def save_fig(state, figname):
fig, ax = qt.hinton(state, [
'00',
'01',
'10',
'11',
], [
'00',
'01',
'10',
'11',
])
plt.savefig('state_hinton_' + str(figname) + '.png')
fig, ax = qt.matrix_histogram(state, [
'00',
'01',
'10',
'11',
], [
'00',
'01',
'10',
'11',
])
plt.savefig('state_hist_' + str(figname) + '.png')
np.savetxt('state_' + str(figname),
state,
header='density matrix data, 00,01,10,11')
from matplotlib import pyplot
import qutip as q
import numpy as np
measurement = [1.0, 0.5, 0.5]
p1, p2, p3 = measurement
density_matrx = np.array([[1-p1, p3 - .5 + 1.j * (p2-.5)],[p3 - .5 - 1.j * (p2-.5), p1]])
real = np.real(density_matrx)
imag = np.imag(density_matrx)
fig = pyplot.figure()
ax = fig.add_subplot(131, projection = '3d')
q.matrix_histogram(real, title = 'Real', limits = [-1,1], fig = fig, ax = ax)
ax = fig.add_subplot(132, projection = '3d')
q.matrix_histogram(imag, title = 'Imaginary', limits = [-1,1], fig = fig, ax = ax)
ax = fig.add_subplot(133)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
def errorBarSimple(trials, prob):
#look at wiki http://en.wikipedia.org/wiki/Checking_whether_a_coin_is_fair
'''returns 1 sigma error bar on each side i.e 1 sigma interval is val - err < val + err'''
Z = 1.0
s = np.sqrt(prob * (1.0 - prob) / float(trials))
err = Z * s
return err
err = errorBarSimple
trials = 100
density_matrx = np.array([[z, x + 1j*y],[x - 1j*y, 1 - z]])
real = np.real(density_matrx)
imag = np.imag(density_matrx)
#make the figure
#this uses the qutip routine as the baseline but then makes modifications for bigger font sizes
fig = pyplot.figure()
labels = ['|D>','|S>']
zlim = [-1,1]
norm = matplotlib.colors.Normalize(zlim[0], zlim[1])
#first plot
ax = fig.add_subplot(121, projection = '3d')
ax.set_title('Real', fontsize = 30)
q.matrix_histogram(real, limits = zlim, fig = fig, ax = ax, colorbar = False)
ax.set_xticklabels(labels, fontsize = 22)
ax.set_yticklabels(labels, fontsize = 22)
ax.tick_params(axis='z', labelsize=22)
cax, kw = matplotlib.colorbar.make_axes(ax, shrink=.75, pad=.0)
cb1 = matplotlib.colorbar.ColorbarBase(cax, norm = norm)
cl = pyplot.getp(cax, 'ymajorticklabels')
pyplot.setp(cl, fontsize=22)
#next subplot
ax = fig.add_subplot(122, projection = '3d')
ax.set_title('Imaginary', fontsize = 30)
q.matrix_histogram(imag, limits = zlim, fig = fig, ax = ax, colorbar = False)
ax.set_xticklabels(labels, fontsize = 22)
ax.set_yticklabels(labels, fontsize = 22)
ax.tick_params(axis='z', labelsize=22)
cax, kw = matplotlib.colorbar.make_axes(ax, shrink=.75, pad=.0)
density_matrx = np.array([[z, x + 1j * y], [x - 1j * y, 1 - z]])
real = np.real(density_matrx)
imag = np.imag(density_matrx)
#make the figure
#this uses the qutip routine as the baseline but then makes modifications for bigger font sizes
fig = pyplot.figure()
labels = ['|D>', '|S>']
zlim = [-1, 1]
norm = matplotlib.colors.Normalize(zlim[0], zlim[1])
#first plot
ax = fig.add_subplot(121, projection='3d')
ax.set_title('Real', fontsize=30)
q.matrix_histogram(real, limits=zlim, fig=fig, ax=ax, colorbar=False)
ax.set_xticklabels(labels, fontsize=22)
ax.set_yticklabels(labels, fontsize=22)
ax.tick_params(axis='z', labelsize=22)
cax, kw = matplotlib.colorbar.make_axes(ax, shrink=.75, pad=.0)
cb1 = matplotlib.colorbar.ColorbarBase(cax, norm=norm)
cl = pyplot.getp(cax, 'ymajorticklabels')
pyplot.setp(cl, fontsize=22)
#next subplot
ax = fig.add_subplot(122, projection='3d')
ax.set_title('Imaginary', fontsize=30)
q.matrix_histogram(imag, limits=zlim, fig=fig, ax=ax, colorbar=False)
ax.set_xticklabels(labels, fontsize=22)
ax.set_yticklabels(labels, fontsize=22)
ax.tick_params(axis='z', labelsize=22)
cax, kw = matplotlib.colorbar.make_axes(ax, shrink=.75, pad=.0)
def genertate_bell_state(state, noise, tc, dec):
'''
state [int]:
0 : |00> + |11>
1 : |00> - |11>
2 : |01> - |10>
3 : |01> + |10>
noise [boolean]:
add noise to the exp
tc [boolean]:
turn tunnelcoupling completely off when you do single qubit gates
dec [boolean]: # not yet implemented.
