def stringent():
err_model = cc.ErrorModel(0.1, 0.0075, 0.0075)
ρ0 = bosonic_bell_pair([0, 3])
ρ1 = cc.make_bell_with(ρ0, err_model, True, False)
ρ1.print()
ρ = cc.make_GHZ_with(ρ1, err_model, True, False)
return ρ
def stringent():
err_model = cc.ErrorModel(0.1, 0.0075, 0.0075)
bell_operator = np.array([[0.4972, 0, 0,
0.4953], [0, 0.002758, 0.001367, 0],
[0, 0.001367, 0.002758, 0],
[0.4953, 0, 0, 0.4972]])
ρ1 = cc.DensityOperator([0, 3], bell_operator)
ρ1 = cc.make_bell(err_model, True, False)
ρ1.print()
ρ = cc.make_GHZ_with(ρ1, err_model, True, False)
return ρ
def expedient():
err_model = cc.ErrorModel(0.1, 0.006, 0.006)
bell_operator = np.array([[0.4978, 0, 0,
0.4962], [0, 0.002229, 0.001136, 0],
[0, 0.001136, 0.002229, 0],
[0.4962, 0, 0, 0.4978]])
ρ1 = cc.DensityOperator([0, 3], bell_operator)
# ρ1 = cc.make_bell(err_model, True, False)
# ρ1.print()
ρ = cc.make_GHZ_with(ρ1, err_model, False, False)
return ρ
def custom(p, stringent):
err_model = cc.ErrorModel(0.1, p, p)
ρ1 = cc.make_bell(err_model, stringent, False)
# ρ1.print()
ρ = cc.make_GHZ_with(ρ1, err_model, stringent, False)
result_correct, result_error = cc.get_result(ρ.operator, err_model)
with open('data/custom_result.npz', 'wb') as f:
np.savez(f, result_correct, result_error)
np.set_printoptions(suppress=True)
r1 = result_correct.reshape((1, -1))[0]
r2 = result_error.reshape((1, -1))[0]
print(r1)
print(r2)
return ρ
def test_BBPSSW_2(p_n=0.1):
err_model = cc.ErrorModel(p_n)
# perfect_bell = cc.bell_pair([0, 1])
perfect_bell = cc.bell_pair(0, [0, 1])
noise_bell = cc.bell_pair(err_model.p_n, [0, 1])
ρ = cc.BBPSSW_2(err_model, True)
# f1 is just 1 - p_n
f1 = cc.entanglement_fidelity(noise_bell, perfect_bell)
f2 = cc.entanglement_fidelity(ρ, perfect_bell)
p_theory = (f1**2 + 2 * f1 * (1 - f1) / 3 + 5 * ((1 - f1) / 3)**2)
f_theory = (f1**2 + ((1 - f1) / 3)**2) / p_theory
print("no purification: ", f1)
print("after purification: ", f2)
print("fidelity in theory: ", f_theory)
print("success probability in theory: ", p_theory)
def expedient(p = 0.006):
err_model = cc.ErrorModel(0.1, p, p)jjk
# [[0.4915 0 0 0.486]
# [ 0 0.008491 0.007086 0]
# [ 0 0.007086 0.008491 0]
# [ 0.486 0 0 0.4915]]
# [[0.49150882 0 0 0.48603865]
# [ 0 0.0084911765 0.0070856237 0]
# [ 0 0.0070856237 0.0084911765 0]
# [0.48603865 0 0 0.49150882]]
ρ0 = bosonic_bell_pair([0, 3])
ρ1 = cc.make_bell_with(ρ0, err_model, False, False)
ρ1.print()
ρ = cc.make_GHZ_with(ρ1, err_model, False, False)
return ρ
def test_BBPSSW(p_n=0.1):
np.set_printoptions(edgeitems=16,
linewidth=200,
formatter=dict(float=lambda x: "%8.4g" % x))
err_model = cc.ErrorModel(p_n)
perfect_bell = cc.BBPSSW_bell_pair([0, 1])
noise_bell = cc.BBPSSW_bell_pair([0, 1], err_model.p_n)
ρ = cc.BBPSSW(err_model, True)
# f1 is just 1 - p_n
f1 = cc.entanglement_fidelity(noise_bell, perfect_bell)
f2 = cc.entanglement_fidelity(ρ, perfect_bell)
p_theory = (f1**2 + 2 * f1 * (1 - f1) / 3 + 5 * ((1 - f1) / 3)**2)
f_theory = (f1**2 + ((1 - f1) / 3)**2) / p_theory
print("no purification: ", f1)
print("after purification: ", f2)
print("fidelity in theory: ", f_theory)
print("success probability in theory: ", p_theory)
def test_1():
err_model = cc.ErrorModel()
ρ1 = cc.bell_pair(err_model.p_n, [1, 3])
ρ2 = cc.bell_pair(err_model.p_n, [2, 4])
# ρ1.print()
# print(ρ1.operator.trace())
ρ1.merge(ρ2)
# ρ1.print()
print("trace of ρ1", ρ1.operator.trace())
