def calc_2D_spectrum_3rd(q_func, g_func, h1_func, h2_func, h4_func, h5_func,
corr_func_freq_qm, dipole_mom, delay_time,
delay_index, E_min1, E_max1, E_min2, E_max2,
num_points_2D, mean):
full_2D_spectrum = np.zeros((num_points_2D, num_points_2D, 3))
counter1 = 0
counter2 = 0
step_length = ((E_max1 - E_min1) / num_points_2D)
print('Compute rfunc')
rfunc = calc_Rfuncs_tdelay(q_func, delay_time, delay_index)
print('Compute rfunc 3rd')
rfunc_3rd = calc_Rfuncs_3rd_tdelay(g_func, h1_func, h2_func, h4_func,
h5_func, corr_func_freq_qm, delay_time,
delay_index)
print('DONE')
print('DIMENSIONS of RFUNC and RFUNC_3rd:')
print(rfunc.shape[0], rfunc_3rd.shape[0])
while counter1 < num_points_2D:
counter2 = 0
omega1 = E_min1 + counter1 * step_length
while counter2 < num_points_2D:
omega2 = E_min2 + counter2 * step_length
full_2D_integrant = twoD_spectrum_integrant_3rd(
rfunc, rfunc_3rd, q_func, omega1 - mean, omega2 - mean,
delay_time)
full_2D_spectrum[counter1, counter2, 0] = omega1
full_2D_spectrum[counter1, counter2, 1] = omega2
full_2D_spectrum[counter1, counter2, 2] = (np.dot(
dipole_mom, dipole_mom))**2.0 * cumul.simpson_integral_2D(
full_2D_integrant).real
counter2 = counter2 + 1
counter1 = counter1 + 1
return full_2D_spectrum
def calc_2DES_time_series_morse_list(morse_list, g2_solvent, E_min1, E_max1,
E_min2, E_max2, num_points_2D, rootname,
num_times, time_step):
averaged_val = np.zeros((num_times, 2))
# make sure chosen delay times break down into an integer number of timesteps in the response function
step_length_t = (g2_solvent[1, 0] - g2_solvent[0, 0]).real
eff_time_index_2DES = int(round(time_step / step_length_t))
eff_time_step_2DES = eff_time_index_2DES * step_length_t
current_delay = 0.0
current_delay_index = 0
counter = 0
while counter < num_times:
print(counter, current_delay)
spectrum_2D = calc_2D_spectrum_exact_morse_list(
morse_list, g2_solvent, current_delay, current_delay_index, E_min1,
E_max1, E_min2, E_max2, num_points_2D)
twoDES.print_2D_spectrum(rootname + '_2DES_' + str(counter) + '.dat',
spectrum_2D, False)
averaged_val[counter, 0] = current_delay
averaged_val[counter, 1] = cumul.simpson_integral_2D(spectrum_2D)
counter = counter + 1
current_delay = current_delay + eff_time_step_2DES
current_delay_index = current_delay_index + eff_time_index_2DES
np.savetxt(rootname + '_Morse_averaged_spectrum.txt', averaged_val)
def calc_2DES_time_series_batch(q_batch, dipole_batch, num_batches, E_min1,
E_max1, E_min2, E_max2, num_points_2D,
rootname, num_times, time_step, mean):
averaged_val = np.zeros((num_times, 2))
transient_abs = np.zeros((num_times, num_points_2D, 3))
# make sure chosen delay times break down into an integer number of timesteps in the response function
step_length_t = ((q_batch[0])[1, 0] - (q_batch[0])[0, 0]).real
eff_time_index_2DES = int(round(time_step / step_length_t))
eff_time_step_2DES = eff_time_index_2DES * step_length_t
current_delay = 0.0
current_delay_index = 0
counter = 0
while counter < num_times:
print(counter, current_delay)
spectrum_2D = np.zeros((num_points_2D, num_points_2D, 3))
batch_count = 0
while batch_count < num_batches:
print('Processing batch number ' + str(batch_count + 1))
spectrum_2D_temp = calc_2D_spectrum(q_batch[batch_count],
