pl_op.compute_matrix(), qml.matrix(pl_op.adjoint(op))),
np.identity(4))
def _(h: qml.Hermitian):
return observables.Hermitian(qml.matrix(h))
def qubit_operator_string(self, observable):
"""Serializes a PennyLane observable to a string compatible with the
openfermion.QubitOperator class.
This method decomposes an observable into a sum of Pauli terms and
identities, if needed.
**Example**
>>> dev = QeQiskitDevice(wires=2)
>>> obs = qml.PauliZ(0)
>>> op_str = dev.qubit_operator_string(obs)
>>> print(op_str)
1 [Z0]
>>> obs = qml.Hadamard(0)
>>> op_str = dev.qubit_operator_string(obs)
>>> print(op_str)
0.7071067811865475 [X0] + 0.7071067811865475 [Z0]
Args:
observable (pennylane.operation.Observable): the observable to serialize
Returns:
str: the ``openfermion.QubitOperator`` string representation
"""
accepted_obs = {"PauliX", "PauliY", "PauliZ", "Identity"}
if isinstance(observable, Tensor):
need_decomposition = any(o.name not in accepted_obs
for o in observable.obs)
else:
need_decomposition = observable.name not in accepted_obs
if need_decomposition:
original_observable = observable
# Decompose the matrix of the observable
# This removes information about the wire labels used and
# consecutive integer wires are used
coeffs, obs_list = decompose_hamiltonian(
matrix(original_observable))
for idx in range(len(obs_list)):
obs = obs_list[idx]
if not isinstance(obs, Tensor):
# Convert terms to Tensor such that _terms_to_qubit_operator
# can be used
obs_list[idx] = Tensor(obs)
# Need to use the custom wire labels of the original observable
original_wires = original_observable.wires.tolist()
for o, mapped_w in zip(obs_list[idx].obs, original_wires):
o._wires = Wires(mapped_w)
else:
if not isinstance(observable, Tensor):
# If decomposition is not needed and is not a Tensor, we need
# to convert the single observable
observable = Tensor(observable)
coeffs = [1]
obs_list = [observable]
# Use consecutive integers as default wire_map
wire_map = {v: idx for idx, v in enumerate(self.wires)}
return _terms_to_qubit_operator_string(coeffs,
obs_list,
wires=wire_map)
# Rotations need to be included
(qml.PauliY(2), "[Z2]"),
(qml.PauliX(0) @ qml.PauliY(2), "[Z0 Z2]"),
(qml.PauliY(0) @ qml.PauliX(1) @ qml.PauliY(2), "[Z0 Z1 Z2]"),
]
# More advanced examples for testing the correct wires
obs_decomposed_wires_check = [
(qml.Hadamard(0), "0.7071067811865475 [X0] + 0.7071067811865475 [Z0]"),
(qml.Hadamard(2), "0.7071067811865475 [X2] + 0.7071067811865475 [Z2]"),
(
qml.Hadamard(2) @ qml.Hadamard(1),
"0.4999999999999999 [X2 X1] + 0.4999999999999999 [X2 Z1] + 0.4999999999999999 [Z2 X1] + 0.4999999999999999 [Z2 Z1]",
),
(
qml.Hermitian(qml.matrix(
qml.PauliY(1) @ qml.PauliX(0) @ qml.PauliZ(2)),
wires=[1, 0, 2]),
"1.0 [Y1 X0 Z2]",
),
(qml.PauliY(2) @ qml.Hermitian(qml.matrix(qml.PauliX(1)), wires=[1]),
"1.0 [Y2 X1]"),
]
class TestSerializeOperator:
"""Test the serialize_operator function"""
@pytest.mark.parametrize("wires, expected", [([2], "[Z2]"),
([0, 2], "[Z0 Z2]"),
([0, 1, 2], "[Z0 Z1 Z2]")])
def test_pauliz_operator_string(self, wires, expected):
"""Test that an operator is serialized correctly on a device with