print("Preparing a model system:") with qr.energy_units("1/cm"): mol1 = qr.Molecule([0.0, 12000]) mol2 = qr.Molecule([0.0, 12000]) mol3 = qr.Molecule([0.0, 12100]) mol4 = qr.Molecule([0.0, 12100]) agg = qr.Aggregate([mol1, mol2, mol3, mol4]) agg.set_resonance_coupling(2,3,qr.convert(100.0,"1/cm","int")) agg.set_resonance_coupling(1,3,qr.convert(100.0,"1/cm","int")) with tempfile.TemporaryDirectory() as tdir: path = os.path.join(tdir,"agg.qrp") qr.save_parcel(agg,path) agg2 = qr.load_parcel(path) agg2.build() H = agg2.get_Hamiltonian() print("...done") print("Setting up Lindblad form relaxation:") Ndim = 5 with qr.eigenbasis_of(H): K12 = qr.qm.ProjectionOperator(1, 2, dim=Ndim) K23 = qr.qm.ProjectionOperator(2, 3, dim=Ndim) K34 = qr.qm.ProjectionOperator(3, 4, dim=Ndim) sbi = qr.qm.SystemBathInteraction(sys_operators=[K12, K23, K34],
# for mol_name in transition_widths: width = qr.convert(transition_widths[mol_name], "1/cm", "int") mol = agg2.get_Molecule_by_name(mol_name) mol.set_transition_width((0, 1), width) print("Aggregate has ", agg2.nmono, "single excited electronic states") agg2.build(mult=2, vibgen_approx="TPA") print("and ", agg2.Ntot, " (electro-vibrational) states in total") print("Number of single exciton states :", agg2.Nb[0] + agg2.Nb[1]) qr.save_parcel(agg2, os.path.join(pre_out, "agg2_built.qrp")) # # Electronic aggregate is built with single exciton states only # for mol_name in transition_widths: width = qr.convert(transition_widths[mol_name], "1/cm", "int") mol = agg_el.get_Molecule_by_name(mol_name) mol.set_transition_width((0, 1), width) print("Aggregate has ", agg_el.nmono, "single excited electronic states") agg_el.build(mult=1) HHe = agg_el.get_Hamiltonian()
def run(omega, HR, dE, JJ, rate, E0, vib_loc="up", use_vib=True, stype=qr.signal_REPH, make_movie=False, save_eUt=False, t2_save_pathways=[], dname=None, trimer=None, disE=None): """Runs a complete set of simulations for a single set of parameters If disE is not None it tries to run averaging over Gaussian energetic disorder. """ if dname is None: dname = "sim_" + vib_loc use_trimer = trimer["useit"] rate_sp = trimer["rate"] # # PARAMETERS FROM INPUT FILE # dip1 = INP.dip1 # [1.5, 0.0, 0.0] dip2 = INP.dip2 # [-1.0, -1.0, 0.0] width = INP.feature_width # 100.0 width2 = INP.feature_width2 normalize_maps_to_maximu = False trim_maps = False units = "1/cm" with qr.energy_units(units): data_descr = "_dO=" + str(dE) + "_omega=" + str(omega) + "_HR=" + str( HR) + "_J=" + str(JJ) if use_vib: sys_char = "_vib" else: sys_char = "_ele" data_ext = sys_char + ".png" obj_ext = sys_char + ".qrp" # parameters of the SP if use_trimer: E2 = trimer["E2"] epsa = (E0 + E2) / 2.0 DE = trimer["DE"] J2 = 0.5 * numpy.sqrt(((E0 - E2)**2) - (DE**2)) ESP2 = epsa + DE / 2.0 ESP1 = epsa - DE / 2.0 # # Model system is a dimer of molecules # with qr.energy_units("1/cm"): if not use_trimer: mol1 = qr.Molecule([0.0, E0]) mol2 = qr.Molecule([0.0, E0 + dE]) print("Monomer 1 energy:", E0) print("Monomer 2 energy:", E0 + dE) else: if disE is not None: mol1 = qr.Molecule([0.0, ESP2 + disE[0]]) mol2 = qr.Molecule([0.0, E0 + dE + disE[1]]) print("Monomer 1 (SP_high) energy:", ESP2 + disE[0]) print("Monomer 2 (B) energy:", E0 + dE + disE[1]) else: mol1 = qr.Molecule([0.0, ESP2]) mol2 = qr.Molecule([0.0, E0 + dE]) print("Monomer 1 (SP_high) energy:", ESP2) print("Monomer 2 (B) energy:", E0 + dE) if disE is not None: mol3 = qr.Molecule([0.0, ESP1 + disE[2]]) print("Monomer 3 (SP_low) energy:", ESP1 + disE[2]) else: mol3 = qr.Molecule([0.0, ESP1]) print("Monomer 3 (SP_low) energy:", ESP1) mol3.set_transition_width((0, 1), width2) mol3.set_dipole(0, 1, trimer["dipsp"]) mol1.set_transition_width((0, 1), width2) mol1.set_dipole(0, 1, dip1) mol2.set_transition_width((0, 1), width) mol2.set_dipole(0, 1, dip2) if use_trimer: agg = qr.Aggregate([mol1, mol2, mol3]) else: agg = qr.Aggregate([mol1, mol2]) if use_trimer: with qr.energy_units("1/cm"): agg.set_resonance_coupling(0, 1, JJ) print("B - SP_high coupling:", JJ) agg.set_resonance_coupling(0, 2, J2) print("SP coupling:", J2) else: with qr.energy_units("1/cm"): agg.set_resonance_coupling(0, 1, JJ) # # Electronic only aggregate # agg_el = agg.deepcopy() # # if nuclear vibrations are to be added, do it here # if use_vib: with qr.energy_units("1/cm"): mod1 = qr.Mode(omega) mod2 = qr.Mode(omega) if vib_loc == "down": set_vib = [True, False] elif vib_loc == "up": set_vib = [False, True] elif vib_loc == "both": set_vib = [True, True] else: raise Exception("Unknown location of the vibrations") if set_vib[0]: print("Vibrations set for SP_high molecule") mol1.add_Mode(mod1) mod1.set_nmax(0, INP.no_g_vib) mod1.set_nmax(1, INP.no_e_vib) mod1.set_HR(1, HR) if set_vib[1]: print("Vibrations set for B molecule") mol2.add_Mode(mod2) mod2.set_nmax(0, INP.no_g_vib) mod2.set_nmax(1, INP.no_e_vib) mod2.set_HR(1, HR) agg3 = agg.deepcopy() agg.build(mult=1) agg_el.build(mult=1) HH = agg.get_Hamiltonian() He = agg_el.get_Hamiltonian() # # Laboratory setup # lab = qr.LabSetup() lab.set_polarizations(pulse_polarizations=[X, X, X], detection_polarization=X) t2_N_steps = INP.t2_N_steps t2_time_step = INP.t2_time_step time2 = qr.TimeAxis(0.0, t2_N_steps, t2_time_step) cont_p = qr.TwoDResponseContainer(t2axis=time2) cont_m = qr.TwoDResponseContainer(t2axis=time2) # # spectra will be indexed by the times in the time axis `time2` # cont_p.use_indexing_type(time2) # # We define two-time axes, which will be FFTed and will define # the omega_1 and omega_3 axes of the 2D spectrum # t1_N_steps = INP.t1_N_steps t1_time_step = INP.t1_time_step t3_N_steps = INP.t3_N_steps t3_time_step = INP.t3_time_step t1axis = qr.TimeAxis(0.0, t1_N_steps, t1_time_step) t3axis = qr.TimeAxis(0.0, t3_N_steps, t3_time_step) # # This calculator calculated 2D spectra from the effective width # msc = qr.MockTwoDResponseCalculator(t1axis, time2, t3axis) with qr.energy_units("1/cm"): msc.bootstrap(rwa=E0, shape="Gaussian") # # System-bath interaction including vibrational states # operators = [] rates = [] if use_trimer: print("Relaxation rates: ", rate, rate_sp) with qr.eigenbasis_of(He): if He.data[3, 3] < He.data[2, 2]: Exception("Electronic states not orderred!") operators.append(qr.qm.ProjectionOperator(2, 3, dim=He.dim)) with qr.energy_units("1/cm"): print("2<-3", He.data[2, 2], He.data[3, 3]) rates.append(rate) print("Transfer time B -> SP:", 1.0 / rate) if He.data[2, 2] < He.data[1, 1]: Exception("Electronic states not