def test_pauli_cob_traverse(self):
"""pauli cob traverse test"""
# Helpful prints for debugging commented out below.
multis = [(X ^ Y) + (I ^ Z) + (Z ^ Z),
(Y ^ X ^ I ^ I) + (I ^ Z ^ Y ^ X)]
dests = [Y ^ Y, I ^ I ^ I ^ Z]
for paulis, dest in zip(multis, dests):
converter = PauliBasisChange(destination_basis=dest, traverse=True)
cob = converter.convert(paulis)
self.assertIsInstance(cob, SummedOp)
inst = [None] * len(paulis)
ret_dest = [None] * len(paulis)
cob_mat = [None] * len(paulis)
for i, pauli in enumerate(paulis):
inst[i], ret_dest[i] = converter.get_cob_circuit(
pauli.to_pauli_op().primitive)
self.assertEqual(dest, ret_dest[i])
self.assertIsInstance(cob.oplist[i], ComposedOp)
cob_mat[i] = cob.oplist[i].to_matrix()
np.testing.assert_array_almost_equal(pauli.to_matrix(),
cob_mat[i])
np.testing.assert_array_almost_equal(paulis.to_matrix(),
sum(cob_mat))
def test_pauli_cob_multiqubit(self):
"""pauli cob multi qubit test"""
# Helpful prints for debugging commented out below.
multis = [
Y ^ X ^ I ^ I, I ^ Z ^ Y ^ X, X ^ Y ^ I ^ Z, I ^ I ^ I ^ X,
X ^ X ^ X ^ X
]
for pauli, dest in itertools.product(multis, reversed(multis)):
# print(pauli)
# print(dest)
converter = PauliBasisChange(destination_basis=dest)
inst, dest = converter.get_cob_circuit(pauli.primitive)
cob = converter.convert(pauli)
# print(inst)
# print(pauli.to_matrix())
# print(np.round(inst.adjoint().to_matrix() @ cob.to_matrix()))
np.testing.assert_array_almost_equal(
pauli.to_matrix(),
inst.adjoint().to_matrix() @ dest.to_matrix()
@ inst.to_matrix())
np.testing.assert_array_almost_equal(pauli.to_matrix(),
cob.to_matrix())
np.testing.assert_array_almost_equal(
inst.compose(pauli).compose(inst.adjoint()).to_matrix(),
dest.to_matrix())
def test_grouped_pauli_statefn(self):
"""grouped pauli test with statefn"""
grouped_pauli = PauliSumOp(SparsePauliOp(["Y"]), grouping_type="TPB")
observable = OperatorStateFn(grouped_pauli, is_measurement=True)
converter = PauliBasisChange(
replacement_fn=PauliBasisChange.measurement_replacement_fn)
cob = converter.convert(observable)
expected = PauliSumOp(SparsePauliOp(["Z"]), grouping_type="TPB")
self.assertEqual(cob[0].primitive, expected)
circuit = QuantumCircuit(1)
circuit.sdg(0)
circuit.h(0)
self.assertEqual(cob[1].primitive, circuit)
def test_pauli_cob_two_qubit(self):
"""pauli cob two qubit test"""
multis = [Y ^ X, Z ^ Y, I ^ Z, Z ^ I, X ^ X, I ^ X]
for pauli, dest in itertools.product(multis, reversed(multis)):
converter = PauliBasisChange(destination_basis=dest)
inst, dest = converter.get_cob_circuit(pauli.primitive)
cob = converter.convert(pauli)
np.testing.assert_array_almost_equal(
pauli.to_matrix(),
inst.adjoint().to_matrix() @ dest.to_matrix()
@ inst.to_matrix())
np.testing.assert_array_almost_equal(pauli.to_matrix(),
cob.to_matrix())
np.testing.assert_array_almost_equal(
inst.compose(pauli).compose(inst.adjoint()).to_matrix(),
dest.to_matrix())
def test_pauli_cob_singles(self):
"""from to file test"""
singles = [X, Y, Z]
dests = [None, Y]
for pauli, dest in itertools.product(singles, dests):
# print(pauli)
converter = PauliBasisChange(destination_basis=dest)
inst, dest = converter.get_cob_circuit(pauli.primitive)
cob = converter.convert(pauli)
np.testing.assert_array_almost_equal(
pauli.to_matrix(),
inst.adjoint().to_matrix() @ dest.to_matrix()
@ inst.to_matrix())
np.testing.assert_array_almost_equal(pauli.to_matrix(),
cob.to_matrix())
np.testing.assert_array_almost_equal(
inst.compose(pauli).compose(inst.adjoint()).to_matrix(),
dest.to_matrix())
def test_grouped_pauli(self):
"""grouped pauli test"""
pauli = 2 * (I ^ I) + (X ^ I) + 3 * (X ^ Y)
grouped_pauli = PauliSumOp(pauli.primitive, grouping_type="TPB")
converter = PauliBasisChange()
cob = converter.convert(grouped_pauli)
np.testing.assert_array_almost_equal(pauli.to_matrix(),
cob.to_matrix())
origin_x = reduce(np.logical_or, pauli.primitive.table.X)
origin_z = reduce(np.logical_or, pauli.primitive.table.Z)
origin_pauli = Pauli((origin_z, origin_x))
inst, dest = converter.get_cob_circuit(origin_pauli)
self.assertEqual(str(dest), "ZZ")
expected_inst = np.array([
[0.5, -0.5j, 0.5, -0.5j],
[0.5, 0.5j, 0.5, 0.5j],
[0.5, -0.5j, -0.5, 0.5j],
[0.5, 0.5j, -0.5, -0.5j],
])
np.testing.assert_array_almost_equal(inst.to_matrix(), expected_inst)