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20 hours ago •
quantumlib
quantumlib
Doube check that depolarize2 error rate statistical test failure on macos was likely a false positive
E AssertionError: Sample rate 0.0108 is over 5 standard deviations away from 0.006666665896773338.
This is presumably a one in a million failure. But the test has been run a lot of times and there are a lot of similar tests. Just compute the probability of seeing this sort of thing by chance and eyeball if it's reasonable.
Note that this occurred very recently after a change to how seeding is done.
work/Stim/Stim/src/stim/circuit/circuit_gate_target_pybind_test.py ..... [ 1%]
.... [ 1%]
work/Stim/Stim/src/stim/circuit/circuit_instruction_pybind_test.py ..... [ 2%]
[ 2%]
work/Stim/Stim/src/stim/circuit/circuit_pybind_test.py ................. [ 6%]
............... [ 9%]
work/Stim/Stim/src/stim/circuit/circuit_repeat_block_test.py ... [ 10%]
work/Stim/Stim/src/stim/dem/detector_error_model_instruction_pybind_test.py . [ 10%]
....... [ 11%]
work/Stim/Stim/src/stim/dem/detector_error_model_pybind_test.py ........ [ 13%]
..... [ 14%]
work/Stim/Stim/src/stim/dem/detector_error_model_repeat_block_pybind_test.py . [ 14%]
.. [ 14%]
work/Stim/Stim/src/stim/dem/detector_error_model_target_pybind_test.py . [ 15%]
..... [ 16%]
work/Stim/Stim/src/stim/py/compiled_detector_sampler_pybind_test.py . [ 16%]
work/Stim/Stim/src/stim/py/compiled_measurement_sampler_pybind_test.py . [ 16%]
.... [ 17%]
work/Stim/Stim/src/stim/py/stim_pybind_test.py .... [ 18%]
work/Stim/Stim/src/stim/simulators/matched_error_pybind_test.py ....... [ 19%]
work/Stim/Stim/src/stim/simulators/measurements_to_detection_events_test.py . [ 19%]
. [ 20%]
work/Stim/Stim/src/stim/simulators/tableau_simulator_pybind_test.py .... [ 20%]
.................................... [ 28%]
work/Stim/Stim/src/stim/stabilizers/pauli_string_pybind_test.py ........ [ 29%]
............... [ 33%]
work/Stim/Stim/src/stim/stabilizers/tableau_pybind_test.py ............. [ 35%]
......... [ 37%]
work/Stim/Stim/glue/cirq/stimcirq/_cirq_to_stim_test.py ................ [ 40%]
........................................................................ [ 55%]
.........................................................F.............. [ 70%]
............ [ 72%]
work/Stim/Stim/glue/cirq/stimcirq/_det_annotation_test.py ...... [ 74%]
work/Stim/Stim/glue/cirq/stimcirq/_measure_and_or_reset_gate_test.py .. [ 74%]
work/Stim/Stim/glue/cirq/stimcirq/_obs_annotation_test.py ...... [ 75%]
work/Stim/Stim/glue/cirq/stimcirq/_shift_coords_annotation_test.py ..... [ 76%]
. [ 77%]
work/Stim/Stim/glue/cirq/stimcirq/_stim_sampler_test.py ..... [ 78%]
work/Stim/Stim/glue/cirq/stimcirq/_stim_to_cirq_test.py ................ [ 81%]
........................................................................ [ 96%]
........... [ 98%]
work/Stim/Stim/glue/cirq/stimcirq/_sweep_pauli_test.py .... [ 99%]
work/Stim/Stim/glue/cirq/stimcirq/_two_qubit_asymmetric_depolarize_test.py . [ 99%]
... [100%]
=================================== FAILURES ===================================
__ test_tableau_simulator_sampling_noisy_gates_agrees_with_cirq_data[gate14] ___
gate = cirq.depolarize(p=0.1,n_qubits=2)
@pytest.mark.parametrize("gate", ROUND_TRIP_NOISY_GATES)
def test_tableau_simulator_sampling_noisy_gates_agrees_with_cirq_data(gate: cirq.Gate):