orderred!") operators.append(qr.qm.ProjectionOperator(1, 2, dim=He.dim)) with qr.energy_units("1/cm"): print("1<-2", He.data[1, 1], He.data[2, 2]) rates.append(rate_sp) print("Transfer time P+ -> P-:", 1.0 / rate_sp) # include detailed balace if detailed_balance: with qr.eigenbasis_of(He): T = INP.temperature #77.0 Den = (He.data[3, 3] - He.data[2, 2]) / (kB_int * T) operators.append(qr.qm.ProjectionOperator(3, 2, dim=He.dim)) thermal_fac = numpy.exp(-Den) rates.append(rate * thermal_fac) else: with qr.eigenbasis_of(He): if He.data[2, 2] < He.data[1, 1]: Exception("Electronic states not orderred!") operators.append(qr.qm.ProjectionOperator(1, 2, dim=He.dim)) rates.append(rate) # include detailed balace if detailed_balance: with qr.eigenbasis_of(He): T = INP.temperature #77.0 Den = (He.data[2, 2] - He.data[1, 1]) / (kB_int * T) operators.append(qr.qm.ProjectionOperator(2, 1, dim=He.dim)) thermal_fac = numpy.exp(-Den) rates.append(rate * thermal_fac) sbi = qr.qm.SystemBathInteraction(sys_operators=operators, rates=rates) sbi.set_system(agg) # # Liouville form for relaxation # LF = qr.qm.ElectronicLindbladForm(HH, sbi, as_operators=True) # # Pure dephasing # p_deph = qr.qm.ElectronicPureDephasing(agg, dtype="Gaussian") # we simplify calculations by converting dephasing to # corresponding Lorentzian form p_deph.convert_to("Lorentzian") eUt = qr.qm.EvolutionSuperOperator(time2, HH, relt=LF, pdeph=p_deph, mode="all") eUt.set_dense_dt(INP.fine_splitting) # # We calculate evolution superoperator # eUt.calculate(show_progress=False) # save the evolution operator if save_eUt: eut_name = os.path.join( dname, "eUt" + "_omega2=" + str(omega) + data_descr + obj_ext) eUt.save(eut_name) # # Prepare aggregate with all states (including 2-EX band) # agg3.build(mult=2) agg3.diagonalize() pways = dict() olow_cm = omega - INP.omega_uncertainty / 2.0 ohigh_cm = omega + INP.omega_uncertainty / 2.0 olow = qr.convert(olow_cm, "1/cm", "int") ohigh = qr.convert(ohigh_cm, "1/cm", "int") for t2 in time2.data: # this could save some memory of pathways become too big pways = dict() print("T2 =", t2) twod = msc.calculate_one_system(t2, agg3, eUt, lab, pways=pways, dtol=1.0e-12, selection=[["omega2", [olow, ohigh]]]) pws = pways[str(t2)] npa = len(pws) print(" p:", npa) has_R = False has_NR = False for pw in pws: if pw.pathway_type == "NR": has_NR = True elif pw.pathway_type == "R": has_R = True print(" R:", has_R, ", NR:", has_NR) if t2 in t2_save_pathways: pws_name = os.path.join( dname, "pws_t2=" + str(t2) + "_omega2=" + str(omega) + data_descr + obj_ext) qr.save_parcel(pways[str(t2)], pws_name) cont_p.set_spectrum(twod) twod = msc.calculate_one_system(t2, agg3, eUt, lab, pways=pways, dtol=1.0e-12, selection=[["omega2", [-ohigh, -olow]]]) pws = pways[str(t2)] npa = len(pws) print(" m:", npa) has_R = False has_NR = False for pw in pws: if pw.pathway_type == "NR": has_NR = True elif pw.pathway_type == "R": has_R = True print(" R:", has_R, ", NR:", has_NR) if t2 in t2_save_pathways: pws_name = os.path.join( dname, "pws_t2=" + str(t2) + "_omega2=" + str(-omega) + data_descr + obj_ext) qr.save_parcel(pways[str(t2)], pws_name) cont_m.set_spectrum(twod) if make_movie: with qr.energy_units("1/cm"): cont_p.make_movie("mov.mp4") # # Save aggregate when