def test_readout_noise_after_moment():
program = cirq.Circuit()
qubits = cirq.LineQubit.range(3)
program.append([
cirq.H(qubits[0]),
cirq.CNOT(qubits[0], qubits[1]),
cirq.CNOT(qubits[1], qubits[2])
])
program.append(
[
cirq.measure(qubits[0], key='q0'),
cirq.measure(qubits[1], key='q1'),
cirq.measure(qubits[2], key='q2'),
],
strategy=cirq.InsertStrategy.NEW_THEN_INLINE,
)
# Use noise model to generate circuit
depol_noise = ccn.DepolarizingNoiseModel(depol_prob=0.01)
readout_noise = ccn.ReadoutNoiseModel(bitflip_prob=0.05)
noisy_circuit = cirq.Circuit(depol_noise.noisy_moments(program, qubits))
noisy_circuit = cirq.Circuit(
readout_noise.noisy_moments(noisy_circuit, qubits))
# Insert channels explicitly
true_noisy_program = cirq.Circuit()
true_noisy_program.append([cirq.H(qubits[0])])
true_noisy_program.append(
[
cirq.DepolarizingChannel(0.01).on(q).with_tags(ops.VirtualTag())
for q in qubits
],
strategy=cirq.InsertStrategy.NEW_THEN_INLINE,
)
true_noisy_program.append([cirq.CNOT(qubits[0], qubits[1])])
true_noisy_program.append(
[
cirq.DepolarizingChannel(0.01).on(q).with_tags(ops.VirtualTag())
for q in qubits
],
strategy=cirq.InsertStrategy.NEW_THEN_INLINE,
)
true_noisy_program.append([cirq.CNOT(qubits[1], qubits[2])])
true_noisy_program.append(
[
cirq.DepolarizingChannel(0.01).on(q).with_tags(ops.VirtualTag())
for q in qubits
],
strategy=cirq.InsertStrategy.NEW_THEN_INLINE,
)
true_noisy_program.append([
cirq.BitFlipChannel(0.05).on(q).with_tags(ops.VirtualTag())
for q in qubits
])
true_noisy_program.append([
cirq.measure(qubits[0], key='q0'),
cirq.measure(qubits[1], key='q1'),
cirq.measure(qubits[2], key='q2'),
])
_assert_equivalent_op_tree(true_noisy_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_per_qubit_readout_decay_from_data():
# Generate the readout decay noise model from calibration data.
calibration = cirq.google.Calibration(_CALIBRATION_DATA)
noise_model = simple_noise_from_calibration_metrics(
calibration=calibration, 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.CNOT(qubits[0], qubits[1])]),
cirq.Moment([cirq.CNOT(qubits[0], qubits[2])]),
cirq.Moment([
cirq.AmplitudeDampingChannel(decay_prob[i]).on(qubits[i])
for i in range(3)
]),
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(ops.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(ops.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_aggregate_decay_noise_after_moment():
program = cirq.Circuit()
qubits = cirq.LineQubit.range(3)
program.append([
cirq.H(qubits[0]),
cirq.CNOT(qubits[0], qubits[1]),
cirq.CNOT(qubits[1], qubits[2])
])
program.append(
[
cirq.measure(qubits[0], key='q0'),
cirq.measure(qubits[1], key='q1'),
cirq.measure(qubits[2], key='q2'),
],
strategy=cirq.InsertStrategy.NEW_THEN_INLINE,
)
# Use noise model to generate circuit
noise_model = ccn.DepolarizingWithDampedReadoutNoiseModel(
depol_prob=0.01, decay_prob=0.02, bitflip_prob=0.05)
noisy_circuit = cirq.Circuit(noise_model.noisy_moments(program, qubits))
# Insert channels explicitly
true_noisy_program = cirq.Circuit()
true_noisy_program.append([cirq.H(qubits[0])])
true_noisy_program.append(
[cirq.DepolarizingChannel(0.01).on(q) for q in qubits],
strategy=cirq.InsertStrategy.NEW_THEN_INLINE,
)
true_noisy_program.append([cirq.CNOT(qubits[0], qubits[1])])
true_noisy_program.append(
[cirq.DepolarizingChannel(0.01).on(q) for q in qubits],
strategy=cirq.InsertStrategy.NEW_THEN_INLINE,
)
true_noisy_program.append([cirq.CNOT(qubits[1], qubits[2])])
true_noisy_program.append(
[cirq.DepolarizingChannel(0.01).on(q) for q in qubits],
strategy=cirq.InsertStrategy.NEW_THEN_INLINE,
)
true_noisy_program.append(
[cirq.AmplitudeDampingChannel(0.02).on(q) for q in qubits])
true_noisy_program.append(
[cirq.BitFlipChannel(0.05).on(q) for q in qubits])
true_noisy_program.append([
cirq.measure(qubits[0], key='q0'),
cirq.measure(qubits[1], key='q1'),
cirq.measure(qubits[2], key='q2'),
])
_assert_equivalent_op_tree(true_noisy_program, noisy_circuit)
