def test_expected_circuit(self):
"""Test if the circuit applied when using the QMC template is the same as the expected
circuit for a fixed example"""
p = np.ones(4) / 4
target_wires, estimation_wires = Wires(range(3)), Wires(range(3, 5))
with qml.tape.QuantumTape() as tape:
QuantumMonteCarlo(p, self.func, target_wires, estimation_wires)
queue_before_qpe = tape.queue[:2]
queue_after_qpe = tape.queue[2:]
A = probs_to_unitary(p)
R = func_to_unitary(self.func, 4)
assert len(queue_before_qpe) == 2
assert queue_before_qpe[0].name == "QubitUnitary"
assert queue_before_qpe[1].name == "QubitUnitary"
assert np.allclose(queue_before_qpe[0].matrix, A)
assert np.allclose(queue_before_qpe[1].matrix, R)
assert queue_before_qpe[0].wires == target_wires[:-1]
assert queue_before_qpe[1].wires == target_wires
Q = make_Q(A, R)
with qml.tape.QuantumTape() as qpe_tape:
qml.templates.QuantumPhaseEstimation(Q, target_wires, estimation_wires)
assert len(queue_after_qpe) == len(qpe_tape.queue)
assert all(o1.name == o2.name for o1, o2 in zip(queue_after_qpe, qpe_tape.queue))
assert all(
np.allclose(o1.matrix, o2.matrix) for o1, o2 in zip(queue_after_qpe, qpe_tape.queue)
)
assert all(o1.wires == o2.wires for o1, o2 in zip(queue_after_qpe, qpe_tape.queue))
def test_non_flat(self):
"""Test if a ValueError is raised when a non-flat array is input"""
p = np.ones((4, 1)) / 4
with pytest.raises(
ValueError,
match="The probability distribution must be specified as a"):
QuantumMonteCarlo(p, self.func, range(3), range(3, 5))
def test_wrong_size_p(self):
"""Test if a ValueError is raised when a probability distribution is passed whose length
cannot be mapped to qubits"""
p = np.ones(5) / 5
with pytest.raises(
ValueError,
match="The probability distribution must have a length"):
QuantumMonteCarlo(p, self.func, range(3), range(3, 5))
def test_unexpected_target_wires_number(self):
"""Test if a ValueError is raised when the number of target wires is incompatible with the
expected number of target wires inferred from the length of the input probability
distribution"""
p = np.ones(4) / 4
with pytest.raises(
ValueError,
match="The probability distribution of dimension 4 requires" " 3 target wires",
):
QuantumMonteCarlo(p, self.func, range(4), range(4, 6))
def test_expected_circuit(self):
"""Test if the circuit applied when using the QMC template is the same as the expected
circuit for a fixed example"""
p = np.ones(4) / 4
target_wires, estimation_wires = Wires(range(3)), Wires(range(3, 5))
op = QuantumMonteCarlo(p, self.func, target_wires, estimation_wires)
tape = op.expand()
# Do expansion in two steps to avoid also decomposing the first QubitUnitary
queue_before_qpe = tape.operations[:2]
# 2-qubit decomposition has 10 operations, and after is a 3-qubit gate so start at 11
queue_after_qpe = tape.expand().operations[11:]
A = probs_to_unitary(p)
R = func_to_unitary(self.func, 4)
assert len(queue_before_qpe) == 2
assert queue_before_qpe[0].name == "QubitUnitary"
assert queue_before_qpe[1].name == "QubitUnitary"
assert np.allclose(queue_before_qpe[0].matrix, A)
assert np.allclose(queue_before_qpe[1].matrix, R)
assert queue_before_qpe[0].wires == target_wires[:-1]
assert queue_before_qpe[1].wires == target_wires
Q = make_Q(A, R)
with qml.tape.QuantumTape() as qpe_tape:
qml.QuantumPhaseEstimation(Q, target_wires, estimation_wires)
qpe_tape = qpe_tape.expand()
assert len(queue_after_qpe) == len(qpe_tape.operations)
assert all(o1.name == o2.name
for o1, o2 in zip(queue_after_qpe, qpe_tape.operations))
assert all(
np.allclose(o1.matrix, o2.matrix)
for o1, o2 in zip(queue_after_qpe, qpe_tape.operations))
assert all(o1.wires == o2.wires
for o1, o2 in zip(queue_after_qpe, qpe_tape.operations))