def test_floquet_parse_result_bad_metric():
q_00, q_01, q_02, q_03 = [cirq.GridQubit(0, index) for index in range(4)]
gate = cirq.FSimGate(theta=np.pi / 4, phi=0.0)
request = FloquetPhasedFSimCalibrationRequest(
gate=gate,
pairs=((q_00, q_01), (q_02, q_03)),
options=FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
),
)
result = cirq.google.CalibrationResult(
code=cirq.google.api.v2.calibration_pb2.SUCCESS,
error_message=None,
token=None,
valid_until=None,
metrics=cirq.google.Calibration(
cirq.google.api.v2.metrics_pb2.MetricsSnapshot(metrics=[
cirq.google.api.v2.metrics_pb2.Metric(
name='angles',
targets=[
'1000gerbils',
],
values=[
cirq.google.api.v2.metrics_pb2.Value(str_val='100_10'),
],
)
])),
)
with pytest.raises(ValueError, match='Unknown metric name 1000gerbils'):
_ = request.parse_result(result)
def test_floquet_to_calibration_layer():
q_00, q_01, q_02, q_03 = [cirq.GridQubit(0, index) for index in range(4)]
gate = cirq.FSimGate(theta=np.pi / 4, phi=0.0)
request = FloquetPhasedFSimCalibrationRequest(
gate=gate,
pairs=((q_00, q_01), (q_02, q_03)),
options=FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
),
)
assert request.to_calibration_layer() == cirq.google.CalibrationLayer(
calibration_type='floquet_phased_fsim_characterization',
program=cirq.Circuit([gate.on(q_00, q_01),
gate.on(q_02, q_03)]),
args={
'est_theta': True,
'est_zeta': True,
'est_chi': False,
'est_gamma': False,
'est_phi': True,
'readout_corrections': True,
},
)
def test_get_parameters():
q_00, q_01, q_02, q_03 = [cirq.GridQubit(0, index) for index in range(4)]
gate = cirq.FSimGate(theta=np.pi / 4, phi=0.0)
result = PhasedFSimCalibrationResult(
parameters={
(q_00, q_01):
PhasedFSimCharacterization(theta=0.1,
zeta=0.2,
chi=None,
gamma=None,
phi=0.3),
(q_02, q_03):
PhasedFSimCharacterization(theta=0.4,
zeta=0.5,
chi=None,
gamma=None,
phi=0.6),
},
gate=gate,
options=FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
),
)
assert result.get_parameters(q_00, q_01) == PhasedFSimCharacterization(
theta=0.1, zeta=0.2, chi=None, gamma=None, phi=0.3)
assert result.get_parameters(q_01, q_00) == PhasedFSimCharacterization(
theta=0.1, zeta=-0.2, chi=None, gamma=None, phi=0.3)
assert result.get_parameters(q_02, q_03) == PhasedFSimCharacterization(
theta=0.4, zeta=0.5, chi=None, gamma=None, phi=0.6)
assert result.get_parameters(q_00, q_03) is None
def test_from_moment():
q_00, q_01, q_02, q_03 = [cirq.GridQubit(0, index) for index in range(4)]
m = cirq.Moment(cirq.ISWAP(q_00, q_01) ** 0.5, cirq.ISWAP(q_02, q_03) ** 0.5)
options = FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
)
request = FloquetPhasedFSimCalibrationRequest.from_moment(m, options)
assert request == FloquetPhasedFSimCalibrationRequest(
gate=cirq.ISWAP ** 0.5, pairs=((q_00, q_01), (q_02, q_03)), options=options
)
non_identical = cirq.Moment(cirq.ISWAP(q_00, q_01) ** 0.5, cirq.ISWAP(q_02, q_03))
with pytest.raises(ValueError, match='must be identical'):
_ = FloquetPhasedFSimCalibrationRequest.from_moment(non_identical, options)
sq = cirq.Moment(cirq.X(q_00))
with pytest.raises(ValueError, match='must be two qubit gates'):
_ = FloquetPhasedFSimCalibrationRequest.from_moment(sq, options)
threeq = cirq.Moment(cirq.TOFFOLI(q_00, q_01, q_02))
with pytest.raises(ValueError, match='must be two qubit gates'):
_ = FloquetPhasedFSimCalibrationRequest.from_moment(threeq, options)
not_gate = cirq.Moment(cirq.CircuitOperation(cirq.FrozenCircuit()))
with pytest.raises(ValueError, match='must be two qubit gates'):
_ = FloquetPhasedFSimCalibrationRequest.from_moment(not_gate, options)
empty = cirq.Moment()
with pytest.raises(ValueError, match='No gates found'):
_ = FloquetPhasedFSimCalibrationRequest.from_moment(empty, options)
def test_run_characterization_with_simulator():
q_00, q_01, q_02, q_03 = [cirq.GridQubit(0, index) for index in range(4)]
gate = SQRT_ISWAP_GATE
request = FloquetPhasedFSimCalibrationRequest(
gate=gate,
pairs=((q_00, q_01), (q_02, q_03)),
options=FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
),
)
simulator = PhasedFSimEngineSimulator.create_with_ideal_sqrt_iswap()
actual = workflow.run_characterizations([request], simulator)
assert actual == [
PhasedFSimCalibrationResult(
parameters={
(q_00, q_01):
PhasedFSimCharacterization(theta=np.pi / 4,
zeta=0.0,
chi=None,
gamma=None,
phi=0.0),
(q_02, q_03):
PhasedFSimCharacterization(theta=np.pi / 4,
zeta=0.0,
chi=None,
gamma=None,
phi=0.0),
},
gate=SQRT_ISWAP_GATE,
options=FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
),
)
]
def test_options_phase_corrected_override():
assert (ALL_ANGLES_FLOQUET_PHASED_FSIM_CHARACTERIZATION.
