def test_density_angle() -> None:
rho0 = qf.random_density(1)
rho1 = qf.random_density(1)
qf.density_angle(rho0, rho1)
assert not qf.densities_close(rho0, rho1)
assert qf.densities_close(rho0, rho0)
def test_fidelity() -> None:
rho0 = qf.random_density(4)
rho1 = qf.random_density(4)
fid = qf.fidelity(rho0, rho1)
assert 0.0 <= fid <= 1.0
rho2 = qf.random_density([3, 2, 1, 0])
fid = qf.fidelity(rho0, rho2)
assert 0.0 <= fid <= 1.0
fid = qf.fidelity(rho0, rho0)
assert np.isclose(fid, 1.0)
ket0 = qf.random_state(3)
ket1 = qf.random_state(3)
fid0 = qf.state_fidelity(ket0, ket1)
rho0 = ket0.asdensity()
rho1 = ket1.asdensity()
fid1 = qf.fidelity(rho0, rho1)
assert np.isclose(fid1, fid0)
fid2 = np.cos(qf.fubini_study_angle(ket0.tensor, ket1.tensor)) ** 2
assert np.isclose(fid2, fid0)
def test_bures_distance(repeat: int) -> None:
rho = qf.random_density(4)
# Note ATOL. Sometimes does not give accurate answer
assert np.isclose(qf.bures_distance(rho, rho), 0.0, atol=ATOL * 100)
rho1 = qf.random_density(4)
qf.bures_distance(rho, rho1)
def test_fidelity():
rho0 = qf.random_density(4)
rho1 = qf.random_density(4)
fid = qf.fidelity(rho0, rho1)
print('FID', fid)
assert 0.0 <= fid <= 1.0
rho2 = qf.random_density([3, 2, 1, 0])
fid = qf.fidelity(rho0, rho2)
assert 0.0 <= fid <= 1.0
fid = qf.fidelity(rho0, rho0)
print('FID', fid)
assert fid == ALMOST_ONE
ket0 = qf.random_state(3)
ket1 = qf.random_state(3)
fid0 = qf.state_fidelity(ket0, ket1)
rho0 = ket0.asdensity()
rho1 = ket1.asdensity()
fid1 = qf.fidelity(rho0, rho1)
assert qf.asarray(fid1 - fid0) == ALMOST_ZERO
fid2 = bk.cos(qf.fubini_study_angle(ket0.vec, ket1.vec))**2
assert qf.asarray(fid2 - fid0) == ALMOST_ZERO
def test_random_density() -> None:
rho = qf.random_density(4)
assert list(rho.tensor.shape) == [2] * 8
rho1 = qf.random_density(4, rank=2, ensemble="Hilbert–Schmidt")
assert list(rho1.tensor.shape) == [2] * 8
rho2 = qf.random_density(4, rank=2, ensemble="Bures")
assert list(rho2.tensor.shape) == [2] * 8
with pytest.raises(ValueError):
qf.random_density(4, rank=2, ensemble="not_an_ensemble")
def test_identity():
chan = qf.identity_gate(1).aschannel()
rho = qf.random_density(2)
after = chan.evolve(rho)
assert qf.densities_close(rho, after)
assert chan.name == 'Channel'
def test_bures_angle():
rho = qf.random_density(4)
assert qf.bures_angle(rho, rho) == ALMOST_ZERO
rho1 = qf.random_density(4)
qf.bures_angle(rho, rho1)
ket0 = qf.random_state(4)
ket1 = qf.random_state(4)
rho0 = ket0.asdensity()
rho1 = ket1.asdensity()
ang0 = qf.fubini_study_angle(ket0.vec, ket1.vec)
ang1 = qf.bures_angle(rho0, rho1)
assert np.isclose(ang0, ang1)
def test_depolarizing() -> None:
p = 1.0 - np.exp(-1 / 20)
chan = qf.Depolarizing(p, 0).aschannel()
rho0 = qf.Density([[0.5, 0], [0, 0.5]])
assert qf.densities_close(rho0, chan.evolve(rho0))
rho0 = qf.random_density(1)
rho1 = chan.evolve(rho0)
pr0 = np.real(qf.purity(rho0))
pr1 = np.real(qf.purity(rho1))
assert pr0 > pr1
# Test data extracted from refereneqvm
rho2 = qf.Density([[0.43328691, 0.48979689], [0.48979689, 0.56671309]])
rho_test = qf.Density(
[[0.43762509 + 0.0j, 0.45794666 + 0.0j], [0.45794666 + 0.0j, 0.56237491 + 0.0j]]
)
assert qf.densities_close(chan.evolve(rho2), rho_test)
ket0 = qf.random_state(1)
qf.Depolarizing(p, 0).run(ket0)
rho1b = qf.Depolarizing(p, 0).evolve(rho0)
assert qf.densities_close(rho1, rho1b)
def test_identity() -> None:
chan = qf.IdentityGate([1]).aschannel()
rho = qf.random_density(2)
after = chan.evolve(rho)
assert qf.densities_close(rho, after)
assert chan.name == "Channel"
def test_bures_angle() -> None:
rho = qf.random_density(4)
assert np.isclose(qf.bures_angle(rho, rho), 0.0, atol=ATOL * 10)
rho1 = qf.random_density(4)
qf.bures_angle(rho, rho1)
ket0 = qf.random_state(4)