enable decoupled gate
'''
# Start in |00>
psi0 = np.array(list(basis(6, 0) * basis(6, 0).dag()))[:, 0]
# define hamiltonian
if tc == True:
db = double_dot_hamiltonian(19.7e9, 18.4e9, 850e9, 840e9, 0 * 0.250e9)
else:
db = double_dot_hamiltonian(19.7e9, 18.4e9, 850e9, 840e9, 0.250e9)
# # # J = ~6MHZ @ epsilon 835e9, t = 210e6 // note a bit of assymetry, so you will get a tiny bit of phase
chargingE = 850e9 * np.pi * 2
detuningE = 828.6e9 * np.pi * 2
# Number of simulation to average.
num_sim = 500
if noise == True:
db = my_noise.add_nuclear_and_charge_noise(db)
db.number_of_sim_for_static_noise(num_sim)
# Do MW on both qubits.
if state == 0 or state == 3:
db.mw_pulse(19.7e9, np.pi / 2, 2e6, 0e-9, 125e-9)
else:
db.mw_pulse(19.7e9, -np.pi / 2, 2e6, 0e-9, 125e-9)
db.mw_pulse(18.4e9, np.pi / 2, 2e6, 0e-9, 125e-9)
# If decoupled is used
if dec == True:
# implement tunnel coupling pulse.
if tc == True:
a = 49e-9
else:
a = 40e-9
db.awg_pulse(detuningE / np.pi / 2, 125e-9, 125e-9 + a, 1e-9)
if tc == True:
db.awg_pulse_tc(0.25e9, 123e-9, 127e-9 + a, 0.05e-9)
db.mw_pulse(18.4e9, 0, 2e6, 200e-9, 450e-9)
db.mw_pulse(19.7e9, 0, 2e6, 200e-9, 450e-9)
db.awg_pulse(detuningE / np.pi / 2, 450e-9, 450e-9 + a, 1e-9)
if tc == True:
db.awg_pulse_tc(0.25e9, 448e-9, 452e-9 + a, 0.05e-9)
if state == 1 or state == 3:
db.mw_pulse(19.7e9, 0, 2e6, 500e-9, 625e-9)
else:
db.mw_pulse(19.7e9, np.pi, 2e6, 500e-9, 625e-9)
db.calc_time_evolution(psi0, 0e-9, 625e-9, int((625e-9) * 1e9 * 100))
else:
if tc == True:
a = 91e-9
else:
a = 85e-9
db.awg_pulse(detuningE / np.pi / 2, 130e-9, 130e-9 + a, 1e-9)
if tc == True:
db.awg_pulse_tc(0.25e9, 125e-9, 135e-9 + a, 0.05e-9)
if state == 1 or state == 3:
db.mw_pulse(19.7e9, 0, 2e6, 235e-9, 360e-9)
else:
db.mw_pulse(19.7e9, np.pi, 2e6, 235e-9, 360e-9)
db.calc_time_evolution(psi0, 0e-9, 365e-9, int((625e-9) * 1e9 * 100))
rho = db.get_density_matrix_final()[:4, :4]
rho_full = db.get_density_matrix_final()
C = calc_concurrence(rho)
bell_states = ['00', '01', '11', '10']
Bell = bell_state(bell_states[state])
Bell.dims = [[4], [1]]
F = (Bell.dag() * Qobj(rho) * Bell)[0, 0]
fig, ax = hinton(rho, ['00', '01', '10', '11'], ['00', '01', '10', '11'])
plt.savefig('Bell_' + str(state) + '_hinton_dec_' + str(dec) + '_noise_' +
str(noise) + "_tc_" + str(tc) + '.png')
fig, ax = matrix_histogram(rho, ['00', '01', '10', '11'],
['00', '01', '10', '11'])
plt.savefig('Bell_' + str(state) + '_hist_dec_' + str(dec) + '_noise_' +
str(noise) + "_tc_" + str(tc) + '.png')
np.savetxt('Bell_' + str(state) + "_dec_" + str(dec) + '_noise_' +
str(noise) + '_tc_' + str(tc) + '_DM.txt',
rho_full,
header='density matrix data, 00,01,10,11,0S,S0')
np.savetxt('Bell_' + str(state) + "_dec_" + str(dec) + '_noise_' +
str(noise) + '_tc_' + str(tc) + '_FID.txt',
np.array([F, C]),
header='State overlap -- Concurrence')
db.clear()
dv.cd(['', 'Experiments', 'RabiTomography', '2013Mar01'])
dv.cd(folder)
dv.open(1)
trials = dv.get_parameter('Tomography.repeat_each_measurement')
measurement = dv.get().asarray
p1, p2, p3 = measurement.transpose()[1]
density_matrx = np.array([[1 - p1, p3 - .5 + 1.j * (p2 - .5)],
[p3 - .5 - 1.j * (p2 - .5), p1]])
real = np.real(density_matrx)
imag = np.imag(density_matrx)
fig = pyplot.figure()
ax = fig.add_subplot(131, projection='3d')
q.matrix_histogram(real, title='Real', limits=[-1, 1], fig=fig, ax=ax)
ax = fig.add_subplot(132, projection='3d')
q.matrix_histogram(imag, title='Imaginary', limits=[-1, 1], fig=fig, ax=ax)
ax = fig.add_subplot(133)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
def errorBarSimple(trials, prob):
#look at wiki http://en.wikipedia.org/wiki/Checking_whether_a_coin_is_fair
'''returns 1 sigma error bar on each side i.e 1 sigma interval is val - err < val + err'''
Z = 1.0
s = np.sqrt(prob * (1.0 - prob) / float(trials))
err = Z * s
return err