def test_flattened_tensor_product():
observable_one = Observable.Z() @ Observable.Y()
observable_two = Observable.X() @ Observable.H()
actual = Observable.TensorProduct([observable_one, observable_two])
expected = Observable.TensorProduct(
[Observable.Z(), Observable.Y(), Observable.X(), Observable.H()]
)
assert expected == actual
def test_tensor_product_matmul_tensor():
t1 = Observable.TensorProduct([Observable.Z(), Observable.I(), Observable.X()])
t2 = Observable.TensorProduct(
[Observable.Hermitian(matrix=Observable.I().to_matrix()), Observable.Y()]
)
t3 = t1 @ t2
assert t3.to_ir() == ["z", "i", "x", [[[1.0, 0], [0, 0]], [[0, 0], [1.0, 0]]], "y"]
assert t3.qubit_count == 5
assert t3.ascii_symbols == tuple(["Z@I@X@Hermitian@Y"] * 5)
def test_tensor_product_to_ir():
t = Observable.TensorProduct(
[Observable.Z(), Observable.I(),
Observable.X()])
assert t.to_ir() == ["z", "i", "x"]
assert t.qubit_count == 3
assert t.ascii_symbols == tuple(["Z@I@X"] * 3)
def test_tensor_product_rmatmul_observable():
t1 = Observable.TensorProduct([Observable.Z(), Observable.I(), Observable.X()])
o1 = Observable.I()
t = o1 @ t1
assert t.to_ir() == ["i", "z", "i", "x"]
assert t.qubit_count == 4
assert t.ascii_symbols == tuple(["I@Z@I@X"] * 4)
def test_observable_from_ir_tensor_product():
expected_observable = Observable.TensorProduct(
[Observable.Z(), Observable.I(),
Observable.X()])
actual_observable = observable_from_ir(["z", "i", "x"])
assert expected_observable == actual_observable
def test_tensor_product_rmatmul_value_error():
"a" @ Observable.TensorProduct(
[Observable.Z(), Observable.I(),
Observable.X()])
def test_tensor_product_value_error():
Observable.TensorProduct([Observable.Z(),
Observable.I(),
Observable.X()]) @ "a"
def test_tensor_product_eigenvalue_index_out_of_bounds():
obs = Observable.TensorProduct(
[Observable.Z(), Observable.I(),
Observable.X()])
obs.eigenvalue(8)
