def continuousTeleportationSimulation(psi, c_ops=[]):
N = 8
psi0 = tensor([basis(2, 0), psi] + [basis(2, 0) for i in range(N - 2)])
schedule = []
# encoding, Hadamards stage 1, 2
schedule.append((constructHadamardH(N, range(N)),
constructHadamardCorr(N, range(N)), np.pi))
# encoding, CZs, stage 3
schedule.append((constructCZH(N, [0, 2, 4], [1, 3, 5]), None, np.pi))
# encoding, Hadamards, stage 4, 5
schedule.append((constructHadamardH(N, [1, 3, 5]),
constructHadamardCorr(N, [1, 3, 5]), np.pi))
# teleportation, stage 6
schedule.append((osum([Sy(N, i) for i in [1, 2, 3, 4]]), None, np.pi / 2.))
# teleportation, stage 7
schedule.append(
(osum([Sz(N, i) for i in [1, 2, 3, 4]]), None, -np.pi / 2.))
# teleportation, stage 8
schedule.append((constructCZH(N, [1, 3], [2, 4]), None, np.pi))
# teleportation, stage 9
schedule.append(
(osum([Sy(N, i) for i in [1, 2, 3, 4]]), None, -np.pi / 2.))
# decoding, stage 10, 11
schedule.append(
(constructHadamardH(N, [1, 3]), constructHadamardCorr(N,
[1, 3]), np.pi))
# decoding, stage 12
schedule.append((constructCZH(N, [0, 2], [1, 3]), None, np.pi))
# decoding, stage 13, 14
schedule.append((constructHadamardH(N, [0, 1, 2, 3]),
constructHadamardCorr(N, [0, 1, 2, 3]), np.pi))
# perform time evolution and return the final state
return scheduledTimeEvolution(psi0, schedule, c_ops=c_ops)
def continuousDecodingSimulation(psi0, c_ops=[]):
N = 8
schedule = []
# decoding, stage 1, 2
schedule.append(
(constructHadamardH(N, [5, 7]), constructHadamardCorr(N,
[5, 7]), np.pi))
# decoding, stage 3
schedule.append((constructCZH(N, [4, 6], [5, 7]), None, np.pi))
# decoding, stage 4, 5
schedule.append((constructHadamardH(N, [4, 5, 6]),
constructHadamardCorr(N, [4, 5, 6]), np.pi))
return scheduledTimeEvolution(psi0, schedule, c_ops=c_ops)
def testHadamardUnitary(self):
H = constructHadamardH(1, [0])
U = snot()
U2 = deriveUnitary(H, np.pi)
Ucorr = constructHadamardCorr(1, [0])
assert Ucorr*U2 == U
assert H.isherm
def testHadamardUnitaryMulti(self):
H = constructHadamardH(2, [0, 1])
UH1 = snot(N=2, target=0)
UH2 = snot(N=2, target=1)
U2 = deriveUnitary(H, np.pi)
Ucorr = constructHadamardCorr(2, [0, 1])
assert Ucorr*U2 == UH1*UH2
assert H.isherm
def testHadamardHamiltonian(self):
t = np.pi
H = constructHadamardH(1, [0])
U = snot()
Ucorr = constructHadamardCorr(1, [0])
for psi0 in [z0, z1, xp, xm, yp, ym, rand_ket(2)]:
psiu = U*psi0
psif = evolve(H, t/2., psi0)
psic = Ucorr*psif
overl = psiu.overlap(psic)
assert are_close(overl, 1.)
assert H.isherm