def check_two_sets_of_krauss_are_same(krauss1, krauss2, numb=1000):
is_same = True
chann1 = AnalyticQChan(krauss1, [1, 1], 2, 2)
chann2 = AnalyticQChan(krauss2, [1, 1], 2, 2)
for _ in range(0, numb):
# Get random Rho
rho = np.array(rand_dm_ginibre(2).data.todense())
rho1 = chann1.channel(rho, 1)
rho2 = chann2.channel(rho, 1)
# Compare them
if np.any(np.abs(rho1 - rho2) > 1e-3):
is_same = False
break
return is_same
def test_channel_method_using_dephrasure():
r"""Test the method 'channel' from 'QCorr.channel.AnalyticQChan' using dephrasure kraus ops."""
p, q = 0.2, 0.4
single_krauss_ops = set_up_dephrasure_conditions(p, q)
orthogonal_krauss_indices = [2]
for sparse in [False, True]:
krauss_ops = single_krauss_ops.copy()
channel = AnalyticQChan(single_krauss_ops, [1, 1], 2, 3,
orthogonal_krauss_indices, sparse)
for n in range(1, 4):
if n != 1:
krauss_ops = np.kron(single_krauss_ops, krauss_ops)
# Get random density state.
rho = np.array(rand_dm_ginibre(2**n).data.todense())
# Test channel method using kraus perators matches 'channel.channel'
desired = np.zeros((3**n, 3**n), dtype=np.complex128)
for krauss in krauss_ops:
temp = krauss.dot(rho).dot(krauss.T)
desired += temp
actual = channel.channel(rho, n)
assert_array_almost_equal(actual, desired)
# Test constructor accepts the right input.
assert_raises(TypeError, AnalyticQChan, "asdsa", [1, 1], 2, 2)