def iteration(Temp):
inst_vel_data = thermal_motion.MB_dist_retVel1D(Temp)
inst_vel = inst_vel_data[0]
laser_w = inverse_doppler(w0, thermal_motion.avg_vel1D(Temp))
laser_f = laser_w/(2*np.pi)
doppler_w = absorption.doppler_shift(laser_w, inst_vel)
delta = np.abs(doppler_w - w0)
#doppler_w = w0
W = absorption.rabi_f(Efield, doppler_w)
absorb = absorption.absorbed(Omega, W)
photon_momentum = (hbar * laser_w)/c
delta_v = photon_momentum/(m_p + m_e)
if absorb[1] == 1:
Temp = thermal_motion.inv_cum_MBdistT(inst_vel_data[0]-delta_v, inst_vel_data[1])
time = absorb[0] + lifetime
else:
time = absorb[0]
return [ time, Temp ]
def analytical(Temp):
inst_vel_data = thermal_motion.MB_dist_retVel1D(Temp)
inst_vel = inst_vel_data[0]
laser_w = inverse_doppler(w0, thermal_motion.avg_vel1D(Temp))
laser_f = laser_w/(2*np.pi)
doppler_w = absorption.doppler_shift(laser_w, inst_vel)
photon_momentum = (hbar * laser_w) / c
a_max = photon_momentum * lifetime / (2*(m_p+ m_e))
return a_max
def absorption_chance(T):
inst_vel_data = thermal_motion.MB_dist_retVel1D(T)
inst_vel = inst_vel_data[0]
laser_w = inverse_doppler(w0, thermal_motion.avg_vel1D(T))
laser_f = laser_w/(2*np.pi)
doppler_w = absorption.doppler_shift(laser_w, inst_vel)
W = absorption.rabi_f(Efield, doppler_w)
absorb = absorption.absorbed(Omega, W)
return absorb[1]
def anal_quickplot(Temp):
'''seems far too small to affect temperature'''
a_max = analytical(Temp)
print a_max
time = np.linspace(0, 1, num=10000)
v0 = thermal_motion.avg_vel1D(Temp)
print v0
temparr = np.zeros(shape=time.shape)
i = 0
while i < time.shape[0]:
temparr[i] = thermal_motion.inv_avg_vel1d(v0- a_max*time[i])
i = i + 1
fig1=pyplot.figure()
ax1=pyplot.subplot()
ax1.plot(time, temparr)
return pyplot.show()
def T_v_laserf():
T_rng = np.linspace(0,293,num=100)
avg_v = thermal_motion.avg_vel1D(T_rng)
laser_w = inverse_doppler(w0, avg_v)
laser_f = laser_w/(2*np.pi)
doppler_w = w0
W = absorption.rabi_f(Efield, doppler_w)
rabi_max =(Omega/ W)**2
fig1 = pyplot.figure()
ax1 = pyplot.subplot()
ax1.plot(T_rng, laser_f-f0)
return pyplot.show()
def T_v_absorption(base_T):
laser_w = inverse_doppler(w0, thermal_motion.avg_vel1D(base_T))
T_rng= np.linspace(base_T*0.99, base_T*1.01,num=1000)
doppler_w = absorption.doppler_shift(laser_w, thermal_motion.avg_vel1D(T_rng))
W = absorption.rabi_f(Efield, doppler_w)
rabi_max = (Omega / W) ** 2
fig2 = pyplot.figure(figsize=(9.5,8))
ax1 = pyplot.subplot()
ax1.plot(thermal_motion.avg_vel1D(T_rng)/thermal_motion.avg_vel1D(base_T), rabi_max, label=r'293$K$', color='black')
ax1.set_xlim([thermal_motion.avg_vel1D(T_rng)[0]/thermal_motion.avg_vel1D(base_T), thermal_motion.avg_vel1D(T_rng)[-1]/thermal_motion.avg_vel1D(base_T)])
base_T = 100
laser_w = inverse_doppler(w0, thermal_motion.avg_vel1D(base_T))
T_rng = np.linspace(base_T * 0.99, base_T * 1.01, num=1000)
doppler_w = absorption.doppler_shift(laser_w, thermal_motion.avg_vel1D(T_rng))
W = absorption.rabi_f(Efield, doppler_w)
rabi_max = (Omega / W) ** 2
ax1 = pyplot.subplot()
ax1.plot(thermal_motion.avg_vel1D(T_rng) / thermal_motion.avg_vel1D(base_T), rabi_max, label=r'100$K$')
base_T = 1
laser_w = inverse_doppler(w0, thermal_motion.avg_vel1D(base_T))
T_rng= np.linspace(base_T*0.99, base_T*1.01,num=1000)
doppler_w = absorption.doppler_shift(laser_w, thermal_motion.avg_vel1D(T_rng))
W = absorption.rabi_f(Efield, doppler_w)
rabi_max = (Omega / W) ** 2
ax1 = pyplot.subplot()
ax1.plot(thermal_motion.avg_vel1D(T_rng)/thermal_motion.avg_vel1D(base_T), rabi_max, label = r'1$K$')
base_T = 1e-2
laser_w = inverse_doppler(w0, thermal_motion.avg_vel1D(base_T))
T_rng = np.linspace(base_T * 0.99, base_T * 1.01, num=1000)
doppler_w = absorption.doppler_shift(laser_w, thermal_motion.avg_vel1D(T_rng))
W = absorption.rabi_f(Efield, doppler_w)
rabi_max = (Omega / W) ** 2
ax1 = pyplot.subplot()
ax1.plot(thermal_motion.avg_vel1D(T_rng) / thermal_motion.avg_vel1D(base_T), rabi_max, label=r'10$mK$')
#ax1.set_title('Absorption sensitivity of atom velocity \n centered on average velocity at given Temperature', fontsize=26)
ax1.set_xlabel(r'Ratio of Atom Velocity from $<v>$ at Temperature', fontsize=22)
ax1.set_ylabel(r'Probability of absorption', fontsize=22)
ax1.tick_params(axis='both', which='major', labelsize=16)
ax1.legend(fancybox=True, framealpha=0.7, fontsize=20)
pyplot.tight_layout()
return pyplot.show()