def test_zero_basis(self):
ARMAs = [SchWARMA.ARMA([.5, .25], [1])]
ARMAs.append(SchWARMA.ARMA([], [1]))
D = {'I': ch.QuantumChannel(np.array(np.eye(4, dtype=complex)))}
sch = SchWARMA.SchWARMA(ARMAs, [s_z, np.zeros((8, 2))], D)
self.assertEqual(sch.N, 2)
self.assertTrue(all([b.shape == (8, 8) for b in sch.basis]))
self.assertEqual(la.norm(1j * s_z - sch.basis[0][:2, :2]), 0)
self.assertEqual(la.norm(sch.basis[0][2:, :]), 0)
self.assertEqual(la.norm(sch.basis[0][:, 2:]), 0)
out = sch['I']
self.assertEqual(out.rank(), 1)
self.assertEqual(out.chi()[1, 1], 0)
self.assertEqual(out.chi()[2, 2], 0)
avg = ch.QuantumChannel(
np.mean([sch['I'].choi() for _ in range(3)], 0), 'choi')
self.assertEqual(avg.rank(), 2)
self.assertEqual(avg.chi()[1, 1], 0)
self.assertEqual(avg.chi()[2, 2], 0)
def test_hamiltonian_basis(self):
ARMAs = [SchWARMA.ARMA([.5, .25], [1])]
ARMAs.append(SchWARMA.ARMA([], [1]))
ARMAs.append(SchWARMA.ARMA([], [1, 1, 1]))
D = {'I': ch.QuantumChannel(np.array(np.eye(4, dtype=complex)))}
sch = SchWARMA.SchWARMA(ARMAs, [s_x, s_y, s_z], D)
self.assertTrue(
all([la.norm(b + b.conj().T < 1e-9) for b in sch.basis]))
def test_zero_basis(self):
ARMAs = [SchWARMA.ARMA([.5, .25], [1])]
ARMAs.append(SchWARMA.ARMA([], [1]))
D = {'I': ch.QuantumChannel(np.array(np.eye(4, dtype=complex)))}
sch = SchWARMA.SchWARMA(ARMAs, [np.zeros((8, 2)), np.zeros((2, 2))], D)
self.assertEqual(sch.N, 2)
self.assertTrue(all([b.shape == (8, 8) for b in sch.basis]))
self.assertEqual(la.norm(sch['I'].liouvillian() - np.eye(4)), 0)
def test_no_SchWARMA(self):
ARMAs = [SchWARMA.ARMA([], [0])]
ARMAs.append(SchWARMA.ARMA([], [0]))
ARMAs.append(SchWARMA.ARMA([], [0]))
D = {
'I': ch.QuantumChannel(np.array(np.eye(4, dtype=complex))),
'X': ch.QuantumChannel(np.kron(s_x.conj(), s_x))
}
sch = SchWARMA.SchWARMA(ARMAs, [s_x, s_y, s_z], D)
sch.init_ARMAs
self.assertEqual(la.norm(D['I'].choi() - sch['I'].choi()), 0)
self.assertEqual(la.norm(D['X'].choi() - sch['X'].choi()), 0)
def test_mixed_basis(self):
ARMAs = [SchWARMA.ARMA([.5, .25], [1])]
ARMAs.append(SchWARMA.ARMA([], [1]))
ARMAs.append(SchWARMA.ARMA([], [1, 1, 1]))
D = {
'I': ch.QuantumChannel(np.array(np.eye(4, dtype=complex))),
'X': ch.QuantumChannel(np.kron(s_x.conj(), s_x))
}
ad = np.zeros((4, 2), dtype=complex)
ad[2, 1] = .1
sch = SchWARMA.SchWARMA(ARMAs, [s_x, 1j * s_y, ad], D)
self.assertEqual(sch.N, 2)
self.assertTrue(
all([la.norm(b + b.conj().T < 1e-9) for b in sch.basis]))
def test_bad_init(self):
ARMAS = [
SchWARMA.ARMA(np.random.randn(1),
np.random.randn(np.random.randint(5)) + 2)
for _ in range(3)
]
D = {'I': ch.QuantumChannel(np.array(np.eye(4, dtype=complex)))}
self.assertRaises(AssertionError, SchWARMA.SchWMA,
*[ARMAS, [s_x, s_y, s_z], D])
def test_init(self):
ARMAS = [
SchWARMA.ARMA([],
np.random.randn(np.random.randint(5)) + 2)
for _ in range(3)
]
D = {'I': ch.QuantumChannel(np.array(np.eye(4, dtype=complex)))}
MA = SchWARMA.SchWMA(ARMAS, [s_x, s_y, s_z], D)
def test_init(self):
ARMAs = [SchWARMA.ARMA([.5, .25], [1])]
ARMAs.append(SchWARMA.ARMA([], [1]))
ARMAs.append(SchWARMA.ARMA([], [1, 1, 1]))
D = {'I': ch.QuantumChannel(np.array(np.eye(4, dtype=complex)))}
sch = SchWARMA.SchWARMA(ARMAs, [s_x, s_y, s_z], D)
xs = [copy.copy(model.x) for model in sch.models]
ys = [copy.copy(model.y) for model in sch.models]
sch.init_ARMAs()
xs2 = [copy.copy(model.x) for model in sch.models]
ys2 = [copy.copy(model.y) for model in sch.models]
xdiff = np.array([la.norm(x - xx) for x, xx in zip(xs, xs2)])
ydiff = np.array([la.norm(yy) for y, yy in zip(ys, ys2)])
self.assertTrue(np.all(xdiff > 0))
self.assertTrue(np.all(ydiff == 0))