dipole_batch[batch_count],
current_delay,
current_delay_index, E_min1,
E_max1, E_min2, E_max2,
num_points_2D, mean)
if batch_count == 0:
spectrum_2D = spectrum_2D + spectrum_2D_temp
else:
spectrum_2D[:, :,
2] = spectrum_2D[:, :, 2] + spectrum_2D_temp[:, :,
2]
batch_count = batch_count + 1
spectrum_2D[:, :, 2] = spectrum_2D[:, :, 2] / (1.0 * num_batches)
print_2D_spectrum(rootname + '_2DES_' + str(counter) + '.dat',
spectrum_2D, False)
#compute transient absorption contribution here:
transient_temp = transient_abs_from_2DES(spectrum_2D)
transient_abs[counter, :, 0] = current_delay
transient_abs[counter, :, 1] = transient_temp[:, 0]
transient_abs[counter, :, 2] = transient_temp[:, 1]
averaged_val[counter, 0] = current_delay
averaged_val[counter, 1] = cumul.simpson_integral_2D(spectrum_2D)
print(averaged_val[counter, 1])
counter = counter + 1
current_delay = current_delay + eff_time_step_2DES
current_delay_index = current_delay_index + eff_time_index_2DES
print_2D_spectrum(
rootname + '_2nd_order_cumulant_transient_absorption_spec.txt',
transient_abs, False)
np.savetxt(rootname + '_2DES_2nd_order_cumulant_averaged_spectrum.txt',
averaged_val)
def compute_HT_term_3rd_order(corr_func_mu_U_U_freq,corr_func_U_U_mu_freq,corr_func_mu_U_mu_freq,mu_av,mu_renorm,mu_reorg,kBT,max_t,steps): Afunc=np.zeros((steps,2),dtype=np.complex_) step_length=max_t/steps for i in range(steps): t_current=i*step_length Afunc[i,0]=t_current integrant1=HT_integrant_U_U_mu(corr_func_U_U_mu_freq,mu_reorg,mu_renorm,mu_av,kBT,t_current) integrant2=HT_integrant_mu_U_mu(corr_func_mu_U_mu_freq,mu_renorm,kBT,t_current) integrant3=HT_integrant_mu_U_U(corr_func_mu_U_U_freq,mu_reorg,mu_renorm,kBT,t_current) tot_integrant=integrant1 tot_integrant[:,:,2]=tot_integrant[:,:,2]-1j*integrant2[:,:,2]+integrant3[:,:,2] Afunc[i,1]=cumulant.simpson_integral_2D(tot_integrant) Afunc[:,1]=Afunc[:,1]*mu_renorm**2.0 return Afunc
def calc_2DES_time_series_GBOM_3rd(q_func, g_func, h1_func, h2_func, h4_func,
h5_func, corr_func, freqs_gs, Omega_sq,
gamma, kbT, dipole_mom, E_min1, E_max1,
E_min2, E_max2, num_points_2D, rootname,
num_times, time_step, mean, is_cl, no_dusch,
four_phonon_term):
averaged_val = np.zeros((num_times, 2))
transient_abs = np.zeros((num_times, num_points_2D, 3))
# make sure chosen delay times break down into an integer number of timesteps in the response function
step_length_t = (q_func[1, 0] - q_func[0, 0]).real
eff_time_index_2DES = int(round(time_step / step_length_t))
eff_time_step_2DES = eff_time_index_2DES * step_length_t
current_delay = 0.0
current_delay_index = 0
counter = 0
while counter < num_times:
print(counter, current_delay)
spectrum_2D = calc_2D_spectrum_GBOM_3rd(
q_func, g_func, h1_func, h2_func, h4_func, h5_func, corr_func,
freqs_gs, Omega_sq, gamma, kbT, dipole_mom, current_delay,
current_delay_index, E_min1, E_max1, E_min2, E_max2, num_points_2D,
mean, is_cl, no_dusch, four_phonon_term)
print_2D_spectrum(rootname + '_2DES_' + str(counter) + '.dat',
spectrum_2D, False)
#compute transient absorption contribution here:
transient_temp = transient_abs_from_2DES(spectrum_2D)
transient_abs[counter, :, 0] = current_delay
transient_abs[counter, :, 1] = transient_temp[:, 0]