# Technically this be a test of the `stim` package itself, but it's so convenient to compare to cirq.
# Create test circuit that uses superdense coding to quantify arbitrary Pauli error mixtures.
n = cirq.num_qubits(gate)
qs = cirq.LineQubit.range(n)
circuit = cirq.Circuit(
cirq.H.on_each(qs),
[cirq.CNOT(q, q + n) for q in qs],
gate(*qs),
[cirq.CNOT(q, q + n) for q in qs],
cirq.H.on_each(qs),
)
expected_rates = cirq.final_density_matrix(circuit).diagonal().real
# Convert test circuit to Stim and sample from it.
stim_circuit, _ = cirq_circuit_to_stim_data(
circuit + cirq.measure(*sorted(circuit.all_qubits())[::-1])
)
sample_count = 10000
samples = []
for _ in range(sample_count):
sim = stim.TableauSimulator()
sim.do(stim_circuit)
s = 0
for k, v in enumerate(sim.current_measurement_record()):
s |= v << k
samples.append(s)
unique, counts = np.unique(samples, return_counts=True)
# Compare sample rates to expected rates.
for value, count in zip(unique, counts):
expected_rate = expected_rates[value]
actual_rate = count / sample_count
allowed_variation = 5 * (expected_rate * (1 - expected_rate) / sample_count) ** 0.5
if not 0 <= expected_rate - allowed_variation <= 1:
raise ValueError("Not enough samples to bound results away from extremes.")
> assert abs(expected_rate - actual_rate) < allowed_variation, (
f"Sample rate {actual_rate} is over 5 standard deviations away from {expected_rate}.\n"
f"Gate: {gate}\n"
f"Test circuit:\n{circuit}\n"
f"Converted circuit:\n{stim_circuit}\n"
)
E AssertionError: Sample rate 0.0108 is over 5 standard deviations away from 0.006666665896773338.
E Gate: depolarize(p=0.1,n_qubits=2)
E Test circuit:
E ┌──┐ ┌──┐
E 0: ───H────@─────D(0.1)────@─────H───
E │ │ │
E 1: ───H────┼@────#2────────┼@────H───
E ││ ││
E 2: ────────X┼──────────────X┼────────
E │ │
E 3: ─────────X───────────────X────────
E └──┘ └──┘
E Converted circuit:
E H 0 1
E TICK
E CX 0 2 1 3
E TICK
E DEPOLARIZE2(0.1) 0 1
E TICK
E CX 0 2 1 3
E TICK
E H 0 1
E TICK
E M 3 2 1 0
E TICK
E
E assert 0.004133334103226662 < 0.004068851638544387
E + where 0.004133334103226662 = abs((0.006666666 - 0.0108))
work/Stim/Stim/glue/cirq/stimcirq/_cirq_to_stim_test.py:235: AssertionError
=========================== short test summary info ============================
FAILED work/Stim/Stim/glue/cirq/stimcirq/_cirq_to_stim_test.py::test_tableau_simulator_sampling_noisy_gates_agrees_with_cirq_data[gate14]
=================== 1 failed, 486 passed in 72.11s (0:01:12) ===================
Error: Command pytest /Users/runner/work/Stim/Stim/src /Users/runner/work/Stim/Stim/glue/cirq failed with code 1. None
✕ 122.06s
Error: Process completed with exit code 1.