a single calculation is done # if save_eUt: fname = os.path.join(dname, "aggregate.qrp") agg3.save(fname) # # Window function for subsequenty FFT # window = func.Tukey(time2, r=INP.tukey_window_r, sym=False) # # FFT with the window function # # Specify REPH, NONR or `total` to get different types of spectra # print("Calculating FFT of the 2D maps") #fcont = cont.fft(window=window, dtype=stype) #, dpart="real", offset=0.0) fcont_p_re = cont_p.fft(window=window, dtype=qr.signal_REPH) fcont_p_nr = cont_p.fft(window=window, dtype=qr.signal_NONR) fcont_p_to = cont_p.fft(window=window, dtype=qr.signal_TOTL) if normalize_maps_to_maximu: fcont_p_re.normalize2(dpart=qr.part_ABS) fcont_p_nr.normalize2(dpart=qr.part_ABS) fcont_p_to.normalize2(dpart=qr.part_ABS) fcont_m_re = cont_m.fft(window=window, dtype=qr.signal_REPH) fcont_m_nr = cont_m.fft(window=window, dtype=qr.signal_NONR) fcont_m_to = cont_m.fft(window=window, dtype=qr.signal_TOTL) if normalize_maps_to_maximu: fcont_m_re.normalize2(dpart=qr.part_ABS) fcont_m_nr.normalize2(dpart=qr.part_ABS) fcont_m_to.normalize2(dpart=qr.part_ABS) if trim_maps: twin = INP.trim_maps_to with qr.energy_units("1/cm"): fcont_p_re.trimall_to(window=twin) fcont_p_nr.trimall_to(window=twin) fcont_p_to.trimall_to(window=twin) show_omega = omega with qr.frequency_units("1/cm"): sp1_p_re, show_Npoint1 = fcont_p_re.get_nearest(show_omega) sp2_p_re, show_Npoint2 = fcont_p_re.get_nearest(-show_omega) sp1_p_nr, show_Npoint1 = fcont_p_nr.get_nearest(show_omega) sp2_p_nr, show_Npoint2 = fcont_p_nr.get_nearest(-show_omega) sp1_p_to, show_Npoint1 = fcont_p_to.get_nearest(show_omega) sp2_p_to, show_Npoint2 = fcont_p_to.get_nearest(-show_omega) sp1_m_re, show_Npoint1 = fcont_m_re.get_nearest(show_omega) sp2_m_re, show_Npoint2 = fcont_m_re.get_nearest(-show_omega) sp1_m_nr, show_Npoint1 = fcont_m_nr.get_nearest(show_omega) sp2_m_nr, show_Npoint2 = fcont_m_nr.get_nearest(-show_omega) sp1_m_to, show_Npoint1 = fcont_m_to.get_nearest(show_omega) sp2_m_to, show_Npoint2 = fcont_m_to.get_nearest(-show_omega) with qr.energy_units(units): if show_plots: # # Spots to look at in detail # with qr.energy_units("1/cm"): with qr.eigenbasis_of(He): Ep_l = He.data[1, 1] Ep_u = He.data[2, 2] Ep = numpy.zeros((4, 2)) Ep[0, 0] = Ep_l Ep[0, 1] = Ep_l Ep[1, 0] = Ep_l Ep[1, 1] = Ep_u Ep[2, 0] = Ep_u Ep[2, 1] = Ep_l Ep[3, 0] = Ep_u Ep[3, 1] = Ep_u print("\nPlotting and saving spectrum at frequency:", fcont_p_re.axis.data[show_Npoint1], units) fftf_1 = os.path.join( dname, "twod_fft" + data_descr + "_stype=REPH" + "_omega=" + str(omega) + data_ext) sp1_p_re.plot(Npos_contours=10, spart=qr.part_ABS, label="Rephasing\n $\omega=" + str(omega) + "$ cm$^{-1}$", text_loc=[0.05, 0.1], show_states=[Ep_l, Ep_u, Ep_u + numpy.abs(omega)], show_diagonal="-k") sp1_p_re.savefig(fftf_1) print("... saved into: ", fftf_1) fftf_2 = os.path.join( dname, "twod_fft" + data_descr + "_stype=NONR" + "_omega=" + str(omega) + data_ext) sp1_p_nr.plot(Npos_contours=10, spart=qr.part_ABS, label="Non-rephasing\n $\omega=" + str(omega) + "$ cm$^{-1}$", text_loc=[0.05, 0.1], show_states=[Ep_l, Ep_u, Ep_u + numpy.abs(omega)], show_diagonal="-k") sp1_p_nr.savefig(fftf_2) print("... saved into: ", fftf_2) fftf_3 = os.path.join( dname, "twod_fft" + data_descr + "_stype=tot" + "_omega=" + str(omega) + data_ext) sp1_p_to.plot(Npos_contours=10, spart=qr.part_ABS, label="Total\n $\omega=" + str(omega) + "$ cm$^{-1}$", text_loc=[0.05, 0.1], show_states=[Ep_l, Ep_u, Ep_u + numpy.abs(omega)], show_diagonal="-k") sp1_p_to.savefig(fftf_3) print("... saved into: ", fftf_3) # # Point evolutions at the expected peak positions # for ii in range(4): points = fcont_p_re.get_point_evolution( Ep[ii, 0], Ep[ii, 1], fcont_p_re.axis) points.apply_to_data(numpy.abs) if ii >= 3: points.plot(show=True) else: points.plot(show=False) print("\nPlotting and saving spectrum at frequency:", fcont_m_re.axis.data[show_Npoint2], units) fftf_4 = os.path.join( dname, "twod_fft" + data_descr + "_stype=REPH" + "_omega=" + str(-omega) + data_ext) sp2_m_re.plot(Npos_contours=10, spart=qr.part_ABS, label="Rephasing\n $\omega=" + str(-omega) + "$ cm$^{-1}$", text_loc=[0.05, 0.1], show_states=[Ep_l, Ep_u, Ep_u + numpy.abs(omega)], show_diagonal="-k") sp2_m_re.savefig(fftf_4) print("... saved into: ", fftf_4) fftf_5 = os.path.join( dname, "twod_fft" + data_descr + "_stype=NONR" + "_omega=" + str(-omega) + data_ext) sp2_m_nr.plot(Npos_contours=10, spart=qr.part_ABS, label="Non-rephasing\n $\omega=" + str(-omega) + "$ cm$^{-1}$", text_loc=[0.05, 0.1], show_states=[Ep_l, Ep_u, Ep_u + numpy.abs(omega)], show_diagonal="-k") sp2_m_nr.savefig(fftf_5) print("... saved into: ", fftf_5) fftf_6 = os.path.join( dname, "twod_fft" + data_descr + "_stype=tot" + "_omega=" + str(-omega) + data_ext) sp2_m_to.plot(Npos_contours=10, spart=qr.part_ABS, label="Total\n $\omega=" + str(-omega) + "$ cm$^{-1}$", text_loc=[0.05, 0.1], show_states=[Ep_l, Ep_u, Ep_u + numpy.abs(omega)], show_diagonal="-k") sp2_m_to.savefig(fftf_6) print("... saved into: ", fftf_6) # # Point evolutions at the expected peak positions # for ii in range(4): points = fcont_p_re.get_point_evolution( Ep[ii, 0], Ep[ii, 1], fcont_m_re.axis) points.apply_to_data(numpy.abs) if ii >= 3: points.plot(show=True) else: points.plot(show=False) save_containers = False if save_containers: fname = os.path.join(dname, "cont_p" + data_descr + obj_ext) print("Saving container into: " + fname) cont_p.save(fname) fname = os.path.join(dname, "cont_m" + data_descr + obj_ext) print("Saving container into: " + fname) cont_m.save(fname) import resource memo = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss / (1024 * 1024) print("Memory usage: ", memo, "in MB") return (sp1_p_re, sp1_p_nr, sp2_m_re, sp2_m_nr)
qr.Manager().gen_conf.legacy_relaxation = True print("Preparing a model system:") with qr.energy_units("1/cm"): mol1 = qr.Molecule([0.0, 12010]) mol2 = qr.Molecule([0.0, 12000]) mol3 = qr.Molecule([0.0, 12100]) mol4 = qr.Molecule([0.0, 12110]) agg = qr.Aggregate([mol1, mol2, mol3, mol4]) agg.set_resonance_coupling(2, 3, qr.convert(100.0, "1/cm", "int")) agg.set_resonance_coupling(1, 3, qr.convert(100.0, "1/cm", "int")) agg.set_resonance_coupling(1, 2, qr.convert(0.0, "1/cm", "int")) qr.save_parcel(agg, "agg.qrp") agg2 = qr.load_parcel("agg.qrp") agg2.build() H = agg2.get_Hamiltonian() print("...done") print("Setting up Lindblad form relaxation:") Ndim = 5 with qr.eigenbasis_of(H): K12 = qr.qm.ProjectionOperator(1, 2, dim=Ndim) K23 = qr.qm.ProjectionOperator(2, 3, dim=Ndim) K34 = qr.qm.ProjectionOperator(3, 4, dim=Ndim) sbi = qr.qm.SystemBathInteraction(sys_operators=[K12, K23, K34], rates=(1.0 / 200, 1.0 / 100.0,
