def test_random_operators_are_reproducible(self):
op1 = random_diagonal_coulomb_hamiltonian(5, seed=5947)
op2 = random_diagonal_coulomb_hamiltonian(5, seed=5947)
numpy.testing.assert_allclose(op1.one_body, op2.one_body)
numpy.testing.assert_allclose(op1.two_body, op2.two_body)
op1 = random_interaction_operator(5, seed=8911)
op2 = random_interaction_operator(5, seed=8911)
numpy.testing.assert_allclose(op1.one_body_tensor, op2.one_body_tensor)
numpy.testing.assert_allclose(op1.two_body_tensor, op2.two_body_tensor)
op1 = random_quadratic_hamiltonian(5, seed=17711)
op2 = random_quadratic_hamiltonian(5, seed=17711)
numpy.testing.assert_allclose(op1.combined_hermitian_part,
op2.combined_hermitian_part)
numpy.testing.assert_allclose(op1.antisymmetric_part,
op2.antisymmetric_part)
op1 = random_antisymmetric_matrix(5, seed=24074)
op2 = random_antisymmetric_matrix(5, seed=24074)
numpy.testing.assert_allclose(op1, op2)
op1 = random_hermitian_matrix(5, seed=56753)
op2 = random_hermitian_matrix(5, seed=56753)
numpy.testing.assert_allclose(op1, op2)
op1 = random_unitary_matrix(5, seed=56486)
op2 = random_unitary_matrix(5, seed=56486)
numpy.testing.assert_allclose(op1, op2)
def test_integration_random_diagonal_coulomb_hamiltonian(self):
hamiltonian1 = normal_ordered(
get_fermion_operator(
random_diagonal_coulomb_hamiltonian(n_qubits=7)))
hamiltonian2 = normal_ordered(
get_fermion_operator(
random_diagonal_coulomb_hamiltonian(n_qubits=7)))
reference = normal_ordered(commutator(hamiltonian1, hamiltonian2))
result = commutator_ordered_diagonal_coulomb_with_two_body_operator(
hamiltonian1, hamiltonian2)
self.assertTrue(result.isclose(reference))
def test_multiply(self):
n_qubits = 5
op1 = random_diagonal_coulomb_hamiltonian(n_qubits)
op2 = op1 * 1.5
op3 = 1.5 * op1
self.assertEqual(get_fermion_operator(op1) * 1.5,
get_fermion_operator(op2),
get_fermion_operator(op3))
def test_simulate_trotter_unsupported_trotter_step_raises_error():
qubits = cirq.LineQubit.range(2)
control = cirq.LineQubit(-1)
hamiltonian = random_diagonal_coulomb_hamiltonian(2, seed=0)
time = 1.0
class EmptyTrotterAlgorithm(TrotterAlgorithm):
supported_types = {openfermion.DiagonalCoulombHamiltonian}
algorithm = EmptyTrotterAlgorithm()
with pytest.raises(ValueError):
_ = next(
simulate_trotter(qubits,
hamiltonian,
time,
order=0,
algorithm=algorithm))
with pytest.raises(ValueError):
_ = next(
simulate_trotter(qubits,
hamiltonian,
time,
order=1,
algorithm=algorithm))
with pytest.raises(ValueError):
_ = next(
simulate_trotter(qubits,
hamiltonian,
time,
order=0,
algorithm=algorithm,
control_qubit=control))
with pytest.raises(ValueError):
_ = next(
simulate_trotter(qubits,
hamiltonian,
time,
order=1,
algorithm=algorithm,
control_qubit=control))
if initial_guess_array is None:
# coverage: ignore
initial_guess_array = numpy.ones((3, black_box.dimension))
a = black_box.evaluate(initial_guess)
b = black_box.evaluate_with_cost(initial_guess_array[0], 1.0)
return OptimizationResult(optimal_value=min(a, b),
optimal_parameters=initial_guess,
num_evaluations=1,
cost_spent=0.0,
status=0,
message='success')
# Construct a Hamiltonian for testing
test_hamiltonian = random_diagonal_coulomb_hamiltonian(4,
real=True,
seed=26191)
test_fermion_op = openfermion.get_fermion_operator(test_hamiltonian)
def test_hamiltonian_variational_study_init_qubit_operator():
ansatz = SwapNetworkTrotterAnsatz(test_hamiltonian)
study = HamiltonianVariationalStudy('study', ansatz,
openfermion.QubitOperator((0, 'X')))
assert study.hamiltonian == openfermion.QubitOperator((0, 'X'))
def test_hamiltonian_variational_study_noise():
ansatz = SwapNetworkTrotterAnsatz(test_hamiltonian)
def test_divide(self):
n_qubits = 5
op1 = random_diagonal_coulomb_hamiltonian(n_qubits)
op2 = op1 / 1.5
self.assertEqual(get_fermion_operator(op1) / 1.5,
get_fermion_operator(op2))
def test_simulate_trotter_bad_order_raises_error():
qubits = cirq.LineQubit.range(2)
hamiltonian = random_diagonal_coulomb_hamiltonian(2, seed=0)
time = 1.0
with pytest.raises(ValueError):
_ = next(simulate_trotter(qubits, hamiltonian, time, order=-1))