Saw this again https://github.com/quantumlib/Stim/runs/6332576101?check_suite_focus=true
============================= test session starts ==============================
platform darwin -- Python 3.9.12, pytest-7.1.2, pluggy-1.0.0
rootdir: /Users/runner/work/Stim/Stim
collected 491 items
work/Stim/Stim/src/stim/circuit/circuit_gate_target_pybind_test.py ..... [ 1%]
.... [ 1%]
work/Stim/Stim/src/stim/circuit/circuit_instruction_pybind_test.py ..... [ 2%]
[ 2%]
work/Stim/Stim/src/stim/circuit/circuit_pybind_test.py ................. [ 6%]
.................. [ 9%]
work/Stim/Stim/src/stim/circuit/circuit_repeat_block_test.py ... [ 10%]
work/Stim/Stim/src/stim/dem/detector_error_model_instruction_pybind_test.py . [ 10%]
....... [ 12%]
work/Stim/Stim/src/stim/dem/detector_error_model_pybind_test.py ........ [ 13%]
..... [ 14%]
work/Stim/Stim/src/stim/dem/detector_error_model_repeat_block_pybind_test.py . [ 15%]
.. [ 15%]
work/Stim/Stim/src/stim/dem/detector_error_model_target_pybind_test.py . [ 15%]
..... [ 16%]
work/Stim/Stim/src/stim/py/compiled_detector_sampler_pybind_test.py . [ 16%]
work/Stim/Stim/src/stim/py/compiled_measurement_sampler_pybind_test.py . [ 17%]
.... [ 17%]
work/Stim/Stim/src/stim/py/stim_pybind_test.py .... [ 18%]
work/Stim/Stim/src/stim/simulators/matched_error_pybind_test.py ....... [ 20%]
work/Stim/Stim/src/stim/simulators/measurements_to_detection_events_test.py . [ 20%]
. [ 20%]
work/Stim/Stim/src/stim/simulators/tableau_simulator_pybind_test.py .... [ 21%]
.................................... [ 28%]
work/Stim/Stim/src/stim/stabilizers/pauli_string_pybind_test.py ........ [ 30%]
............... [ 33%]
work/Stim/Stim/src/stim/stabilizers/tableau_pybind_test.py ............. [ 36%]
......... [ 37%]
work/Stim/Stim/glue/cirq/stimcirq/_cirq_to_stim_test.py ................ [ 41%]
........................................................................ [ 55%]
........................................................................ [ 70%]
.......F..... [ 73%]
work/Stim/Stim/glue/cirq/stimcirq/_det_annotation_test.py ...... [ 74%]
work/Stim/Stim/glue/cirq/stimcirq/_measure_and_or_reset_gate_test.py .. [ 74%]
work/Stim/Stim/glue/cirq/stimcirq/_obs_annotation_test.py ...... [ 75%]
work/Stim/Stim/glue/cirq/stimcirq/_shift_coords_annotation_test.py ..... [ 76%]
. [ 77%]
work/Stim/Stim/glue/cirq/stimcirq/_stim_sampler_test.py ..... [ 78%]
work/Stim/Stim/glue/cirq/stimcirq/_stim_to_cirq_test.py ................ [ 81%]
........................................................................ [ 96%]
........... [ 98%]
work/Stim/Stim/glue/cirq/stimcirq/_sweep_pauli_test.py .... [ 99%]
work/Stim/Stim/glue/cirq/stimcirq/_two_qubit_asymmetric_depolarize_test.py . [ 99%]
... [100%]
=================================== FAILURES ===================================
__ test_tableau_simulator_sampling_noisy_gates_agrees_with_cirq_data[gate36] ___
gate = stimcirq.TwoQubitAsymmetricDepolarizingChannel((0.0033333333333333335, 0.006666666666666667, 0.01, 0.01333333333333333...66666666666667, 0.03, 0.03333333333333333, 0.03666666666666667, 0.04, 0.043333333333333335, 0.04666666666666667, 0.05))
@pytest.mark.parametrize("gate", ROUND_TRIP_NOISY_GATES)
def test_tableau_simulator_sampling_noisy_gates_agrees_with_cirq_data(gate: cirq.Gate):
# Technically this be a test of the `stim` package itself, but it's so convenient to compare to cirq.
# Create test circuit that uses superdense coding to quantify arbitrary Pauli error mixtures.
n = cirq.num_qubits(gate)
qs = cirq.LineQubit.range(n)
circuit = cirq.Circuit(
cirq.H.on_each(qs),
[cirq.CNOT(q, q + n) for q in qs],
gate(*qs),
[cirq.CNOT(q, q + n) for q in qs],
cirq.H.on_each(qs),
)
expected_rates = cirq.final_density_matrix(circuit).diagonal().real
# Convert test circuit to Stim and sample from it.
stim_circuit, _ = cirq_circuit_to_stim_data(
circuit + cirq.measure(*sorted(circuit.all_qubits())[::-1])
)
sample_count = 10000
samples = []
for _ in range(sample_count):
sim = stim.TableauSimulator()
sim.do(stim_circuit)
s = 0
for k, v in enumerate(sim.current_measurement_record()):
s |= v << k
samples.append(s)
unique, counts = np.unique(samples, return_counts=True)
# Compare sample rates to expected rates.
for value, count in zip(unique, counts):
expected_rate = expected_rates[value]
actual_rate = count / sample_count
allowed_variation = 5 * (expected_rate * (1 - expected_rate) / sample_count) ** 0.5
if not 0 <= expected_rate - allowed_variation <= 1:
raise ValueError("Not enough samples to bound results away from extremes.")