print("Preparing a model system:") with qr.energy_units("1/cm"): mol1 = qr.Molecule([0.0, 12000]) mol2 = qr.Molecule([0.0, 12000]) mol3 = qr.Molecule([0.0, 12100]) mol4 = qr.Molecule([0.0, 12100]) agg = qr.Aggregate([mol1, mol2, mol3, mol4]) agg.set_resonance_coupling(2, 3, qr.convert(100.0, "1/cm", "int")) agg.set_resonance_coupling(1, 3, qr.convert(100.0, "1/cm", "int")) with tempfile.TemporaryDirectory() as tdir: path = os.path.join(tdir, "agg.qrp") qr.save_parcel(agg, path) agg2 = qr.load_parcel(path) agg2.build() H = agg2.get_Hamiltonian() print("...done") print("Setting up Lindblad form relaxation:") Ndim = 5 with qr.eigenbasis_of(H): K12 = qr.qm.ProjectionOperator(1, 2, dim=Ndim) K23 = qr.qm.ProjectionOperator(2, 3, dim=Ndim) K34 = qr.qm.ProjectionOperator(3, 4, dim=Ndim) sbi = qr.qm.SystemBathInteraction(sys_operators=[K12, K23, K34], rates=(1.0 / 200, 1.0 / 100.0,
# THIS MAY BE PARALLELIZED # data_initialized = False disM = numpy.zeros((3, Nreal)) sigma = INP.disorder_fwhm / (2.0 * numpy.sqrt(2.0 * numpy.log(2.0))) if INP.random_state["reset"]: try: random_state = qr.load_parcel(INP.random_state["file"]) numpy.random.set_state(random_state) except: raise Exception("Loading random state failed") if INP.random_state["save"]: random_state = numpy.random.get_state() qr.save_parcel(random_state, INP.random_state["file"]) for ri in range(Nreal): disM[:, ri] = sigma * numpy.random.randn(3) # # PARALLEL (if ON) LOOP OVER DISORDER # for ds in qr.block_distributed_range(0, Nreal): # generating random numbers disE = numpy.zeros(3, dtype=qr.REAL) if Nreal > 1: disE[0] = disM[0, ds] disE[1] = disM[1, ds] disE[2] = disM[2, ds]
qr.Manager().gen_conf.legacy_relaxation = True print("Preparing a model system:") with qr.energy_units("1/cm"): mol1 = qr.Molecule([0.0, 12010]) mol2 = qr.Molecule([0.0, 12000]) mol3 = qr.Molecule([0.0, 12100]) mol4 = qr.Molecule([0.0, 12110]) agg = qr.Aggregate([mol1, mol2, mol3, mol4]) agg.set_resonance_coupling(2,3,qr.convert(100.0,"1/cm","int")) agg.set_resonance_coupling(1,3,qr.convert(100.0,"1/cm","int")) agg.set_resonance_coupling(1,2,qr.convert(0.0,"1/cm","int")) qr.save_parcel(agg,"agg.qrp") agg2 = qr.load_parcel("agg.qrp") agg2.build() H = agg2.get_Hamiltonian() print("...done") print("Setting up Lindblad form relaxation:") Ndim = 5 with qr.eigenbasis_of(H): K12 = qr.qm.ProjectionOperator(1, 2, dim=Ndim) K23 = qr.qm.ProjectionOperator(2, 3, dim=Ndim) K34 = qr.qm.ProjectionOperator(3, 4, dim=Ndim) sbi = qr.qm.SystemBathInteraction(sys_operators=[K12, K23, K34],
def run(omega, HR, dE, JJ, rate, E0, vib_loc="up", use_vib=True, detailed_balance=False, temperature=77.0, stype=qr.signal_REPH, save_eUt=False, t2_save_pathways=[], dname=None, trimer=None, disE=None): """Runs a complete set of simulations for a single set of parameters If disE is not None it tries to run averaging over Gaussian energetic disorder. """ if dname is None: dname = "sim_" + vib_loc use_trimer = trimer["useit"] rate_sp = trimer["rate"] # # PARAMETERS FROM INPUT FILE # dip1 = INP.dip1 # [1.5, 0.0, 0.0] dip2 = INP.dip2 # [-1.0, -1.0, 0.0] width = INP.feature_width # 100.0 width2 = INP.feature_width2 normalize_maps_to_maximu = False trim_maps = False units = "1/cm" with qr.energy_units(units): data_descr = "_dO="+str(dE)+"_omega="+str(omega)+ \ "_HR="+str(HR)+"_J="+str(JJ) if use_vib: sys_char = "_vib" else: sys_char = "_ele" data_ext = sys_char + ".png" obj_ext = sys_char + ".qrp" # parameters of the SP if use_trimer: E2 = trimer["E2"] epsa = (E0 + E2) / 2.0 DE = trimer["DE"] J2 = 0.5 * numpy.sqrt(((E0 - E2)**2) - (DE**2)) ESP2 = epsa + DE / 2.0 ESP1 = epsa - DE / 2.0 # # Model system is a dimer of molecules # with qr.energy_units("1/cm"): if not use_trimer: if disE is not None: mol1 = qr.Molecule([0.0, E0 + disE[0]]) mol2 = qr.Molecule([0.0, E0 + dE + disE[1]]) print("Monomer 1 energy:", E0 + disE[0], "1/cm") print("Monomer 2 energy:", E0 + dE + disE[1], "1/cm") else: mol1 = qr.Molecule([0.0, E0]) mol2 = qr.Molecule([0.0, E0 + dE]) print("Monomer 1 energy:", E0, "1/cm") print("Monomer 2 energy:", E0 + dE, "1/cm") else: if disE is not None: mol1 = qr.Molecule([0.0, ESP2 + disE[0]]) mol2 = qr.Molecule([0.0, E0 + dE + disE[1]]) print("Monomer 1 (SP_high) energy:", ESP2 + disE[0], "1/cm") print("Monomer 2 (B) energy:", E0 + dE + disE[1], "1/cm") else: mol1 = qr.Molecule([0.0, ESP2]) mol2 = qr.Molecule([0.0, E0 + dE]) print("Monomer 1 (SP_high) energy:", ESP2, "1/cm") print("Monomer 2 (B) energy:", E0 + dE, "1/cm") if disE is not None: mol3 = qr.Molecule([0.0, ESP1 + disE[2]]) print("Monomer 3 (SP_low) energy:", ESP1 + disE[2], "1/cm") else: mol3 = qr.Molecule([0.0, ESP1]) print("Monomer 3 (SP_low) energy:", ESP1, "1/cm") mol3.set_transition_width((0, 1), width2) mol3.set_dipole(0, 1, trimer["dipsp"]) mol1.set_transition_width((0, 1), width2) mol1.set_dipole(0, 1, dip1) mol2.set_transition_width((0, 1), width) mol2.set_dipole(0, 1, dip2) if use_trimer: agg = qr.Aggregate([mol1, mol2, mol3]) else: agg = qr.Aggregate([mol1, mol2]) if use_trimer: with qr.energy_units("1/cm"): agg.set_resonance_coupling(0, 1, JJ) print("B - SP_high coupling:", JJ, "1/cm") agg.set_resonance_coupling(0, 2, J2) print("SP coupling:", J2, "1/cm") else: with qr.energy_units("1/cm"): agg.set_resonance_coupling(0, 1, JJ) # # Electronic only aggregate # agg_el = agg.deepcopy() # # if nuclear vibrations are to be added, do it here # if use_vib: with qr.energy_units("1/cm"): mod1 = qr.Mode(omega) mod2 = qr.Mode(omega) if vib_loc == "down": set_vib = [True, False] elif vib_loc == "up": set_vib = [False, True] elif vib_loc == "both": set_vib = [True, True] else: raise Exception("Unknown location of the vibrations") if set_vib[0]: print("Vibrations set for SP_high molecule") mol1.add_Mode(mod1) mod1.set_nmax(0, INP.vibmode["no_g_vib"]) mod1.set_nmax(1, INP.vibmode["no_e_vib"]) mod1.set_HR(1, HR) if set_vib[1]: print("Vibrations set for B molecule") mol2.add_Mode(mod2) mod2.set_nmax(0, INP.vibmode["no_g_vib"]) mod2.set_nmax(1, INP.vibmode["no_e_vib"]) mod2.set_HR(1, HR) # # Before we build the aggregate, we make its copy to have an unbuilt version # agg3 = agg.deepcopy() aggA = agg.deepcopy() # # here we build the complete aggregate and its electronic only version # agg.build(mult=1) agg_el.build(mult=1) aggA.build(mult=1) # total