zeta_chi_gamma_correction_override() == PhasedFSimCharacterization(
zeta=0.0, chi=0.0, gamma=0.0))
assert (FloquetPhasedFSimCalibrationOptions(
characterize_theta=False,
characterize_zeta=False,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=False,
).zeta_chi_gamma_correction_override() == PhasedFSimCharacterization())
def test_floquet_parse_result():
q_00, q_01, q_02, q_03 = [cirq.GridQubit(0, index) for index in range(4)]
gate = cirq.FSimGate(theta=np.pi / 4, phi=0.0)
request = FloquetPhasedFSimCalibrationRequest(
gate=gate,
pairs=((q_00, q_01), (q_02, q_03)),
options=FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
),
)
result = cirq.google.CalibrationResult(
code=cirq.google.api.v2.calibration_pb2.SUCCESS,
error_message=None,
token=None,
valid_until=None,
metrics=cirq.google.Calibration(
cirq.google.api.v2.metrics_pb2.MetricsSnapshot(metrics=[
cirq.google.api.v2.metrics_pb2.Metric(
name='angles',
targets=[
'0_qubit_a',
'0_qubit_b',
'0_theta_est',
'0_zeta_est',
'0_phi_est',
'1_qubit_a',
'1_qubit_b',
'1_theta_est',
'1_zeta_est',
'1_phi_est',
],
values=[
cirq.google.api.v2.metrics_pb2.Value(str_val='0_0'),
cirq.google.api.v2.metrics_pb2.Value(str_val='0_1'),
cirq.google.api.v2.metrics_pb2.Value(double_val=0.1),
cirq.google.api.v2.metrics_pb2.Value(double_val=0.2),
cirq.google.api.v2.metrics_pb2.Value(double_val=0.3),
cirq.google.api.v2.metrics_pb2.Value(str_val='0_2'),
cirq.google.api.v2.metrics_pb2.Value(str_val='0_3'),
cirq.google.api.v2.metrics_pb2.Value(double_val=0.4),
cirq.google.api.v2.metrics_pb2.Value(double_val=0.5),
cirq.google.api.v2.metrics_pb2.Value(double_val=0.6),
],
)
])),
)
assert request.parse_result(result) == PhasedFSimCalibrationResult(
parameters={
(q_00, q_01):
PhasedFSimCharacterization(theta=0.1,
zeta=0.2,
chi=None,
gamma=None,
phi=0.3),
(q_02, q_03):
PhasedFSimCharacterization(theta=0.4,
zeta=0.5,
chi=None,
gamma=None,
phi=0.6),
},
gate=gate,
options=FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
),
)
def test_run_floquet_characterization_for_circuit():
q_00, q_01, q_02, q_03 = [cirq.GridQubit(0, index) for index in range(4)]
gate = cirq.FSimGate(theta=np.pi / 4, phi=0.0)
circuit = cirq.Circuit([gate.on(q_00, q_01), gate.on(q_02, q_03)])
options = FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
)
job = cirq.google.engine.EngineJob('', '', '', None)
job._calibration_results = [
cirq.google.CalibrationResult(
code=cirq.google.api.v2.calibration_pb2.SUCCESS,
error_message=None,
token=None,
valid_until=None,
metrics=cirq.google.Calibration(
cirq.google.api.v2.metrics_pb2.MetricsSnapshot(metrics=[
cirq.google.api.v2.metrics_pb2.Metric(
name='angles',
targets=[
'0_qubit_a',
'0_qubit_b',
'0_theta_est',
'0_zeta_est',
'0_phi_est',
'1_qubit_a',
'1_qubit_b',
'1_theta_est',
'1_zeta_est',
'1_phi_est',
],
values=[
cirq.google.api.v2.metrics_pb2.Value(
str_val='0_0'),
cirq.google.api.v2.metrics_pb2.Value(
str_val='0_1'),
cirq.google.api.v2.metrics_pb2.Value(
double_val=0.1),
cirq.google.api.v2.metrics_pb2.Value(
double_val=0.2),
cirq.google.api.v2.metrics_pb2.Value(
