def test_apply_1q_random_ptm(self, state_cls, dm_basis, qubit):
unity = np.identity(2)
unitary = random_unitary_matrix(2, 45)
einsum_args = [unity, [0, 3], unity, [1, 4], unity, [2, 5]]
einsum_args[2 * qubit] = unitary
unitary3q = np.einsum(*einsum_args, optimize=True).reshape(8, 8)
dm_before = random_density_matrix(8, seed=46)
dm_after = unitary3q @ dm_before @ unitary3q.conj().T
assert dm_before.trace() == approx(1)
assert dm_after.trace() == approx(1)
b = (dm_basis(2), )
bases = b * 3
state0 = state_cls.from_dm(dm_before, bases)
state1 = state_cls.from_dm(dm_after, bases)
# sanity check
for q in range(3):
if q != qubit:
assert state0.meas_prob(q) == approx(state1.meas_prob(q))
else:
assert state0.meas_prob(q) != approx(state1.meas_prob(q))
ptm = kraus_to_ptm(unitary.reshape(1, 2, 2), b, b)
state0.apply_ptm(ptm, qubit)
assert state0.to_pv() == approx(state1.to_pv())
def test_apply_1q_random_ptm(self, state_cls, dm_basis, qubit):
unity = np.identity(2)
unitary = random_unitary_matrix(2, 45)
einsum_args = [unity, [0, 3], unity, [1, 4], unity, [2, 5]]
einsum_args[2*qubit] = unitary
unitary3q = np.einsum(*einsum_args, optimize=True).reshape(8, 8)
dm_before = random_density_matrix(8, seed=46)
dm_after = unitary3q @ dm_before @ unitary3q.conj().T
assert dm_before.trace() == approx(1)
assert dm_after.trace() == approx(1)
b = (dm_basis(2),)
bases = b * 3
state0 = state_cls.from_dm(dm_before, bases)
state1 = state_cls.from_dm(dm_after, bases)
# sanity check
for q in range(3):
if q != qubit:
assert state0.meas_prob(q) == approx(state1.meas_prob(q))
else:
assert state0.meas_prob(q) != approx(state1.meas_prob(q))
ptm = kraus_to_ptm(unitary.reshape(1, 2, 2), b, b)
state0.apply_ptm(ptm, qubit)
assert state0.to_pv() == approx(state1.to_pv())
def test_apply_1q_projecting_ptm(self, pauli_vector_cls, dm_basis, qubit):
unitary = random_unitary_matrix(2, 45)
b_in = (dm_basis(2), )
b_out = (dm_basis(2).subbasis([1]), )
bases = b_in * 3
dm_before = random_density_matrix(8, seed=46)
pv = pauli_vector_cls.from_dm(dm_before, bases)
pv_before = pv.to_pv()
ix_out = [0, 1, 2]
ix_out[qubit] = 3
ptm = kraus_to_ptm(unitary.reshape(1, 2, 2), b_in, b_out)
pv_ref = np.einsum(ptm, [3, qubit], pv_before, [0, 1, 2], ix_out)
pv.apply_ptm(ptm, qubit)
pv.to_pv() == approx(pv_ref)
def test_apply_random_ptm1q_state1q(self, state_cls, dm_basis):
unitary = random_unitary_matrix(2, 45)
dm_before = random_density_matrix(2, seed=256)
dm_after = unitary @ dm_before @ unitary.conj().T
assert dm_before.trace() == approx(1)
assert dm_after.trace() == approx(1)
b = (dm_basis(2), )
state0 = state_cls.from_dm(dm_before, b)
state1 = state_cls.from_dm(dm_after, b)
# sanity check
assert state0.meas_prob(0) != approx(state1.meas_prob(0))
ptm = kraus_to_ptm(unitary.reshape(1, 2, 2), b, b)
b_gm = (quantumsim.bases.gell_mann(2), )
ptm2 = ptm_convert_basis(ptm, b, b, b_gm, b_gm)
assert np.allclose(ptm2[0, 1:], 0)
assert ptm2[0, 0] == approx(1)
state0.apply_ptm(ptm, 0)
assert state0.to_pv() == approx(state1.to_pv())
def test_apply_random_ptm1q_state1q(self, state_cls, dm_basis):
unitary = random_unitary_matrix(2, 45)
dm_before = random_density_matrix(2, seed=256)
dm_after = unitary @ dm_before @ unitary.conj().T
assert dm_before.trace() == approx(1)
assert dm_after.trace() == approx(1)
b = (dm_basis(2),)
state0 = state_cls.from_dm(dm_before, b)
state1 = state_cls.from_dm(dm_after, b)
# sanity check
assert state0.meas_prob(0) != approx(state1.meas_prob(0))
ptm = kraus_to_ptm(unitary.reshape(1, 2, 2), b, b)
b_gm = (quantumsim.bases.gell_mann(2),)
ptm2 = ptm_convert_basis(ptm, b, b, b_gm, b_gm)
assert np.allclose(ptm2[0, 1:], 0)
assert ptm2[0, 0] == approx(1)
state0.apply_ptm(ptm, 0)
assert state0.to_pv() == approx(state1.to_pv())
def test_apply_2q_random_ptm(self, state_cls, dm_basis, qubits):
unity = np.identity(2)
unitary = random_unitary_matrix(4, 45).reshape(2, 2, 2, 2)
decay = np.array([[0.9, 0], [0, 0.7]])
op = decay @ unitary
q0, q1 = qubits
(q2, ) = tuple(q for q in range(3) if q not in qubits)
einsum_args = [op, [q0, q1, q0 + 3, q1 + 3], unity, [q2, q2 + 3]]
op3q = np.einsum(*einsum_args, optimize=True).reshape(8, 8)
dm_before = random_density_matrix(8, seed=46)
dm_after = op3q @ dm_before @ op3q.conj().T
assert dm_before.trace() == approx(1)
assert dm_after.trace() < 1.
b = (dm_basis(2), )
bases = b * 3
state0 = state_cls.from_dm(dm_before, bases)
state1 = state_cls.from_dm(dm_after, bases)
ptm = kraus_to_ptm(op.reshape(1, 4, 4), b * 2, b * 2)
state0.apply_ptm(ptm, *qubits)
assert state0.to_pv() == approx(state1.to_pv())
def test_apply_2q_random_ptm(self, state_cls, dm_basis, qubits):
unity = np.identity(2)
unitary = random_unitary_matrix(4, 45).reshape(2, 2, 2, 2)
decay = np.array([[0.9, 0], [0, 0.7]])
op = decay @ unitary
q0, q1 = qubits
(q2,) = tuple(q for q in range(3) if q not in qubits)
einsum_args = [op, [q0, q1, q0+3, q1+3], unity, [q2, q2+3]]
op3q = np.einsum(*einsum_args, optimize=True).reshape(8, 8)
dm_before = random_density_matrix(8, seed=46)
dm_after = op3q @ dm_before @ op3q.conj().T
assert dm_before.trace() == approx(1)
assert dm_after.trace() < 1.
b = (dm_basis(2),)
bases = b * 3
state0 = state_cls.from_dm(dm_before, bases)
state1 = state_cls.from_dm(dm_after, bases)
ptm = kraus_to_ptm(op.reshape(1, 4, 4), b * 2, b * 2)
state0.apply_ptm(ptm, *qubits)
assert state0.to_pv() == approx(state1.to_pv())