transient_abs[counter, :, 2] = transient_temp[:, 1]
averaged_val[counter, 0] = current_delay
averaged_val[counter, 1] = cumul.simpson_integral_2D(spectrum_2D)
counter = counter + 1
current_delay = current_delay + eff_time_step_2DES
current_delay_index = current_delay_index + eff_time_index_2DES
print_2D_spectrum(
rootname + '_3rd_order_cumulant_transient_absorption_spec.txt',
transient_abs, False)
np.savetxt(rootname + '2DES_3rd_order_cumulant_averaged_spectrum.txt',
averaged_val)
def calc_2D_spectrum(q_func, dipole_mom, delay_time, delay_index, E_min1,
E_max1, E_min2, E_max2, num_points_2D, mean):
full_2D_spectrum = np.zeros((num_points_2D, num_points_2D, 3))
step_length = ((E_max1 - E_min1) / num_points_2D)
rfunc = calc_Rfuncs_tdelay(q_func, delay_time, delay_index)
for counter1 in range(num_points_2D):
omega1 = E_min1 + counter1 * step_length
for counter2 in range(num_points_2D):
omega2 = E_min2 + counter2 * step_length
full_2D_integrant = twoD_spectrum_integrant(
rfunc, q_func, omega1 - mean, omega2 - mean, delay_time)
full_2D_spectrum[counter1, counter2, 0] = omega1
full_2D_spectrum[counter1, counter2, 1] = omega2
full_2D_spectrum[counter1, counter2, 2] = (np.dot(
dipole_mom, dipole_mom))**2.0 * cumul.simpson_integral_2D(
full_2D_integrant).real
return full_2D_spectrum
def calc_2DES_time_series(q_func, dipole_mom, E_min1, E_max1, E_min2, E_max2,
num_points_2D, rootname, num_times, time_step, mean):
averaged_val = np.zeros((num_times, 2))
transient_abs = np.zeros((num_times, num_points_2D, 3))
# make sure chosen delay times break down into an integer number of timesteps in the response function
step_length_t = (q_func[1, 0] - q_func[0, 0]).real
eff_time_index_2DES = int(round(time_step / step_length_t))
eff_time_step_2DES = eff_time_index_2DES * step_length_t
current_delay = 0.0
current_delay_index = 0
counter = 0
while counter < num_times:
print(counter, current_delay)
spectrum_2D = calc_2D_spectrum(q_func, dipole_mom, current_delay,
current_delay_index, E_min1, E_max1,
E_min2, E_max2, num_points_2D, mean)
print_2D_spectrum(rootname + '_2DES_' + str(counter) + '.dat',
spectrum_2D, False)
#compute transient absorption contribution here:
transient_temp = transient_abs_from_2DES(spectrum_2D)
transient_abs[counter, :, 0] = current_delay
transient_abs[counter, :, 1] = transient_temp[:, 0]
transient_abs[counter, :, 2] = transient_temp[:, 1]
averaged_val[counter, 0] = current_delay
averaged_val[counter, 1] = cumul.simpson_integral_2D(spectrum_2D)
#averaged_val[counter,1]=np.sum(spectrum_2D[:,:,2])/(spectrum_2D.shape[0]*2.0)
print(averaged_val[counter, 1])
counter = counter + 1
current_delay = current_delay + eff_time_step_2DES
current_delay_index = current_delay_index + eff_time_index_2DES
print_2D_spectrum(
rootname + '_2nd_order_cumulant_transient_absorption_spec.txt',
transient_abs, False)
np.savetxt(rootname + '_2DES_2nd_order_cumulant_averaged_spectrum.txt',
averaged_val)
def calc_2D_spectrum_GBOM_3rd(q_func, g_func, h1_func, h2_func, h4_func,
h5_func, corr_func, freqs_gs, Omega_sq, gamma,
kbT, dipole_mom, delay_time, delay_index, E_min1,
E_max1, E_min2, E_max2, num_points_2D, mean,
is_cl, no_dusch, four_phonon_term):