double_val=0.3),
cirq.google.api.v2.metrics_pb2.Value(
str_val='0_2'),
cirq.google.api.v2.metrics_pb2.Value(
str_val='0_3'),
cirq.google.api.v2.metrics_pb2.Value(
double_val=0.4),
cirq.google.api.v2.metrics_pb2.Value(
double_val=0.5),
cirq.google.api.v2.metrics_pb2.Value(
double_val=0.6),
],
)
])),
)
]
engine = mock.MagicMock(spec=cirq.google.Engine)
engine.run_calibration.return_value = job
circuit_with_calibration, requests = workflow.run_floquet_characterization_for_circuit(
circuit, engine, 'qproc', cirq.google.FSIM_GATESET, options=options)
assert requests == [
PhasedFSimCalibrationResult(
parameters={
(q_00, q_01):
PhasedFSimCharacterization(theta=0.1,
zeta=0.2,
chi=None,
gamma=None,
phi=0.3),
(q_02, q_03):
PhasedFSimCharacterization(theta=0.4,
zeta=0.5,
chi=None,
gamma=None,
phi=0.6),
},
gate=gate,
options=options,
)
]
assert circuit_with_calibration.circuit == circuit
assert circuit_with_calibration.moment_to_calibration == [0]
def test_run_characterization():
q_00, q_01, q_02, q_03 = [cirq.GridQubit(0, index) for index in range(4)]
gate = cirq.FSimGate(theta=np.pi / 4, phi=0.0)
request = FloquetPhasedFSimCalibrationRequest(
gate=gate,
pairs=((q_00, q_01), (q_02, q_03)),
options=FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
),
)
result = cirq.google.CalibrationResult(
code=cirq.google.api.v2.calibration_pb2.SUCCESS,
error_message=None,
token=None,
valid_until=None,
metrics=cirq.google.Calibration(
cirq.google.api.v2.metrics_pb2.MetricsSnapshot(metrics=[
cirq.google.api.v2.metrics_pb2.Metric(
name='angles',
targets=[
'0_qubit_a',
'0_qubit_b',
'0_theta_est',
'0_zeta_est',
'0_phi_est',
'1_qubit_a',
'1_qubit_b',
'1_theta_est',
'1_zeta_est',
'1_phi_est',
],
values=[
cirq.google.api.v2.metrics_pb2.Value(str_val='0_0'),
cirq.google.api.v2.metrics_pb2.Value(str_val='0_1'),
cirq.google.api.v2.metrics_pb2.Value(double_val=0.1),
cirq.google.api.v2.metrics_pb2.Value(double_val=0.2),
cirq.google.api.v2.metrics_pb2.Value(double_val=0.3),
cirq.google.api.v2.metrics_pb2.Value(str_val='0_2'),
cirq.google.api.v2.metrics_pb2.Value(str_val='0_3'),
cirq.google.api.v2.metrics_pb2.Value(double_val=0.4),
cirq.google.api.v2.metrics_pb2.Value(double_val=0.5),
cirq.google.api.v2.metrics_pb2.Value(double_val=0.6),
],
)
])),
)
job = cirq.google.engine.EngineJob('', '', '', None)
job._calibration_results = [result]
engine = mock.MagicMock(spec=cirq.google.Engine)
engine.run_calibration.return_value = job
progress_calls = []
def progress(step: int, steps: int) -> None:
progress_calls.append((step, steps))
actual = workflow.run_characterizations([request],
engine,
'qproc',
cirq.google.FSIM_GATESET,
progress_func=progress)
expected = [
PhasedFSimCalibrationResult(
parameters={
(q_00, q_01):
PhasedFSimCharacterization(theta=0.1,
zeta=0.2,
chi=None,
gamma=None,
phi=0.3),
(q_02, q_03):
PhasedFSimCharacterization(theta=0.4,
zeta=0.5,
chi=None,
gamma=None,
phi=0.6),
},
gate=gate,
options=FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
),
)
]
assert actual == expected
assert progress_calls == [(1, 1)]