> assert abs(expected_rate - actual_rate) < allowed_variation, (
f"Sample rate {actual_rate} is over 5 standard deviations away from {expected_rate}.\n"
f"Gate: {gate}\n"
f"Test circuit:\n{circuit}\n"
f"Converted circuit:\n{stim_circuit}\n"
)
E AssertionError: Sample rate 0.0386 is over 5 standard deviations away from 0.0299999937415123.
E Gate: stimcirq.TwoQubitAsymmetricDepolarizingChannel((0.0033333333333333335, 0.006666666666666667, 0.01, 0.013333333333333334, 0.016666666666666666, 0.02, 0.023333333333333334, 0.02666666666666667, 0.03, 0.03333333333333333, 0.03666666666666667, 0.04, 0.043333333333333335, 0.04666666666666667, 0.05))
E Test circuit:
E ┌──┐ ┌──┐
E 0: ───H────@─────PauliMix(II:0.6,IX:0.00333,IY:0.00667,IZ:0.01,XI:0.0133,XX:0.0167,XY:0.02,XZ:0.0233,YI:0.0267,YX:0.03,YY:0.0333,YZ:0.0367,ZI:0.04,ZX:0.0433,ZY:0.0467,ZZ:0.05)────@─────H───
E │ │ │
E 1: ───H────┼@────#2────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┼@────H───
E ││ ││
E 2: ────────X┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────X┼────────
E │ │
E 3: ─────────X───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────X────────
E └──┘ └──┘
E Converted circuit:
E H 0 1
E TICK
E CX 0 2 1 3
E TICK
E PAULI_CHANNEL_2(0.00333333, 0.00666667, 0.01, 0.0133333, 0.0166667, 0.02, 0.0233333, 0.0266667, 0.03, 0.0333333, 0.0366667, 0.04, 0.0433333, 0.0466667, 0.05) 0 1
E TICK
E CX 0 2 1 3
E TICK
E H 0 1
E TICK
E M 3 2 1 0
E TICK
E
E assert 0.008600006258487704 < 0.00852936019[245](https://github.com/quantumlib/Stim/runs/6332576101?check_suite_focus=true#step:10:245)018
E + where 0.008600006[258](https://github.com/quantumlib/Stim/runs/6332576101?check_suite_focus=true#step:10:258)487704 = abs((0.0[299](https://github.com/quantumlib/Stim/runs/6332576101?check_suite_focus=true#step:10:299)99994 - 0.0386))
work/Stim/Stim/glue/cirq/stimcirq/_cirq_to_stim_test.py:235: AssertionError
=============================== warnings summary ===============================
I think, both times, this failed on osx. This most recent one was OSX. If it happens again make sure to document.
Saw one on windows this time:
================================== FAILURES ===================================
__ test_tableau_simulator_sampling_noisy_gates_agrees_with_cirq_data[gate36] __
gate = stimcirq.TwoQubitAsymmetricDepolarizingChannel((0.0033333333333333335, 0.006666666666666667, 0.01, 0.01333333333333333...66666666666667, 0.03, 0.03333333333333333, 0.03666666666666667, 0.04, 0.043333333333333335, 0.04666666666666667, 0.05))
@pytest.mark.parametrize("gate", ROUND_TRIP_NOISY_GATES)
def test_tableau_simulator_sampling_noisy_gates_agrees_with_cirq_data(gate: cirq.Gate):
