def test_qiskit_mitigate_executor_with_shot_list():
true_zne_value = 1.0
scale_factors = [1.0, 3.0]
shot_list = [10_000, 30_000]
fac = inference.ExpFactory(
scale_factors=scale_factors, shot_list=shot_list, asymptote=0.5,
)
mitigated_executor = mitigate_executor(qiskit_executor, factory=fac)
circuit = qiskit_measure(
*generate_rb_circuits(
n_qubits=1,
num_cliffords=TEST_DEPTH,
trials=1,
return_type="qiskit",
),
0,
)
base = qiskit_executor(circuit)
zne_value = mitigated_executor(circuit)
assert abs(true_zne_value - zne_value) < abs(true_zne_value - base)
for i in range(len(fac._instack)):
assert fac._instack[i] == {
"scale_factor": scale_factors[i],
"shots": shot_list[i],
}
def test_mitigate_executor():
qp = generate_rb_circuits(
n_qubits=1, num_cliffords=TEST_DEPTH, trials=1, return_type="pyquil",
)
new_executor = mitigate_executor(noiseless_executor)
result = new_executor(*qp)
assert np.isclose(result, 1.0, atol=1e-5)
def test_mitigate_executor():
rand_circ = random_identity_circuit(depth=TEST_DEPTH)
qp = measure(rand_circ, qid=0)
new_executor = mitigate_executor(basic_executor, None, scale_noise)
# bad_result is computed with native noise (scale = 1)
bad_result = basic_executor(scale_noise(qp, 1))
good_result = new_executor(qp)
assert not np.isclose(bad_result, 1.0, atol=1.0e-1)
assert np.isclose(good_result, 1.0, atol=1.0e-1)
def test_mitigate_executor():
true_zne_value = 1.0
circuit = measure(
random_one_qubit_identity_circuit(num_cliffords=TEST_DEPTH), 0)
base = qiskit_executor(circuit)
mitigated_executor = zne.mitigate_executor(qiskit_executor)
zne_value = mitigated_executor(circuit)
assert abs(true_zne_value - zne_value) < abs(true_zne_value - base)
def test_mitigate_executor():
"""Tests a random identity circuit executor."""
rand_circ = random_one_qubit_identity_circuit(num_cliffords=TEST_DEPTH)
qp = measure(rand_circ, qid=0)
new_executor = mitigate_executor(basic_executor, scale_noise=scale_noise)
# bad_result is computed with native noise (scale = 1)
bad_result = basic_executor(scale_noise(qp, 1))
good_result = new_executor(qp)
assert not np.isclose(bad_result, 1.0, atol=1.0e-1)
assert np.isclose(good_result, 1.0, atol=1.0e-1)
def test_doc_is_preserved():
"""Tests that the doc of the original executor is preserved."""
def first_executor(circuit):
"""Doc of the original executor."""
return 0
mit_executor = mitigate_executor(first_executor)
assert mit_executor.__doc__ == first_executor.__doc__
@zne_decorator()
def second_executor(circuit):
"""Doc of the original executor."""
return 0
assert second_executor.__doc__ == first_executor.__doc__
def test_qiskit_mitigate_executor():
true_zne_value = 1.0
circuit = qiskit_measure(
*generate_rb_circuits(
n_qubits=1,
num_cliffords=TEST_DEPTH,
trials=1,
return_type="qiskit",
),
0,
)
base = qiskit_executor(circuit)
mitigated_executor = mitigate_executor(qiskit_executor)
zne_value = mitigated_executor(circuit)
assert abs(true_zne_value - zne_value) < abs(true_zne_value - base)
def test_mitigate_executor_with_shot_list():
"""Tests the mitigation of an executor using different shots
for each noise scale factor.
"""
rand_circ = random_one_qubit_identity_circuit(num_cliffords=TEST_DEPTH)
qp = measure(rand_circ, qid=0)
fac = RichardsonFactory(
[1.0, 2.0, 3.0], shot_list=[10 ** 4, 10 ** 5, 10 ** 6]
)
new_executor = mitigate_executor(
basic_executor, scale_noise=scale_noise, factory=fac
)
# bad_result is computed with native noise (scale = 1)
bad_result = basic_executor(scale_noise(qp, 1))
good_result = new_executor(qp)
assert not np.isclose(bad_result, 1.0, atol=1.0e-1)
assert np.isclose(good_result, 1.0, atol=1.0e-1)
assert fac._instack[0] == {"scale_factor": 1.0, "shots": 10 ** 4}
assert fac._instack[1] == {"scale_factor": 2.0, "shots": 10 ** 5}
assert fac._instack[2] == {"scale_factor": 3.0, "shots": 10 ** 6}
def test_random_benchmarks(scale_noise, fac):
trials = 3
circuits = generate_rb_circuits(n_qubits=2, num_cliffords=4, trials=trials)
noise = 0.01
obs = np.diag([1, 0, 0, 0])
def executor(qc):
return noisy_simulation(qc, noise=noise, obs=obs)
mit_executor = mitigate_executor(executor, fac, scale_noise)
unmitigated = []
mitigated = []
for qc in circuits:
unmitigated.append(executor(qc))
mitigated.append(mit_executor(qc))
unmit_err = np.abs(1.0 - np.asarray(unmitigated))
mit_err = np.abs(1.0 - np.asarray(mitigated))
assert np.average(unmit_err) >= np.average(mit_err)
def test_mitigate_executor_with_shot_list():
true_zne_value = 1.0
scale_factors = [1.0, 2.0, 3.0]
shot_list = [1_000, 2_000, 3_000]
fac = zne.inference.ExpFactory(scale_factors=scale_factors,
shot_list=shot_list)
mitigated_executor = zne.mitigate_executor(qiskit_executor, fac)
circuit = measure(
random_one_qubit_identity_circuit(num_cliffords=TEST_DEPTH), 0)
base = qiskit_executor(circuit)
zne_value = mitigated_executor(circuit)
assert abs(true_zne_value - zne_value) < abs(true_zne_value - base)
for i in range(len(fac._instack)):
assert fac._instack[i] == {
"scale_factor": scale_factors[i],
"shots": shot_list[i],
}
def test_mitigate_executor():
qp = random_one_qubit_identity_circuit(num_cliffords=TEST_DEPTH)
new_executor = mitigate_executor(noiseless_executor)
result = new_executor(qp)
assert np.isclose(result, 1.0, atol=1e-5)
