def repratescan(treplist, pool, savefigs=None, **kargs):
# # mnames, v, laser_det, delta, pulsefunc, pulseshape, pulsearea, pulsetotaltime, pulsepoints, trep, npulse = args
TASKS = [(kargs['mnames'], kargs['v'], bloch.laser_detd2,
kargs['detu'], kargs['gausspulse'], kargs['gausssigma'],
kargs['gausstheta'], kargs['gausstau'], 30, trep, kargs['npulse']) for trep in treplist]
try:
out = pool.map_async(pulsescalc, TASKS).get(999999)
except KeyboardInterrupt:
pool.terminate()
sys.exit(0)
nelems = len(kargs['v'])
results = zeros((len(treplist), nelems+1))
for i, res in enumerate(out):
results[i, 0] = treplist[i]
for k in xrange(nelems):
results[i, k+1] = res[k][-1]
d01 = abs(bloch.laser_detd2(0)[21,6])
timescale = d01/2/np.pi
pl.figure()
for i in xrange(2,6):
pl.plot(results[:, 0]*timescale, results[:, i+1], '.-', label="|%d>"%i)
pl.plot(results[:, 0]*timescale, results[:, 3]+results[:, 4]+results[:, 5]+results[:, 6], 'k--', label='total')
pl.legend(loc='best')
pl.title('Upper state populations')
pl.xlim([results[0,0]*timescale, results[-1,0]*timescale])
pl.xlabel('Repetition rate divider')
pl.ylabel('Population')
if savefigs:
figname = "%s_pop.png" %savefigs
pl.savefig(figname)
# catchimgup("Population", "%s" %figname)
pl.figure()
for i in [6]:
pl.plot(results[:,0]*timescale, results[:, i+1], '--', label='Real')
for i in [21]:
pl.plot(results[:,0]*timescale, results[:, i+1], ':', label='Imag')
pl.legend(loc='best')
pl.title('Ground state coherence')
pl.xlim([results[0,0]*timescale, results[-1,0]*timescale])
pl.xlabel('Repetition rate divider')
pl.ylabel('Coherence')
if savefigs:
figname = "%s_coh.png" %savefigs
pl.savefig(figname)
def main():
try:
import multiprocessing as processing
except:
import processing
NUMBER_OF_PROCESSES = processing.cpu_count()
pool = processing.Pool(processes=NUMBER_OF_PROCESSES)
# bloch.laser_detd2(0)
# sys.exit(0)
matrices = bloch.blochd2()
mnames = ['bloch_atomic', 'laser_pow']
for i in range(len(mnames)):
matrices[i].export_mtx(mnames[i])
v = matrix(zeros((36, 1)))
# v[0] = 0.5
# v[1] = 0.5
v[2] = 1
# TASKS = [(mnames, t, bloch.laser_det) for t in range(10,1000)]
# out = pool.map(timedomain, TASKS)
# print out[0]
# print bloch.laser_det(255)
# omega = np.pi
# delta = -1756
# maxt = 10
# params = [mnames, v, maxt, omega, bloch.laser_detd2, delta]
# res = timedomain(params)
# t = linspace(0, maxt, 1001)
# # print res[2, :]
# # markers = ['k-', 'b--', 'r-.', 'g:']
# # for i in range(3, -1, -1):
# # pl.plot(t, res[i, :], markers[i], label='|%d>' % (i), linewidth=2)
# [pl.plot(t, res[i, :]) for i in range(6)]
# # pl.legend(loc='best')
# pl.show()
# sys.exit(0)
# #### D2 line frequency comb - time dependent
# G = 32.889e6
# timescale = 1/G
# # pulse length = 1ps
# tauP = 1e-12 / timescale
# gausssigma = tauP * sqrt(pi/(2*log(2)))
# gausstheta = 1/50
# gausstau = 4 * gausssigma
# v = matrix(zeros((36, 1)))
# v[0] = 0.5
# v[1] = 0.5
# #
# d01 = abs(bloch.laser_detd2(0)[21,6])
# trep = 100.5/(d01/2/np.pi)
# # print("trep %f" %trep)
# # print("gtau %f" %gausstau)
# # sys.exit(0)
# npulse = 100
# # detu = -2009.3/2
# detu = 0
# # mnames, v, laser_det, delta, pulsefunc, pulseshape, pulsearea, pulsetotaltime, pulsepoints, trep, npulse = args
# res = pulsescalc((mnames, v, bloch.laser_detd2, detu, gausspulse, gausssigma, gausstheta, gausstau, 30, trep, npulse))
# pulses = range(npulse+1)
# pl.figure(1)
# for i in xrange(0,2):
# pl.plot(pulses, res[i, :], '.-', label='%d'%i)
# pl.plot(pulses, res[0, :]+res[1, :], 'kx-', label='Sum')
# pl.title('Lower state populations')
# pl.legend(loc='best')
# pl.figure(0)
# for i in xrange(2,6):
# pl.plot(pulses, res[i, :], '.-', label='%d'%i)
# pl.plot(pulses, res[2, :]+res[3, :]+res[4, :]+res[5, :], 'kx-', label='Sum')
# pl.title('Upper state populations')
# pl.legend(loc='best')
# # pl.figure()
# # for i in xrange(4, 6):
# # pl.plot(pulses, res[i, :], label='%d'%i)
# # pl.title('Real Coherence')
# # pl.legend(loc='best')
# # pl.figure()
# # for i in xrange(10, ):
# # pl.plot(pulses, res[i, :], label='%d'%i)
# # pl.title('Imag Coherence')
# # pl.legend(loc='best')
# pl.show()
# sys.exit(0)
# sys.exit(0)
# # #### Fixed repetition rate and scanned detuning
G = 32.889e6
timescale = 1/G
# pulse length = 1ps
tauP = 1e-12 / timescale
gausssigma = tauP * sqrt(pi/(2*log(2)))
gausstheta = 1/25
gausstau = 4 * gausssigma
v = matrix(zeros((36, 1)))
v[0] = 0.5
v[1] = 0.5
d01 = abs(bloch.laser_detd2(0)[21,6])
# trep = 100.5/(d01/2/np.pi)
# print("trep %f" %trep)
# print("gtau %f" %gausstau)
# sys.exit(0)
npulse = 500
# # detu = -2009.3/2
# detu = 0
trepbase = 100
dt = 0.04
ntrep = 81
treplist = linspace(trepbase-dt, trepbase+dt, ntrep)/(d01/2/np.pi)
figs = ['6level_f32',
'6level_f33',
'6level_f34',
'6level_f35',
'6level_f42',
'6level_f43',
'6level_f44',
'6level_f45']
detus = [0, 28.89, 28.89+38.46, 28.89+38.46+47.97,
-1756.33, -1756.33+28.89, -1756.33+28.89+38.46, -1756.33+28.89+38.46+47.97]
# loop through all the settings
for pars in zip(figs, detus):
repratescan(treplist, pool=pool, savefigs=pars[0], mnames=mnames, v=v,
detu=pars[1], gausspulse=gausspulse, gausssigma=gausssigma,
gausstheta=gausstheta, gausstau=gausstau,
npulse=npulse)
# # on resonance with F=4->F'5
# detu = -1638.01
# repratescan(treplist, pool=pool, savefigs="6level_f45", mnames=mnames, v=v,
# detu=detu, gausspulse=gausspulse, gausssigma=gausssigma,
# gausstheta=gausstheta, gausstau=gausstau,
# npulse=npulse)
pl.show()