ket1 = qf.random_state(4)
rho0 = ket0.asdensity()
rho1 = ket1.asdensity()
ang0 = qf.fubini_study_angle(ket0.tensor, ket1.tensor)
ang1 = qf.bures_angle(rho0, rho1)
assert np.isclose(ang0, ang1)
def test_purity():
density = qf.ghz_state(4).asdensity()
assert qf.asarray(qf.purity(density)) == ALMOST_ONE
for _ in range(10):
rho = qf.random_density(4)
purity = np.real(qf.asarray(qf.purity(rho)))
assert purity < 1.0
assert purity >= 0.0
def test_density_trace():
rho = qf.random_density(3)
assert qf.asarray(rho.trace()) == ALMOST_ONE
rho = qf.Density(np.eye(8))
assert np.isclose(qf.asarray(rho.trace()), 8)
rho = rho.normalize()
assert np.isclose(qf.asarray(rho.trace()), 1)
def test_density_trace() -> None:
rho = qf.random_density(3)
assert np.isclose(rho.trace(), 1)
rho = qf.Density(np.eye(8))
assert np.isclose(rho.trace(), 8)
rho = rho.normalize()
assert np.isclose(rho.trace(), 1)
def test_purity() -> None:
density = qf.ghz_state(4).asdensity()
assert np.isclose(qf.purity(density), 1.0)
for _ in range(10):
rho = qf.random_density(4)
purity = np.real(qf.purity(rho))
assert purity < 1.0
assert purity >= 0.0
def test_gate_evolve(gatet: Type[qf.StdGate]) -> None:
gate0 = _randomize_gate(gatet)
gate1 = qf.Unitary(gate0.tensor, gate0.qubits)
rho = qf.random_density(gate0.qubits)
rho0 = gate0.evolve(rho)
rho1 = gate1.evolve(rho)
assert qf.densities_close(rho0, rho1)
def test_random_channel() -> None:
chan = qf.random_channel([0, 1, 2], rank=4)
rho0 = qf.random_density([0, 1, 2], rank=2)
purity0 = qf.purity(rho0)
rho1 = chan.evolve(rho0)
purity1 = qf.purity(rho1)
assert purity1 < purity0
chan = qf.random_channel([0, 1, 2], rank=4, unital=True)
assert qf.almost_unital(chan)
def test_purity() -> None:
density = qf.ghz_state(4).asdensity()
assert np.isclose(qf.purity(density), 1.0)
for _ in range(10):
density = qf.random_density(4)
purity = np.real(qf.purity(density))
assert purity < 1.0
assert purity >= 0.0
rho = qf.Density(np.diag([0.9, 0.1]))
assert np.isclose(qf.purity(rho), 0.82) # Kudos: Josh Combs
def test_purity():
density = qf.ghz_state(4).asdensity()
assert qf.asarray(qf.purity(density)) == ALMOST_ONE
for _ in range(10):
density = qf.random_density(4)
purity = np.real(qf.asarray(qf.purity(density)))
assert purity < 1.0
assert purity >= 0.0
rho = qf.Density(np.diag([0.9, 0.1]))
assert np.isclose(qf.asarray(qf.purity(rho)), 0.82) # Kudos: Josh Combes
def test_reset():
reset = qf.Reset(0, 1, 2)
with pytest.raises(TypeError):
reset.evolve(qf.random_density([0, 1, 3]))
with pytest.raises(TypeError):
reset.asgate()
with pytest.raises(TypeError):
reset.aschannel()
assert reset.H is reset
def test_reset() -> None:
reset = qf.Reset(0, 1, 2)
ket = qf.random_state([0, 1, 2, 3])
ket = reset.run(ket)
assert ket.tensor[1, 1, 0, 0] == 0.0
assert str(reset) == "Reset 0 1 2"
reset = qf.Reset()
ket = qf.random_state([0, 1, 2, 3])
ket = reset.run(ket)
assert qf.states_close(ket, qf.zero_state([0, 1, 2, 3]))
assert str(reset) == "Reset"
with pytest.raises(TypeError):
reset.evolve(qf.random_density([0, 1, 3]))
with pytest.raises(TypeError):
reset.asgate()
with pytest.raises(TypeError):
reset.aschannel()
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_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_bures_distance():
rho = qf.random_density(4)
assert qf.bures_distance(rho, rho) == ALMOST_ZERO
rho1 = qf.random_density(4)
qf.bures_distance(rho, rho1)
def test_trace_distance() -> None:
rho = qf.random_density(4)
assert np.isclose(qf.trace_distance(rho, rho), 0.0)
rho1 = qf.random_density(4)
qf.trace_distance(rho, rho1)
def test_random_density():
rho = qf.random_density(4)
assert list(rho.vec.asarray().shape) == [2] * 8
def test_random_density() -> None:
rho = qf.random_density(4)
assert rho.tensor.shape == (2,) * 8
