def test_direct_fidelity_estimation_no_noise_clifford():
qubits = cirq.LineQubit.range(3)
circuit = cirq.Circuit(cirq.Z(qubits[0]), cirq.X(qubits[1]),
cirq.X(qubits[2]))
no_noise_simulator = cirq.DensityMatrixSimulator()
estimated_fidelity, _ = dfe.direct_fidelity_estimation(
circuit,
qubits,
no_noise_simulator,
n_measured_operators=3,
samples_per_term=0)
assert np.isclose(estimated_fidelity, 1.0, atol=0.01)
def test_direct_fidelity_estimation_no_noise_clifford():
qubits = cirq.LineQubit.range(3)
circuit = cirq.Circuit(cirq.Z(qubits[0]), cirq.X(qubits[1]),
cirq.X(qubits[2]))
no_noise = cirq.ConstantQubitNoiseModel(cirq.depolarize(0.0))
no_noise_simulator = cirq.DensityMatrixSimulator(noise=no_noise)
estimated_fidelity, _ = dfe.direct_fidelity_estimation(circuit,
qubits,
no_noise_simulator,
n_trials=100,
n_clifford_trials=3,
samples_per_term=0)
assert np.isclose(estimated_fidelity, 1.0, atol=0.01)
def test_direct_fidelity_estimation_with_noise_clifford():
qubits = cirq.LineQubit.range(3)
circuit = cirq.Circuit(cirq.Z(qubits[0]), cirq.X(qubits[1]),
cirq.X(qubits[2]))
noise = cirq.ConstantQubitNoiseModel(cirq.depolarize(0.1))
noisy_simulator = cirq.DensityMatrixSimulator(noise=noise)
estimated_fidelity, _ = dfe.direct_fidelity_estimation(
circuit,
qubits,
noisy_simulator,
n_measured_operators=None,
samples_per_term=100)
assert estimated_fidelity >= -1.0 and estimated_fidelity <= 1.0
def test_direct_fidelity_estimation_clifford_all_trials():
qubits = cirq.LineQubit.range(2)
circuit = cirq.Circuit(cirq.Z(qubits[0]), cirq.X(qubits[1]))
no_noise_simulator = cirq.DensityMatrixSimulator()
for n_measured_operators in [1, 2, 3, 4, None]:
estimated_fidelity, _ = dfe.direct_fidelity_estimation(
circuit,
qubits,
no_noise_simulator,
n_measured_operators=n_measured_operators,
samples_per_term=0,
)
assert np.isclose(estimated_fidelity, 1.0, atol=0.01)
def test_direct_fidelity_estimation_no_noise_non_clifford():
qubits = cirq.LineQubit.range(3)
circuit = cirq.Circuit(
cirq.Z(qubits[0])**0.123, cirq.X(qubits[1]), cirq.X(qubits[2]))
no_noise = cirq.ConstantQubitNoiseModel(cirq.depolarize(0.0))
estimated_fidelity = direct_fidelity_estimation.direct_fidelity_estimation(
circuit,
qubits,
no_noise,
n_trials=100,
n_clifford_trials=3,
samples_per_term=0)
assert np.isclose(estimated_fidelity, 1.0, atol=0.01)
def test_direct_fidelity_estimation_with_noise():
qubits = cirq.LineQubit.range(3)
circuit = cirq.Circuit(
cirq.Z(qubits[0])**0.25, # T-Gate, non Clifford.
cirq.X(qubits[1])**0.123,
cirq.X(qubits[2])**0.456)
noise = cirq.ConstantQubitNoiseModel(cirq.depolarize(0.1))
noisy_simulator = cirq.DensityMatrixSimulator(noise=noise)
estimated_fidelity, _ = dfe.direct_fidelity_estimation(circuit,
qubits,
noisy_simulator,
n_trials=10,
n_clifford_trials=3,
samples_per_term=10)
assert estimated_fidelity >= -1.0 and estimated_fidelity <= 1.0
def test_direct_fidelity_estimation_intermediate_results():
qubits = cirq.LineQubit.range(1)
circuit = cirq.Circuit(cirq.I(qubits[0]))
no_noise_simulator = cirq.DensityMatrixSimulator()
_, intermediate_result = dfe.direct_fidelity_estimation(
circuit,
qubits,
no_noise_simulator,
n_measured_operators=1,
samples_per_term=0)
# We only test a few fields to be sure that they are set properly. In
# particular, some of them are random, and so we don't test them.
np.testing.assert_allclose(
intermediate_result.clifford_state.ch_form.gamma, [0])
np.testing.assert_equal(len(intermediate_result.pauli_traces), 1)
assert np.isclose(intermediate_result.pauli_traces[0].rho_i, 1.0)
assert np.isclose(intermediate_result.pauli_traces[0].Pr_i, 0.5)
np.testing.assert_equal(len(intermediate_result.trial_results), 1)
assert np.isclose(intermediate_result.trial_results[0].sigma_i, 1.0)
