def b_vec_fun_no_a(b_vec, binval, delmval, p):
bval = b_vec[0] + 1j * b_vec[1]
Omega = p['Omega']
rho = np.array(
rho_broad_full(0, bval, 0, delmval, find_dressed_states_m, p))
p['Omega'] = 0
rho_no_pump = np.array(
rho_broad_full(0, bval, 0, delmval, find_dressed_states_m, p))
p['Omega'] = Omega
#S12val=rho[1,0]*p['Nm']*p['gm']
S12val = rho[2, 1] * p['No'] * p['gm'] + rho_no_pump[2, 1] * (
p['Nm'] - p['No']) * p['gm']
bval1 = (-1j * S12val + np.sqrt(p['gammamc']) * binval) / (
(p['gammamc'] + p['gammami']) / 2 - 1j * delmval)
return [bval1.real, bval1.imag] - b_vec
def S12_4(Bval, bval, delmval, p):
p['No'] = p['No_total']
p['Nm'] = p['Nm_total']
omegaao = omegaao4_from_I(B_val, p)
p['sd_delao'] = sd_delao4_from_I(B_val, p)
p['mean_delao'] = deltaao_from_I(B_val, omegaao, p)
p['mean_delam'] = deltamac_from_I(B_val, p)
p['nbath'] = nbath_from_T(T, p, p['mean_delam'])
p['Omega'] = Omega_from_PdBm(P_pump, p)
rho = np.array(
rho_broad_full(0, bval, 0, delmval, find_dressed_states_m, p))
p['Omega'] = 0
rho_no_pump = np.array(
rho_broad_full(0, bval, 0, delmval, find_dressed_states_m, p))
return rho[2, 1] * p['No'] * p['gm'] + rho_no_pump[2, 1] * (
p['Nm'] - p['No']) * p['gm']
def S12_1(B_val, bval, delmval, p):
p['No'] = p['No_total'] / (np.exp(B_val * p['Gg'] * 6.63e-34 /
(1.38e-23 * T)) - 1)
p['Nm'] = p['Nm_total'] / (np.exp(B_val * p['Gg'] * 6.63e-34 /
(1.38e-23 * T)) - 1)
omegaao = omegaao1_from_I(B_val, p)
p['sd_delao'] = sd_delao1_from_I(B_val, p)
p['mean_delao'] = deltaao_from_I(B_val, omegaao, p)
p['mean_delam'] = deltamac_from_I(B_val, p)
p['nbath'] = nbath_from_T(T, p, deltamacval=p['mean_delam'])
p['Omega'] = Omega_from_PdBm(P_pump, p)
rho = np.array(
rho_broad_full(0, bval, 0, delmval, find_dressed_states_m, p))
p['Omega'] = 0
rho_no_pump = np.array(
rho_broad_full(0, bval, 0, delmval, find_dressed_states_m, p))
return rho[2, 1] * p['No'] * p['gm'] + rho_no_pump[2, 1] * (
p['Nm'] - p['No']) * p['gm']
#start_guess_vec_bout=[boutvals[ii,jj-1].real,boutvals[ii,jj-1].imag]
start_guess_vec_b = [bvals[0, jj - 1].real, bvals[0, jj - 1].imag]
#start_guess_vec_b2=[bvals2[ii,jj-1].real,bvals2[ii,jj-1].imag,avals[ii,jj-1].real,avals[ii,jj-1].imag]
elif jj == 0:
start_guess_vec_b = [bvals[ii - 1, 0].real, bvals[ii - 1, 0].imag]
else:
start_guess_complex_b = (bvals[ii, jj - 1] + bvals[ii - 1, jj]) / 2
start_guess_vec_b = [
start_guess_complex_b.real, start_guess_complex_b.imag
]
# for pkey in p:
# print(pkey +' = '+str(type(p[pkey])))
#print(type(binval))
#print(type(deltamval))
bvals[ii, jj] = find_b_no_a(binval, deltamval, p, start_guess_vec_b)
rho_out[:, :, ii, jj] = rho_broad_full(0, bvals[ii, jj], 0, deltamval,
find_dressed_states_m, p)
calc_time[ii, jj] = time.time() - time1
elapsed_time = time.time() - start_time
print(' ' + filename + ': ' + str(ii) + ', Time: ' + time.ctime() +
', Elapsed: ' + str(elapsed_time))
np.savez(filename,
binvals=binvals,
B_vals=B_vals,
deltamvals=deltamvals,
p=p,
bvals=bvals,
rho_out=rho_out,
P_pump=P_pump,
P_mu=P_mu,
T=T,
elapsed_time=elapsed_time,
start_guess_vec_b)
#rho_out_b[:,:,ii,jj]=S12_2(B_val,bvals[ii,jj],deltamval,p)#+S12_2(B_val,bvals[ii,jj],deltamval,p)+S12_3(B_val,bvals[ii,jj],deltamval,p)+S12_4(B_val,bvals[ii,jj],deltamval,p)
p['No'] = p['No_total'] / (np.exp(B_val * p['Gg'] * 6.63e-34 /
(1.38e-23 * T)) - 1)
p['Nm'] = p['Nm_total'] / (np.exp(B_val * p['Gg'] * 6.63e-34 /
(1.38e-23 * T)) - 1)
omegaao = omegaao1_from_I(B_val, p)
p['sd_delao'] = sd_delao1_from_I(B_val, p)
p['mean_delao'] = deltaao_from_I(B_val, omegaao, p)
p['mean_delam'] = deltamac_from_I(B_val, p)
p['nbath'] = nbath_from_T(T, p, deltamacval=p['mean_delam'])
p['Omega'] = Omega_from_PdBm(P_pump, p)
#bvals[ii,jj]=find_b_no_a(binval,deltamval,p,start_guess_vec_b)
rho_out_b[:, :, ii, jj] = np.array(
rho_broad_full(
0, bvals[ii, jj], 0, deltamval, find_dressed_states_m,
p)) * p['No_total'] / (np.exp(B_val * p['Gg'] * 6.63e-34 /
(1.38e-23 * T)) - 1)
p['No'] = p['No_total'] / (np.exp(B_val * p['Gg'] * 6.63e-34 /
(1.38e-23 * T)) - 1)
p['Nm'] = p['Nm_total'] / (np.exp(B_val * p['Gg'] * 6.63e-34 /
(1.38e-23 * T)) - 1)
omegaao = omegaao2_from_I(B_val, p)
p['sd_delao'] = sd_delao2_from_I(B_val, p)
p['mean_delao'] = deltaao_from_I(B_val, omegaao, p)
p['mean_delam'] = deltamac_from_I(B_val, p)
p['nbath'] = nbath_from_T(T, p, p['mean_delam'])
p['Omega'] = Omega_from_PdBm(P_pump, p)
rho_out_b[:, :, ii, jj] = rho_out_b[:, :, ii, jj] + np.array(