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_channel_adjoint():
kraus0 = qf.Damping(0.1, 0)
chan0 = kraus0.aschannel()
chan1 = chan0.H.H
assert qf.channels_close(chan0, chan1)
chan2 = kraus0.H.aschannel()
assert qf.channels_close(chan2, chan0.H)
# 2 qubit hermitian channel
chan3 = qf.CZ(0, 1).aschannel()
chan4 = chan3.H
assert qf.channels_close(chan3, chan4)
def test_amplitude_damping():
rho = qf.zero_state(1).asdensity()
p = 1.0 - np.exp(-(50) / 15000)
chan = qf.Damping(p, 0).aschannel()
rho1 = chan.evolve(rho)
assert qf.densities_close(rho, rho1)
rho2 = qf.X(0).aschannel().evolve(rho1)
rho3 = chan.evolve(rho2)
expected = qf.Density([[0.00332778 + 0.j, 0.00000000 + 0.j],
[0.00000000 + 0.j, 0.99667222 + 0.j]])
assert qf.densities_close(expected, rho3)
def test_kraus_evolve():
rho = qf.zero_state(1).asdensity()
p = 1 - np.exp(-50 / 15000)
kraus = qf.Damping(p, 0)
rho1 = kraus.evolve(rho)
assert qf.densities_close(rho, rho1)
rho2 = qf.X(0).aschannel().evolve(rho1)
rho3 = kraus.evolve(rho2)
expected = qf.Density([[0.00332778 + 0.j, 0.00000000 + 0.j],
[0.00000000 + 0.j, 0.99667222 + 0.j]])
assert qf.densities_close(expected, rho3)
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_kraus_run():
ket0 = qf.zero_state(['a'])
ket0 = qf.X('a').run(ket0)
p = 1.0 - np.exp(-2000 / 15000)
kraus = qf.Damping(p, 'a')
reps = 1000
results = [kraus.run(ket0).asdensity().asoperator() for _ in range(reps)]
matrix = reduce(add, results) / reps
rho_kraus = qf.Density(matrix, ['a'])
rho0 = ket0.asdensity()
chan = kraus.aschannel()
rho_chan = chan.evolve(rho0)
# If this fails occasionally consider increasing tolerance
# Can't be very tolerant due to stochastic dynamics
assert qf.densities_close(rho_chan, rho_kraus, tolerance=0.05)
def test_stdchannels_creation():
qf.Damping(0.1, 0).aschannel()
qf.Depolarizing(0.1, 0).aschannel()
qf.Dephasing(0.1, 0).aschannel()
def test_stdkraus_creation():
qf.Damping(0.1, 0)
qf.Depolarizing(0.1, 0)
qf.Dephasing(0.1, 0)
def test_channle_choi() -> None:
chan0 = qf.Damping(0.1, 0).aschannel()
choi = chan0.choi()
chan1 = qf.Channel.from_choi(choi, [0])
assert qf.channels_close(chan0, chan1)
def test_average_gate_fidelity() -> None:
kraus = qf.Damping(0.9, q0=0)
qf.average_gate_fidelity(kraus)
qf.average_gate_fidelity(kraus, qf.X(0))
