def test_log_i(self):
""" MatrixOp.log_i() test """
op = (-1.052373245772859 * I ^ I) + \
(0.39793742484318045 * I ^ Z) + \
(0.18093119978423156 * X ^ X) + \
(-0.39793742484318045 * Z ^ I) + \
(-0.01128010425623538 * Z ^ Z) * np.pi/2
# Test with CircuitOp
log_exp_op = op.to_matrix_op().exp_i().log_i().to_pauli_op()
np.testing.assert_array_almost_equal(op.to_matrix(), log_exp_op.to_matrix())
# Test with MatrixOp
log_exp_op = op.to_matrix_op().exp_i().to_matrix_op().log_i().to_pauli_op()
np.testing.assert_array_almost_equal(op.to_matrix(), log_exp_op.to_matrix())
# Test with PauliOp
log_exp_op = op.to_matrix_op().exp_i().to_pauli_op().log_i().to_pauli_op()
np.testing.assert_array_almost_equal(op.to_matrix(), log_exp_op.to_matrix())
# Test with EvolvedOp
log_exp_op = op.exp_i().to_pauli_op().log_i().to_pauli_op()
np.testing.assert_array_almost_equal(op.to_matrix(), log_exp_op.to_matrix())
# Test with proper ListOp
op = ListOp([(0.39793742484318045 * I ^ Z),
(0.18093119978423156 * X ^ X),
(-0.39793742484318045 * Z ^ I),
(-0.01128010425623538 * Z ^ Z) * np.pi / 2])
log_exp_op = op.to_matrix_op().exp_i().to_matrix_op().log_i().to_pauli_op()
np.testing.assert_array_almost_equal(op.to_matrix(), log_exp_op.to_matrix())
def test_to_matrix_called(self):
"""test to matrix called in different situations"""
qs = 45
states_op = ListOp([Zero ^ qs, One ^ qs, (Zero ^ qs) + (One ^ qs)])
paulis_op = ListOp([Z ^ qs, (I ^ Z ^ I) ^ int(qs / 3)])
# 45 qubit calculation - throws exception if to_matrix is called
# massive is False
with self.assertRaises(ValueError):
states_op.to_matrix()
paulis_op.to_matrix()
# now set global variable or argument
try:
algorithm_globals.massive = True
with self.assertRaises(MemoryError):
states_op.to_matrix()
paulis_op.to_matrix()
algorithm_globals.massive = False
with self.assertRaises(MemoryError):
states_op.to_matrix(massive=True)
paulis_op.to_matrix(massive=True)
finally:
algorithm_globals.massive = False