# ρ1.print()
c1 = cc.cphase([2, 1])
c2 = cc.cphase([4, 3])
ρ1.evolution(c1)
ρ1.evolution(c2)
print("trace of ρ1", ρ1.operator.trace())
ρ1.bell_measure(2, 4, 'z', 'z')
ρ1.print()
return ρ1
# print(probs)
print("sum", np.sum(probs))
print("trace", mat.trace())
c_correct = np.zeros((4, 4, 4, 4))
c_error = np.zeros((4, 4, 4, 4))
for (i, ps) in enumerate(probs):
_c_correct, _c_error = get_pair_result_1(err_model, ps[0], ps[1], i)
c_correct += _c_correct
c_error += _c_error
return c_correct, c_error
# _pair_result_1(cc.ErrorModel(0.1, 0.0075, 0.0075), p)air_result_1(cc.ErrorModel(0.1, 0.0075, 0.0075), p)
# p = 0.9535
c_correct1, c_error1 = get_result(GHZ_expedient,
cc.ErrorModel(0.1, 0.006, 0.006))
with open('data/expedient_GHZ.npy', 'wb') as f:
np.save(f, GHZ_expedient, False)
with open('data/expedient_result_correct.npy', 'wb') as f:
np.save(f, c_correct1, False)
with open('data/expedient_result_error.npy', 'wb') as f:
np.save(f, c_error1, False)
c_correct2, c_error2 = get_result(GHZ_stringent,
cc.ErrorModel(0.1, 0.0075, 0.0075))
with open('data/stringent_GHZ.npy', 'wb') as f:
np.save(f, GHZ_stringent, False)
if __name__ == "__main__":
np.set_printoptions(edgeitems=16, linewidth=200,
formatter=dict(float=lambda x: "%6.4g" % x)
)
# ρ = expedient()
# ρ = stringent()
GHZ_perfect = np.array([1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1])
GHZ_perfect = np.outer(GHZ_perfect, GHZ_perfect) / 2
GHZ_perfect = cc.DensityOperator([0, 3, 6, 9], GHZ_perfect)
ps = np.arange(0.002, 0.004, 0.00025)
results_c = []
results_e = []
for p in ps:
print("running probs ", p)
error_model = cc.ErrorModel(1, p, p)
ρ1 = cc.make_bell(error_model, False, False)
ρ1.print()
ρ = cc.make_GHZ_with(ρ1, error_model, False, False)
result_correct, result_error = cc.get_result(ρ.operator, error_model)
print(cc.entanglement_fidelity(ρ, GHZ_perfect))
ρ.print()
results_c.append(result_correct)
results_e.append(result_error)
for i in range(len(ps)):
print(ps[i], " : ", results_c[i][0, 0, 0, 0], " ", results_e[i][0, 0, 0, 0])
with open('data/scan_result.npz', 'wb') as f:
np.savez(f, results_c, results_e)
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], # 1
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], # 2
[0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # 3
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], # 4
[0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0], # 5
[0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0], # 6
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], # 7
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], # 8
[0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0], # 9
[0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0], # 10
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], # 11
[1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0], # 12
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], # 13
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], # 14
[0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # 15
]) / 2
print("\n--------------\n")
print(array)
if __name__ == '__main__':
np.set_printoptions(edgeitems=16,
linewidth=200,
formatter=dict(float=lambda x: "%8.4g" % x))
err_model = cc.ErrorModel(0.1, 0.006, 0.006)
ρ = cc.bell_pair(err_model.p_n, [0, 3])
cc.bell_purify_1(ρ, err_model, 0, 3, 1, 2, 4, 5, 'z')
ρ.print()
