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For replication, it appears that the sk_norm.py script is failing for the following case:
n = 2, a = 0.5
@pytest.mark.parametrize("n, a", [(2, 0.5), (2, -0.5), (3, 0.5), (3, -0.5)])
def test_s1_norm_werner(n, a):
"""Test S(1) norm of a Werner state."""
rho = werner(n, a)
# See:
# N. Johnston.
# Norms and Cones in the Theory of Quantum Entanglement.
# PhD thesis (arXiv:1207.1479)
# Proposition 5.2.10 and Table 5.1
expected = (1 + abs(min(0, a))) / (n * (n - a))
lower_bound, upper_bound = sk_operator_norm(rho, k=1)
> np.testing.assert_equal(np.allclose(lower_bound, expected), True)
E AssertionError:
E Items are not equal:
E ACTUAL: False
E DESIRED: True
tests/test_matrix_props/test_sk_norm.py:60: AssertionError
The text was updated successfully, but these errors were encountered:
Refer to the comment from #150 (comment)
For replication, it appears that the
sk_norm.py
script is failing for the following case:The text was updated successfully, but these errors were encountered: