def test_matvec_0(self):
"""Testing with zero term."""
qubit_operator = QubitOperator.zero()
vec = numpy.array([1, 2, 3, 4, 5, 6, 7, 8])
matvec_expected = numpy.zeros(vec.shape)
self.assertTrue(
numpy.allclose(
LinearQubitOperator(qubit_operator, 3) * vec, matvec_expected))
def test_get_lowest_n(self):
"""Test for get_lowest_n()."""
dimension = 2**self.n_qubits
qubit_operator = QubitOperator.zero()
for i in range(min(self.n_qubits, 4)):
numpy.random.seed(dimension + i)
qubit_operator += QubitOperator(((i, 'Z'), ),
numpy.random.rand(1)[0])
qubit_operator *= self.coefficient
davidson = QubitDavidson(qubit_operator, self.n_qubits)
n_lowest = 6
numpy.random.seed(dimension)
initial_guess = numpy.random.rand(dimension, n_lowest)
success, eigen_values, eigen_vectors = davidson.get_lowest_n(
n_lowest, initial_guess, max_iterations=20)
expected_eigen_values = -3.80376934 * numpy.ones(n_lowest)
self.assertTrue(success)
self.assertTrue(numpy.allclose(eigen_values, expected_eigen_values))
self.assertAlmostEqual(
get_difference(davidson.linear_operator, eigen_values,
eigen_vectors), 0)
