def test_noise_from_metrics_unsupported():
# Attempt to generate a damping noise model (not yet supported).
calibration = cirq_google.Calibration(_CALIBRATION_DATA)
with pytest.raises(NotImplementedError,
match='Gate damping is not yet supported.'):
simple_noise_from_calibration_metrics(calibration=calibration,
damping_noise=True)
def test_per_qubit_combined_noise_from_data():
# Generate the combined noise model from calibration data.
calibration = cirq_google.Calibration(_CALIBRATION_DATA)
noise_model = simple_noise_from_calibration_metrics(
calibration=calibration,
depol_noise=True,
readout_error_noise=True,
readout_decay_noise=True,
)
# Create the circuit and apply the noise model.
qubits = [cirq.GridQubit(0, 0), cirq.GridQubit(0, 1), cirq.GridQubit(1, 0)]
program = cirq.Circuit(
cirq.Moment([cirq.H(qubits[0])]),
cirq.Moment([cirq.CNOT(qubits[0], qubits[1])]),
cirq.Moment([cirq.CNOT(qubits[0], qubits[2])]),
cirq.Moment([
cirq.measure(qubits[0], key='q0'),
cirq.measure(qubits[1], key='q1'),
cirq.measure(qubits[2], key='q2'),
]),
)
noisy_circuit = cirq.Circuit(noise_model.noisy_moments(program, qubits))
# Insert channels explicitly to construct expected output.
decay_prob = [
1 - exp(-1 / 0.007), 1 - exp(-1 / 0.008), 1 - exp(-1 / 0.009)
]
expected_program = cirq.Circuit(
cirq.Moment([cirq.H(qubits[0])]),
cirq.Moment([cirq.DepolarizingChannel(DEPOL_001).on(qubits[0])]),
cirq.Moment([cirq.CNOT(qubits[0], qubits[1])]),
cirq.Moment([
cirq.DepolarizingChannel(DEPOL_001).on(qubits[0]),
cirq.DepolarizingChannel(DEPOL_002).on(qubits[1]),
]),
cirq.Moment([cirq.CNOT(qubits[0], qubits[2])]),
cirq.Moment([
cirq.DepolarizingChannel(DEPOL_001).on(qubits[0]),
cirq.DepolarizingChannel(DEPOL_003).on(qubits[2]),
]),
cirq.Moment([
cirq.AmplitudeDampingChannel(decay_prob[i]).on(qubits[i])
for i in range(3)
]),
cirq.Moment([
cirq.BitFlipChannel(0.004).on(qubits[0]),
cirq.BitFlipChannel(0.005).on(qubits[1]),
cirq.BitFlipChannel(0.006).on(qubits[2]),
]),
cirq.Moment([
cirq.measure(qubits[0], key='q0'),
cirq.measure(qubits[1], key='q1'),
cirq.measure(qubits[2], key='q2'),
]),
)
assert_equivalent_op_tree(expected_program, noisy_circuit)
def test_per_qubit_depol_noise_from_data():
# Generate the depolarization noise model from calibration data.
calibration = cirq_google.Calibration(_CALIBRATION_DATA)
noise_model = simple_noise_from_calibration_metrics(calibration=calibration, depol_noise=True)
# Create the circuit and apply the noise model.
qubits = [cirq.GridQubit(0, 0), cirq.GridQubit(0, 1), cirq.GridQubit(1, 0)]
program = cirq.Circuit(
cirq.Moment([cirq.H(qubits[0])]),
cirq.Moment([cirq.CNOT(qubits[0], qubits[1])]),
cirq.Moment([cirq.CNOT(qubits[0], qubits[2])]),
cirq.Moment([cirq.Z(qubits[1]).with_tags(cirq.VirtualTag())]),
cirq.Moment(
[
cirq.measure(qubits[0], key='q0'),
cirq.measure(qubits[1], key='q1'),
cirq.measure(qubits[2], key='q2'),
]
),
)
noisy_circuit = cirq.Circuit(noise_model.noisy_moments(program, qubits))
# Insert channels explicitly to construct expected output.
expected_program = cirq.Circuit(
cirq.Moment([cirq.H(qubits[0])]),
cirq.Moment([cirq.DepolarizingChannel(DEPOL_001).on(qubits[0])]),
cirq.Moment([cirq.CNOT(qubits[0], qubits[1])]),
cirq.Moment(
[
cirq.DepolarizingChannel(DEPOL_001).on(qubits[0]),
cirq.DepolarizingChannel(DEPOL_002).on(qubits[1]),
]
),
cirq.Moment([cirq.CNOT(qubits[0], qubits[2])]),
cirq.Moment(
[
cirq.DepolarizingChannel(DEPOL_001).on(qubits[0]),
cirq.DepolarizingChannel(DEPOL_003).on(qubits[2]),
]
),
cirq.Moment([cirq.Z(qubits[1]).with_tags(cirq.VirtualTag())]),
cirq.Moment(
[
cirq.measure(qubits[0], key='q0'),
cirq.measure(qubits[1], key='q1'),
cirq.measure(qubits[2], key='q2'),
]
),
)
assert_equivalent_op_tree(expected_program, noisy_circuit)
def test_per_qubit_readout_error_from_data():
# Generate the readout error noise model from calibration data.
calibration = cirq_google.Calibration(_CALIBRATION_DATA)
noise_model = simple_noise_from_calibration_metrics(
calibration=calibration, readout_error_noise=True
)
# Create the circuit and apply the noise model.
qubits = [cirq.GridQubit(0, 0), cirq.GridQubit(0, 1), cirq.GridQubit(1, 0)]
program = cirq.Circuit(
cirq.Moment([cirq.H(qubits[0])]),
cirq.Moment([cirq.CNOT(qubits[0], qubits[1])]),
cirq.Moment([cirq.CNOT(qubits[0], qubits[2])]),
cirq.Moment(
[
cirq.measure(qubits[0], key='q0'),
cirq.measure(qubits[1], key='q1'),
cirq.measure(qubits[2], key='q2'),
]
),
)
noisy_circuit = cirq.Circuit(noise_model.noisy_moments(program, qubits))
# Insert channels explicitly to construct expected output.
expected_program = cirq.Circuit(
cirq.Moment([cirq.H(qubits[0])]),
cirq.Moment([cirq.CNOT(qubits[0], qubits[1])]),
cirq.Moment([cirq.CNOT(qubits[0], qubits[2])]),
cirq.Moment(
[
cirq.BitFlipChannel(0.004).on(qubits[0]),
cirq.BitFlipChannel(0.005).on(qubits[1]),
cirq.BitFlipChannel(0.006).on(qubits[2]),
]
),
cirq.Moment(
[
cirq.measure(qubits[0], key='q0'),
cirq.measure(qubits[1], key='q1'),
cirq.measure(qubits[2], key='q2'),
]
),
)
assert_equivalent_op_tree(expected_program, noisy_circuit)
def test_noise_from_metrics_requires_type():
# Attempt to generate a noise model without specifying a noise type.
calibration = cirq_google.Calibration(_CALIBRATION_DATA)
with pytest.raises(ValueError, match='At least one error type must be specified.'):
simple_noise_from_calibration_metrics(calibration=calibration)