full_2D_spectrum = np.zeros((num_points_2D, num_points_2D, 3))
counter1 = 0
counter2 = 0
step_length = ((E_max1 - E_min1) / num_points_2D)
print('Compute rfunc')
rfunc = calc_Rfuncs_tdelay(q_func, delay_time, delay_index)
print('Compute rfunc 3rd')
rfunc_3rd = calc_Rfuncs_3rd_GBOM_tdelay(g_func, h1_func, h2_func, h4_func,
h5_func, corr_func, freqs_gs,
Omega_sq, gamma, kbT, delay_time,
delay_index, is_cl, no_dusch,
four_phonon_term)
print('DONE')
print('Dimensions RFunc and Rfunc 3rd')
print(rfunc.shape[0], rfunc_3rd.shape[0])
while counter1 < num_points_2D:
counter2 = 0
omega1 = E_min1 + counter1 * step_length
while counter2 < num_points_2D:
omega2 = E_min2 + counter2 * step_length
full_2D_integrant = twoD_spectrum_integrant_3rd(
rfunc, rfunc_3rd, q_func, omega1 - mean, omega2 - mean,
delay_time)
full_2D_spectrum[counter1, counter2, 0] = omega1
full_2D_spectrum[counter1, counter2, 1] = omega2
full_2D_spectrum[counter1, counter2, 2] = (np.dot(
dipole_mom, dipole_mom))**2.0 * cumul.simpson_integral_2D(
full_2D_integrant).real
counter2 = counter2 + 1
counter1 = counter1 + 1
return full_2D_spectrum
def calc_2D_spectrum_exact_morse(gs_energies, ex_energies, overlap,
boltzmann_fac, g2_solvent, delay_time,
delay_index, E_min1, E_max1, E_min2, E_max2,
num_points_2D):
full_2D_spectrum = np.zeros((num_points_2D, num_points_2D, 3))
step_length = ((E_max1 - E_min1) / num_points_2D)
rfunc = total_Rfuncs_exact(gs_energies, ex_energies, overlap, g2_solvent,
delay_time, delay_index)
for counter1 in range(num_points_2D):
omega1 = E_min1 + counter1 * step_length
for counter2 in range(num_points_2D):
omega2 = E_min2 + counter2 * step_length
full_2D_integrant = twoD_spectrum_integrant_morse(
rfunc, omega1, omega2, delay_time)
full_2D_spectrum[counter1, counter2, 0] = omega1
full_2D_spectrum[counter1, counter2, 1] = omega2
full_2D_spectrum[counter1, counter2,
2] = cumul.simpson_integral_2D(
full_2D_integrant).real
return full_2D_spectrum
def calc_2D_spectrum_exact_morse_list(morse_list, g2_solvent, delay_time,
delay_index, E_min1, E_max1, E_min2,
E_max2, num_points_2D):
full_2D_spectrum = np.zeros((num_points_2D, num_points_2D, 3))
step_length = ((E_max1 - E_min1) / num_points_2D)
num_steps = g2_solvent.shape[0]
max_t = g2_solvent[num_steps - 1, 0]
rfunc = total_Rfuncs_exact_list(morse_list, g2_solvent, delay_time,
delay_index)
for counter1 in range(num_points_2D):
omega1 = E_min1 + counter1 * step_length
for counter2 in range(num_points_2D):
omega2 = E_min2 + counter2 * step_length
full_2D_integrant = twoD_spectrum_integrant_morse(
rfunc, omega1, omega2, delay_time)
full_2D_spectrum[counter1, counter2, 0] = omega1
full_2D_spectrum[counter1, counter2, 1] = omega2
full_2D_spectrum[counter1, counter2,
2] = cumul.simpson_integral_2D(
full_2D_integrant).real
return full_2D_spectrum
def calc_2D_spectrum_Eopt_av_cumul(q_func_list, dipole_list, delay_time,
delay_index, E_min1, E_max1, E_min2, E_max2,
num_points_2D, mean_fluct):
full_2D_spectrum = np.zeros((num_points_2D, num_points_2D, 3))
counter1 = 0
counter2 = 0
step_length = ((E_max1 - E_min1) / num_points_2D)
# work out size of Rfuncs:
temp_max_index = q_func_list[0].shape[0] - delay_index
max_index = 0
if (temp_max_index % 2) == 0:
