def test_naive_decoder_decode(error):
code = FiveQubitCode()
decoder = NaiveDecoder()
syndrome = pt.bsp(error, code.stabilizers.T)
recovery = decoder.decode(code, syndrome)
assert np.array_equal(pt.bsp(recovery, code.stabilizers.T), syndrome), (
'recovery {} does not give the same syndrome as the error {}'.format(
recovery, error))
assert np.all(pt.bsp(recovery ^ error, code.stabilizers.T) == 0), (
'recovery ^ error ({} ^ {}) does not commute with stabilizers.'.format(
recovery, error))
def test_run_count(max_runs, max_failures):
code = FiveQubitCode()
error_model = BitPhaseFlipErrorModel()
decoder = NaiveDecoder()
error_probability = 0.05
data = app.run(code, error_model, decoder, error_probability,
max_runs=max_runs, max_failures=max_failures) # no error raised
assert {'n_run', 'n_fail'} <= data.keys(), 'data={} missing count keys'
if max_runs is None and max_failures is None:
assert data['n_run'] == 1, 'n_run does not equal 1 when max_runs and max_failures unspecified'
if max_runs is not None:
assert data['n_run'] <= max_runs, ('n_run is not <= requested max_runs (data={}).'.format(data))
if max_failures is not None:
assert data['n_fail'] <= max_failures, ('n_fail is not <= requested max_failures (data={}).'.format(data))
def test_naive_decoder_properties():
decoder = NaiveDecoder()
assert isinstance(decoder.label, str)
assert isinstance(repr(decoder), str)
assert isinstance(str(decoder), str)
def test_naive_decoder_max_qubits_override():
code = SteaneCode()
decoder = NaiveDecoder(max_qubits=None)
decoder.decode(code, []) # no error raised
def test_naive_decoder_max_qubits_limit():
code = SteaneCode()
decoder = NaiveDecoder(max_qubits=5)
with pytest.raises(ValueError):
decoder.decode(code, None)
def test_naive_decoder_new_invalid_parameters(max_qubits):
with pytest.raises((ValueError, TypeError),
match=r"^NaiveDecoder") as exc_info:
NaiveDecoder(max_qubits)
print(exc_info)
def test_naive_decoder_new_valid_parameters(max_qubits):
NaiveDecoder(max_qubits) # no error raised
def test_run_invalid_parameters(error_probability):
with pytest.raises(ValueError) as exc_info:
app.run(FiveQubitCode(), DepolarizingErrorModel(), NaiveDecoder(), error_probability, max_runs=2)
print(exc_info)
class _FixedDecoder(Decoder):
def __init__(self, decoding):
self.decoding = decoding
def decode(self, code, syndrome, **kwargs):
return self.decoding
@property
def label(self):
return 'fixed'
@pytest.mark.parametrize('code, error_model, decoder', [
# each code with each valid decoder
(Color666Code(5), DepolarizingErrorModel(), Color666MPSDecoder(chi=8)),
(FiveQubitCode(), DepolarizingErrorModel(), NaiveDecoder()),
(PlanarCode(5, 5), DepolarizingErrorModel(), PlanarCMWPMDecoder()),
(PlanarCode(5, 5), DepolarizingErrorModel(), PlanarMPSDecoder(chi=6)),
(PlanarCode(5, 5), DepolarizingErrorModel(), PlanarMWPMDecoder()),
(PlanarCode(5, 5), DepolarizingErrorModel(), PlanarRMPSDecoder(chi=6)),
(PlanarCode(4, 5), BitPhaseFlipErrorModel(), PlanarYDecoder()),
(RotatedPlanarCode(7, 7), DepolarizingErrorModel(), RotatedPlanarMPSDecoder(chi=8)),
(RotatedPlanarCode(7, 7), DepolarizingErrorModel(), RotatedPlanarRMPSDecoder(chi=8)),
(RotatedPlanarCode(7, 7), BiasedDepolarizingErrorModel(100), RotatedPlanarSMWPMDecoder()),
(RotatedToricCode(6, 6), BiasedDepolarizingErrorModel(100), RotatedToricSMWPMDecoder()),
(SteaneCode(), DepolarizingErrorModel(), NaiveDecoder()),
(ToricCode(5, 5), DepolarizingErrorModel(), ToricMWPMDecoder()),
# each generic noise model
(PlanarCode(5, 5), BiasedDepolarizingErrorModel(10), PlanarMPSDecoder(chi=6)),
(PlanarCode(5, 5), BiasedYXErrorModel(10), PlanarMPSDecoder(chi=6)),
(PlanarCode(5, 5), BitFlipErrorModel(), PlanarMPSDecoder(chi=6)),