def test_kraus_qubits() -> None:
kraus = qf.Kraus([qf.X(1), qf.Y(0)])
assert kraus.qubits == (0, 1)
kraus = qf.Kraus([qf.X("a"), qf.Y("b")])
assert len(kraus.qubits) == 2
assert kraus.qubit_nb == 2
def test_kraus_qubits():
kraus = qf.Kraus([qf.X(1), qf.Y(0)])
assert kraus.qubits == (0, 1)
kraus = qf.Kraus([qf.X('a'), qf.Y('b')])
assert len(kraus.qubits) == 2
assert kraus.qubit_nb == 2
def test_measurement():
rho = qf.zero_state(2).asdensity()
chan = qf.H(0).aschannel()
rho = chan.evolve(rho)
rho = qf.Kraus([qf.P0(0), qf.P1(0)]).aschannel().evolve(rho)
K = qf.Kraus([qf.P0(1), qf.P1(1)])
chan = K.aschannel()
rho = qf.Kraus([qf.P0(1), qf.P1(1)]).aschannel().evolve(rho)
prob = qf.asarray(rho.probabilities())
assert np.allclose(prob, [[0.5, 0], [0.5, 0]])
assert prob[0, 0] * 2 == ALMOST_ONE
assert prob[1, 0] * 2 == ALMOST_ONE
def test_measurement() -> None:
rho = qf.zero_state(2).asdensity()
chan = qf.H(0).aschannel()
rho = chan.evolve(rho)
rho = qf.Kraus([qf.P0(0), qf.P1(0)]).aschannel().evolve(rho)
K = qf.Kraus([qf.P0(1), qf.P1(1)])
_ = K.aschannel()
rho = qf.Kraus([qf.P0(1), qf.P1(1)]).aschannel().evolve(rho)
prob = rho.probabilities()
assert np.allclose(prob, [[0.5, 0], [0.5, 0]])
assert np.isclose(prob[0, 0] * 2, 1.0)
assert np.isclose(prob[1, 0] * 2, 1.0)
def test_kraus_complete():
kraus = qf.Kraus([qf.X(1)])
assert qf.kraus_iscomplete(kraus)
kraus = qf.Damping(0.1, 0)
assert qf.kraus_iscomplete(kraus)
assert qf.kraus_iscomplete(qf.Damping(0.1, 0))
assert qf.kraus_iscomplete(qf.Dephasing(0.1, 0))
assert qf.kraus_iscomplete(qf.Depolarizing(0.1, 0))
def test_askraus():
def _roundtrip(kraus):
assert qf.kraus_iscomplete(kraus)
chan0 = kraus.aschannel()
kraus1 = qf.channel_to_kraus(chan0)
assert qf.kraus_iscomplete(kraus1)
chan1 = kraus1.aschannel()
assert qf.channels_close(chan0, chan1)
p = 1 - np.exp(-50 / 15000)
_roundtrip(qf.Kraus([qf.X(1)]))
_roundtrip(qf.Damping(p, 0))
_roundtrip(qf.Depolarizing(0.9, 1))
def test_transpose_map():
# The transpose map is a superoperator that transposes a 1-qubit
# density matrix. Not physical.
# quant-ph/0202124
ops = [
qf.Gate(np.asarray([[1, 0], [0, 0]])),
qf.Gate(np.asarray([[0, 0], [0, 1]])),
qf.Gate(np.asarray([[0, 1], [1, 0]]) / np.sqrt(2)),
qf.Gate(np.asarray([[0, 1], [-1, 0]]) / np.sqrt(2))
]
kraus = qf.Kraus(ops, weights=(1, 1, 1, -1))
rho0 = qf.random_density(1)
rho1 = kraus.evolve(rho0)
op0 = qf.asarray(rho0.asoperator())
op1 = qf.asarray(rho1.asoperator())
assert np.allclose(op0.T, op1)
# The Choi matrix should be same as SWAP operator
choi = kraus.aschannel().choi()
choi = qf.asarray(choi)
assert np.allclose(choi, qf.asarray(qf.SWAP(0, 2).asoperator()))
def test_transpose_map() -> None:
# The transpose map is a superoperator that transposes a 1-qubit
# density matrix. Not physical.
# quant-ph/0202124
q0 = 0
ops = [
qf.Unitary(np.asarray([[1, 0], [0, 0]]), [q0]),
qf.Unitary(np.asarray([[0, 0], [0, 1]]), [q0]),
qf.Unitary(np.asarray([[0, 1], [1, 0]]) / np.sqrt(2), [q0]),
qf.Unitary(np.asarray([[0, 1], [-1, 0]]) / np.sqrt(2), [q0]),
]
kraus = qf.Kraus(ops, weights=(1, 1, 1, -1))
rho0 = qf.random_density(1)
rho1 = kraus.evolve(rho0)
op0 = rho0.asoperator()
op1 = rho1.asoperator()
assert np.allclose(op0.T, op1)
# The Choi matrix should be same as Swap operator
choi = kraus.aschannel().choi()
assert np.allclose(choi, qf.Swap(0, 2).asoperator())
def test_kraus_errors():
kraus = qf.Kraus([qf.X(1), qf.Y(0)])
with pytest.raises(TypeError):
kraus.asgate()
def test_chan_qubits():
chan = qf.Kraus([qf.X(1), qf.Y(0)]).aschannel()
assert chan.qubits == (0, 1)
assert chan.qubit_nb == 2
def test_kruas_qubits():
rho = qf.Kraus([qf.P0(0), qf.P1(1)])
assert rho.qubits == (0, 1)
assert rho.qubit_nb == 2
