def test_normalization(backend):
D, d, N = 10, 2, 10
tensors = [np.random.randn(1, d, D)
] + [np.random.randn(D, d, D)
for _ in range(N - 2)] + [np.random.randn(D, d, 1)]
mps = FiniteMPS(tensors, center_position=0, backend=backend)
mps.position(len(mps) - 1)
Z = mps.position(0, normalize=True)
np.testing.assert_allclose(Z, 1.0)
def test_apply_one_site_gate(backend_dtype_values):
backend = backend_dtype_values[0]
dtype = backend_dtype_values[1]
D, d, N = 10, 2, 10
tensors = [get_random_np((1, d, D), dtype)
] + [get_random_np((D, d, D), dtype)
for _ in range(N - 2)] + [get_random_np((D, d, 1), dtype)]
mps = FiniteMPS(tensors, center_position=0, backend=backend)
gate = get_random_np((2, 2), dtype)
mps.apply_one_site_gate(gate, 5)
actual = np.transpose(np.tensordot(tensors[5], gate, ([1], [1])),
(0, 2, 1))
np.testing.assert_allclose(mps.nodes[5].tensor, actual)
def test_mps_init(backend, N, pos):
D, d = 10, 2
tensors = [np.random.randn(1, d, D)
] + [np.random.randn(D, d, D)
for _ in range(N - 2)] + [np.random.randn(D, d, 1)]
with pytest.raises(ValueError):
FiniteMPS(tensors, center_position=pos, backend=backend)
def test_apply_two_site_gate(backend_dtype_values):
backend = backend_dtype_values[0]
dtype = backend_dtype_values[1]
D, d, N = 10, 2, 10
tensors = [get_random_np((1, d, D), dtype)
] + [get_random_np((D, d, D), dtype)
for _ in range(N - 2)] + [get_random_np((D, d, 1), dtype)]
mps = FiniteMPS(tensors, center_position=0, backend=backend)
gate = get_random_np((2, 2, 2, 2), dtype)
mps.apply_two_site_gate(gate, 5, 6)
tmp = np.tensordot(tensors[5], tensors[6], ([2], [0]))
actual = np.transpose(np.tensordot(tmp, gate, ([1, 2], [2, 3])),
(0, 2, 3, 1))
res = tn.contract_between(mps.nodes[5], mps.nodes[6])
np.testing.assert_allclose(res.tensor, actual)
def test_right_orthonormalization(backend_dtype_values):
backend = backend_dtype_values[0]
dtype = backend_dtype_values[1]
D, d, N = 10, 2, 10
tensors = [get_random_np((1, d, D), dtype)
] + [get_random_np((D, d, D), dtype)
for _ in range(N - 2)] + [get_random_np((D, d, 1), dtype)]
mps = FiniteMPS(tensors, center_position=0, backend=backend)
mps.position(len(mps) - 1)
mps.position(0)
assert all([
mps.check_orthonormality('right', site) < 1E-12
for site in range(len(mps))
])
def test_local_measurement(backend_dtype_values):
backend = backend_dtype_values[0]
dtype = backend_dtype_values[1]
D, d, N = 1, 2, 10
tensors_1 = [np.ones((1, d, D), dtype=dtype)] + [
np.ones((D, d, D), dtype=dtype) for _ in range(N - 2)
] + [np.ones((D, d, 1), dtype=dtype)]
mps_1 = FiniteMPS(tensors_1, center_position=0, backend=backend)
tensors_2 = [np.zeros((1, d, D), dtype=dtype)] + [
np.zeros((D, d, D), dtype=dtype) for _ in range(N - 2)
] + [np.zeros((D, d, 1), dtype=dtype)]
for t in tensors_2:
t[0, 0, 0] = 1
mps_2 = FiniteMPS(tensors_2, center_position=0, backend=backend)
sz = np.diag([0.5, -0.5]).astype(dtype)
result_1 = np.array(mps_1.measure_local_operator([sz] * N, range(N)))
result_2 = np.array(mps_2.measure_local_operator([sz] * N, range(N)))
np.testing.assert_almost_equal(result_1, np.zeros(N))
np.testing.assert_allclose(result_2, np.ones(N) * 0.5)
def test_correlation_measurement(backend_dtype_values):
backend = backend_dtype_values[0]
dtype = backend_dtype_values[1]
D, d, N = 1, 2, 10
tensors_1 = [np.ones((1, d, D), dtype=dtype)] + [
np.ones((D, d, D), dtype=dtype) for _ in range(N - 2)
] + [np.ones((D, d, 1), dtype=dtype)]
mps_1 = FiniteMPS(tensors_1, center_position=0, backend=backend)
mps_1.position(N - 1)
mps_1.position(0)
tensors_2 = [np.zeros((1, d, D), dtype=dtype)] + [
np.zeros((D, d, D), dtype=dtype) for _ in range(N - 2)
] + [np.zeros((D, d, 1), dtype=dtype)]
for t in tensors_2:
t[0, 0, 0] = 1
mps_2 = FiniteMPS(tensors_2, center_position=0, backend=backend)
mps_2.position(N - 1)
mps_2.position(0)
sz = np.diag([0.5, -0.5]).astype(dtype)
result_1 = np.array(
mps_1.measure_two_body_correlator(sz, sz, N // 2, range(N)))
result_2 = np.array(
mps_2.measure_two_body_correlator(sz, sz, N // 2, range(N)))
actual = np.zeros(N)
actual[N // 2] = 0.25
np.testing.assert_almost_equal(result_1, actual)
np.testing.assert_allclose(result_2, np.ones(N) * 0.25)