# even.
max_index = temp_max_index / 2
else:
# odd
max_index = (temp_max_index - 1) / 2
print(delay_time, delay_index)
print(E_min1, E_max1)
# build rfunc list:
exp_rfunc_av = np.zeros((max_index, max_index, 4), dtype=complex)
for i in range(len(q_func_list)):
rfuncs_temp = calc_Rfuncs_tdelay(q_func_list[i], delay_time,
delay_index)
exp_rfunc_av[:, :, 0] = rfuncs_temp[:, :, 0]
exp_rfunc_av[:, :, 1] = rfuncs_temp[:, :, 1]
exp_rfunc_av[:, :, 2] = exp_rfunc_av[:, :, 2] + (
np.exp(rfuncs_temp[:, :, 2]) + np.exp(rfuncs_temp[:, :, 5]))
exp_rfunc_av[:, :, 3] = exp_rfunc_av[:, :, 3] + (
np.exp(rfuncs_temp[:, :, 3]) + np.exp(rfuncs_temp[:, :, 4]))
# now divide by batch number
exp_rfunc_av[:, :, 2] = exp_rfunc_av[:, :, 2] / (1.0 * len(q_func_list))
exp_rfunc_av[:, :, 3] = exp_rfunc_av[:, :, 3] / (1.0 * len(q_func_list))
# now use rfuncs_av to compute spectrum
for i in range(len(q_func_list)):
temp_spec = np.zeros(
(full_2D_spectrum.shape[0], full_2D_spectrum.shape[1], 3))
counter1 = 0
while counter1 < num_points_2D:
counter2 = 0
omega1 = E_min1 + counter1 * step_length
while counter2 < num_points_2D:
omega2 = E_min2 + counter2 * step_length
full_2D_integrant = twoD_spectrum_integrant_Eopt_av_cumulant(
exp_rfunc_av, q_func_list[i], omega1 - mean_fluct[i],
omega2 - mean_fluct[i], delay_time)
temp_spec[counter1, counter2, 0] = omega1
temp_spec[counter1, counter2, 1] = omega2
temp_spec[counter1, counter2, 2] = (np.dot(
dipole_list[i], dipole_list[i]
))**2.0 * cumul.simpson_integral_2D(full_2D_integrant).real
counter2 = counter2 + 1
counter1 = counter1 + 1
full_2D_spectrum[:, :, 0] = temp_spec[:, :, 0]
full_2D_spectrum[:, :, 1] = temp_spec[:, :, 1]
# write temp spec to file:
full_2D_spectrum[:, :,
2] = full_2D_spectrum[:, :, 2] + temp_spec[:, :, 2]
full_2D_spectrum[:, :,
2] = full_2D_spectrum[:, :, 2] / (1.0 * len(q_func_list))
return full_2D_spectrum