# Technically this be a test of the `stim` package itself, but it's so convenient to compare to cirq.
# Create test circuit that uses superdense coding to quantify arbitrary Pauli error mixtures.
n = cirq.num_qubits(gate)
qs = cirq.LineQubit.range(n)
circuit = cirq.Circuit(
cirq.H.on_each(qs),
[cirq.CNOT(q, q + n) for q in qs],
gate(*qs),
[cirq.CNOT(q, q + n) for q in qs],
cirq.H.on_each(qs),
)
expected_rates = cirq.final_density_matrix(circuit).diagonal().real
# Convert test circuit to Stim and sample from it.
stim_circuit, _ = cirq_circuit_to_stim_data(
circuit + cirq.measure(*sorted(circuit.all_qubits())[::-1])
)
sample_count = 10000
samples = []
for _ in range(sample_count):
sim = stim.TableauSimulator()
sim.do(stim_circuit)
s = 0
for k, v in enumerate(sim.current_measurement_record()):
s |= v << k
samples.append(s)
unique, counts = np.unique(samples, return_counts=True)
# Compare sample rates to expected rates.
for value, count in zip(unique, counts):
expected_rate = expected_rates[value]
actual_rate = count / sample_count
allowed_variation = 5 * (expected_rate * (1 - expected_rate) / sample_count) ** 0.5
if not 0 <= expected_rate - allowed_variation <= 1:
raise ValueError("Not enough samples to bound results away from extremes.")
> assert abs(expected_rate - actual_rate) < allowed_variation, (
f"Sample rate {actual_rate} is over 5 standard deviations away from {expected_rate}.\n"
f"Gate: {gate}\n"
f"Test circuit:\n{circuit}\n"
f"Converted circuit:\n{stim_circuit}\n"
)
E AssertionError: Sample rate 0.0266 is over 5 standard deviations away from 0.03666665777564049.
E Gate: stimcirq.TwoQubitAsymmetricDepolarizingChannel((0.00[333](https://github.com/quantumlib/Stim/runs/6641808548?check_suite_focus=true#step:10:338)33333333333335, 0.006666666666666667, 0.01, 0.013333333333333[334](https://github.com/quantumlib/Stim/runs/6641808548?check_suite_focus=true#step:10:339), 0.016666666666666666, 0.02, 0.023333333333333334, 0.02666666666666667, 0.03, 0.03333333333333333, 0.03666666666666667, 0.04, 0.043333333333333[335](https://github.com/quantumlib/Stim/runs/6641808548?check_suite_focus=true#step:10:340), 0.04666666666666667, 0.05))
E Test circuit:
E \u250c\u2500\u2500\u2510 \u250c\u2500\u2500\u2510
E 0: \u2500\u2500\u2500H\u2500\u2500\u2500\u2500@\u2500\u2500\u2500\u2500\u2500PauliMix(II:0.6,IX:0.00333,IY:0.00667,IZ:0.01,XI:0.0133,XX:0.0167,XY:0.02,XZ:0.0233,YI:0.0267,YX:0.03,YY:0.0333,YZ:0.0367,ZI:0.04,ZX:0.0433,ZY:0.0467,ZZ:0.05)\u2500\u2500\u2500\u2500@\u2500\u2500\u2500\u2500\u2500H\u2500\u2500\u2500
E \u2502 \u2502 \u2502
E 1: \u2500\u2500\u2500H\u2500\u2500\u2500\u2500\u253c@\u2500\u2500\u2500\u2500#2\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c@\u2500\u2500\u2500\u2500H\u2500\u2500\u2500
E \u2502\u2502 \u2502\u2502
E 2: \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500X\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500X\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500
E \u2502 \u2502
E 3: \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500X\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500X\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500
E \u2514\u2500\u2500\u2518 \u2514\u2500\u2500\u2518
E Converted circuit:
E H 0 1
E TICK
E CX 0 2 1 3
E TICK
E PAULI_CHANNEL_2(0.00333333, 0.00666667, 0.01, 0.0133333, 0.0166667, 0.02, 0.0233333, 0.0266667, 0.03, 0.0333333, 0.0[366](https://github.com/quantumlib/Stim/runs/6641808548?check_suite_focus=true#step:10:371)667, 0.04, 0.0433333, 0.0466667, 0.05) 0 1
E TICK
E CX 0 2 1 3
E TICK
E H 0 1
E TICK
E M 3 2 1 0
E TICK
E
E assert 0.010066657775640489 < 0.009397102476721821
E + where 0.010066657775640489 = abs((0.036666658 - 0.0266))
D:\a\Stim\Stim\glue\cirq\stimcirq\_cirq_to_stim_test.py:235: AssertionError
============================== warnings summary ===============================
Was the source of this ever pinpointed? I am really glad that this is documented regardless of the source
@ChrisPattison No.
I suspect it's just that the tests have tolerances that are too tight, but I'm not closing the issue until I actually do the math and work out the expected false positive rate.