def recompose_kak(g, a, v, b) -> np.ndarray:
a1, a0 = a
x, y, z = v
b1, b0 = b
xx = cirq.kron(X, X)
yy = cirq.kron(Y, Y)
zz = cirq.kron(Z, Z)
a = cirq.kron(a1, a0)
m = cirq.map_eigenvalues(xx * x + yy * y + zz * z,
lambda e: np.exp(1j * e))
b = cirq.kron(b1, b0)
return cirq.dot(a, m, b) * g
def test_map_eigenvalues_raise(matrix, exponent, desired):
exp_mapped = cirq.map_eigenvalues(matrix, lambda e: complex(e)**exponent)
assert np.allclose(desired, exp_mapped)
def test_map_eigenvalues_identity(matrix):
identity_mapped = cirq.map_eigenvalues(matrix, lambda e: e)
assert np.allclose(matrix, identity_mapped)
]) * np.sqrt(0.5)),
(1,
np.array([
[1, 0, 0, -1j],
[0, 1, -1j, 0],
[0, -1j, 1, 0],
[-1j, 0, 0, 1],
]) * np.sqrt(0.5)),
(1,
np.array([
[1, 0, 0, 1j],
[0, 1, -1j, 0],
[0, -1j, 1, 0],
[1j, 0, 0, 1],
]) * np.sqrt(0.5)),
(1.5, cirq.map_eigenvalues(cirq.unitary(cirq.SWAP), lambda e: e**0.5)),
(2, cirq.unitary(cirq.SWAP).dot(cirq.unitary(cirq.CZ))),
(3, cirq.unitary(cirq.SWAP)),
(3, np.array([
[0, 0, 0, 1],
[0, 1, 0, 0],
[0, 0, 1, 0],
[1, 0, 0, 0j],
])),
] + [(1, _random_single_MS_effect())
for _ in range(10)] + [(3, cirq.testing.random_unitary(4))
for _ in range(10)] +
[(2, _random_double_MS_effect()) for _ in range(10)])
def test_two_to_ops(max_ms_depth: int, effect: np.array):
q0 = cirq.NamedQubit('q0')
q1 = cirq.NamedQubit('q1')
]) * np.sqrt(0.5)),
(1, 1,
np.array([
[1, 0, 0, -1j],
[0, 1, -1j, 0],
[0, -1j, 1, 0],
[-1j, 0, 0, 1],
]) * np.sqrt(0.5)),
(1, 1,
np.array([
[1, 0, 0, 1j],
[0, 1, -1j, 0],
[0, -1j, 1, 0],
[1j, 0, 0, 1],
]) * np.sqrt(0.5)),
(1.5, 3, cirq.map_eigenvalues(cirq.SWAP.matrix(), lambda e: e**0.5)),
(2, 2, cirq.SWAP.matrix().dot(cirq.CZ.matrix())),
(3, 3, cirq.SWAP.matrix()),
(3, 3, np.array([
[0, 0, 0, 1],
[0, 1, 0, 0],
[0, 0, 1, 0],
[1, 0, 0, 0j],
])),
] + [(1, 2, _random_single_partial_cz_effect())
for _ in range(10)] + [(2, 2, _random_double_full_cz_effect())
for _ in range(10)] +
[(2, 3, _random_double_partial_cz_effect())
for _ in range(10)] +
[(3, 3, cirq.testing.random_unitary(4))
for _ in range(10)])
def test_map_eigenvalues_raise(matrix, exponent, desired):
exp_mapped = cirq.map_eigenvalues(matrix, lambda e: complex(e)**exponent)
assert np.allclose(desired, exp_mapped)
def test_map_eigenvalues_identity(matrix):
identity_mapped = cirq.map_eigenvalues(matrix, lambda e: e)
assert np.allclose(matrix, identity_mapped)
[1j, 0, 0, 1],
]) * np.sqrt(0.5)),
(1, 1, np.array([
[1, 0, 0, -1j],
[0, 1, -1j, 0],
[0, -1j, 1, 0],
[-1j, 0, 0, 1],
]) * np.sqrt(0.5)),
(1, 1, np.array([
[1, 0, 0, 1j],
[0, 1, -1j, 0],
[0, -1j, 1, 0],
[1j, 0, 0, 1],
]) * np.sqrt(0.5)),
(1.5, 3, cirq.map_eigenvalues(cirq.SWAP.matrix(), lambda e: e**0.5)),
(2, 2, cirq.SWAP.matrix().dot(cirq.CZ.matrix())),
(3, 3, cirq.SWAP.matrix()),
(3, 3, np.array([
[0, 0, 0, 1],
[0, 1, 0, 0],
[0, 0, 1, 0],
[1, 0, 0, 0j],
])),
] + [
(1, 2, _random_single_partial_cz_effect()) for _ in range(10)
] + [
(2, 2, _random_double_full_cz_effect()) for _ in range(10)
] + [
