def target_robustness_1d(system, amps,dt,Utarget, gvar, vals):
# initialize the fidelities
fidelities = empty(len(vals))
for k in range(len(vals)):
c_sys = control_system(system.drift + vals[k]*gvar, system.control_generators.copy())
fidelities[k] = grape_objective(Utarget, evolve_system(c_sys,amps,dt))/4
plt.plot(vals, fidelities)
plt.ticklabel_format(useOffset=False)
plt.show()
def obj(x):
#nonlocal num
#num = num+1
# evolve the system that computes both the final unitary as well
# as decoupling terms
prop = evolve_system(dec_sys, x, dt, deriv=1)
#extract the final unitary, as well as the array of derivatives
# with respect to control amplitudes
Ufinal = prop[0][0:2, 0:2]
Uderiv = prop[1][:, :, 0:2, 0:2]
# compute the grape objective; the fidelity to the target gate
# as well its jacobian
g, gp = grape_objective(Utarget, (Ufinal, Uderiv), deriv=1)
# compute the norms of the decoupling terms, as well as their
# derivatives
decx, decxp = zero_block_objective(prop, 2, 0, 1, deriv=1)
decy, decyp = zero_block_objective(prop, 2, 1, 2, deriv=1)
decz, deczp = zero_block_objective(prop, 2, 2, 3, deriv=1)
# add together the decoupling objectives and derivatives
dec = decx + decy + decz
decp = decxp + decyp + deczp
shape, shaped = cons.mono_objective(x,
power_lb,
power_ub,
power_tol,
change_b,
change_tol,
deriv=1)
#if num % 100 == 0:
# print('Value at ' + str(num) + ' iterations: '+ str(real(-g+dec+shape)))
#return real(-g+dec+power+change/20),real(-gp+decp+powerp+changep/20)
return real(-g + dec + shape / 100), real(-gp + decp + shaped / 100)
def obj(x):
# fora given control value, propagate the decoupling system, and compute
# derivatives
prop = evolve_system(dec_z_sys, x, dt, deriv=1)
# extract the final unitary and its derivatives
Ufinal = prop[0][0:2, 0:2]
Uderiv = prop[1][:, :, 0:2, 0:2]
# compute the target unitary objective and its derivatives
g, gp = grape_objective(Utarget, (Ufinal, Uderiv), deriv=1)
# compute the decoupling objective and its derivatives
dec, decp = zero_block_objective(prop, 2, 0, 1, deriv=1)
shape, shaped = cons.mono_objective(x,
power_lb,
power_ub,
power_tol,
change_b,
change_tol,
deriv=1)
return real(-g + dec + shape / 20), real(-gp + decp + shaped / 20)