Example #1
0
def swap_map(x):
    base = (1j * x * swap()).expm()
    dims = [[[2], [2]], [[2], [2]]]
    return Qobj(base, dims=dims, type='super', superrep='super')
Example #2
0
from qutip.qip.operations import swap

from diamond import *
from qutip import *
from math import *

# Define gates for 2 diamond chip
# -- 1: z = π/2 -------- 2: z = π/3 ---
#
#       0:C1a                4:C1b
# 2:T1a  |    3:T2a –– 6:T1b  |    7:T2b
#       1:C2a                5:C2b
#
N = 2 * 4
U2 = lambda t: UN(t, t)
SWAP = swap(N, [3, 6])

init = ket('0' * 8)

entangling_opers = [{
    'oper': U2(π / 2) * X(N, 0) * U2(π / 2) * X(N, 1),
    'state': (ket('11000000') + zero8) / sqrt(2),
    'goal state': '1100 0000'
}, {
    'oper': U2(π / 2) * X(N, 4) * U2(π / 2) * X(N, 5),
    'state': (ket('00001100') + zero8) / sqrt(2),
    'goal state': '0000 1100'
}, {
    'oper': U2(π / 2) * X(N, 2) * U2(π / 2) * X(N, 3),
    'state': (ket('00110000') + zero8) / sqrt(2),
    'goal state': '0011 0000'
Example #3
0
 def __init__(self):
     # We start out with all zeros |0000>
     self._dm = sp.ImmutableDenseMatrix([[1] + [0] * (2**4 - 1),
                                         *([[0] * (2**4)] * (2**4 - 1))])
     self._swap_matrix = swap(4, [1, 2])
Example #4
0
                                 [x3 * sp.exp(1j * phi3)],
                                 [x4 * sp.exp(1j * phi4)]])

ws = sp.symbols('w:2:2', real=True, nonnegative=True)
omegas = sp.symbols('omega:2:2', real=True)
ws_conj = (sp.conjugate(w) for w in ws)
w1, w2, w3, w4 = ws
_, omega2, omega3, omega4 = omegas
init_w_state = sp.ImmutableDenseMatrix([[w1], [w2 * sp.exp(1j * omega2)],
                                        [w3 * sp.exp(1j * omega3)],
                                        [w4 * sp.exp(1j * omega4)]])
xs2_sum = sum([1.0 * xs[i]**2 for i in range(4)])
ws2_sum = sum([1.0 * ws[i]**2 for i in range(4)])

state = sp.kronecker_product(state, init_w_state)
state = swap(4, [1, 2]) @ state
norm_factor = normalization_factor(state)
state2_sum = 1 / norm_factor**2
# state = norm_factor * state
# state = normalize_state(state)
state = Ut @ state
state = state.subs(1.0, 1).expand(basic=True, complex=True).simplify()

dm = density_matrix(
    state)  #.subs(xs[0]*sp.conjugate(xs[0]), sp.abs xs[0].norm()**2)
# Measurement of C2
dm_C2 = partial_trace(dm, 4, [0, 2, 3])
P0_C2 = dm_C2[0, 0].simplify()
P1_C2 = dm_C2[1, 1].simplify()
P01_C2 = (P0_C2 + P1_C2).simplify()
# Measurement of T2