Hamiltonian HH = agg.get_Hamiltonian() # electronic Hamiltonian He = agg_el.get_Hamiltonian() # # Laboratory setup # lab = qr.LabSetup() lab.set_polarizations(pulse_polarizations=[X, X, X], detection_polarization=X) # # Time axis for the calculation of excited state evolution # t2_N_steps = INP.t2_N_steps t2_time_step = INP.t2_time_step time2 = qr.TimeAxis(0.0, t2_N_steps, t2_time_step) # # Containers for 2D maps with positive and negative frequencies # cont_p = qr.TwoDResponseContainer(t2axis=time2) cont_m = qr.TwoDResponseContainer(t2axis=time2) cont_tot = qr.TwoDResponseContainer(t2axis=time2) # # spectra will be indexed by the times in the time axis `time2` # cont_p.use_indexing_type(time2) cont_m.use_indexing_type(time2) cont_tot.use_indexing_type(time2) # # We define two-time axes, which will be FFTed and will define # the omega_1 and omega_3 axes of the 2D spectrum # t1_N_steps = INP.t1_N_steps t1_time_step = INP.t1_time_step t3_N_steps = INP.t3_N_steps t3_time_step = INP.t3_time_step t1axis = qr.TimeAxis(0.0, t1_N_steps, t1_time_step) t3axis = qr.TimeAxis(0.0, t3_N_steps, t3_time_step) # # This calculator calculated 2D spectra from the effective width # msc = qr.MockTwoDResponseCalculator(t1axis, time2, t3axis) with qr.energy_units("1/cm"): msc.bootstrap(rwa=E0, shape="Gaussian") # # System-bath interaction including vibrational states # operators = [] rates = [] print("Relaxation rates: ", rate, rate_sp, "1/fs") with qr.eigenbasis_of(He): if use_trimer: if He.data[3, 3] < He.data[2, 2]: Exception("Electronic states not orderred!") operators.append(qr.qm.ProjectionOperator(2, 3, dim=He.dim)) with qr.energy_units("1/cm"): print("2 <- 3 : energies = ", He.data[2, 2], He.data[3, 3], "1/cm") rates.append(rate) print("Transfer time 2 <- 3:", 1.0 / rate, "fs") if He.data[2, 2] < He.data[1, 1]: Exception("Electronic states not orderred!") operators.append(qr.qm.ProjectionOperator(1, 2, dim=He.dim)) with qr.energy_units("1/cm"): print("1 <- 2 : energies = ", He.data[1, 1], He.data[2, 2], "1/cm") rates.append(rate_sp) print("Transfer time 1 <- 2", 1.0 / rate_sp, "fs") else: if He.data[2, 2] < He.data[1, 1]: Exception("Electronic states not orderred!") operators.append(qr.qm.ProjectionOperator(1, 2, dim=He.dim)) with qr.energy_units("1/cm"): print("1 <- 2 : energies = ", He.data[1, 1], He.data[2, 2], "1/cm") rates.append(rate_sp) print("Transfer time 1 <- 2", 1.0 / rate, "fs") # include detailed balace if detailed_balance: if use_trimer: with qr.eigenbasis_of(He): T = temperature #77.0 Den = (He.data[3, 3] - He.data[2, 2]) / (kB_int * T) operators.append(qr.qm.ProjectionOperator(3, 2, dim=He.dim)) thermal_fac = numpy.exp(-Den) rates.append(rate * thermal_fac) Den = (He.data[2, 2] - He.data[1, 1]) / (kB_int * T) operators.append(qr.qm.ProjectionOperator(2, 1, dim=He.dim)) thermal_fac = numpy.exp(-Den) rates.append(rate_sp * thermal_fac) else: with qr.eigenbasis_of(He): T = temperature #77.0 Den = (He.data[2, 2] - He.data[1, 1]) / (kB_int * T) operators.append(qr.qm.ProjectionOperator(2, 1, dim=He.dim)) thermal_fac = numpy.exp(-Den) rates.append(rate * thermal_fac) sbi = qr.qm.SystemBathInteraction(sys_operators=operators, rates=rates) sbi.set_system(agg) # # Lindblad form for relaxation # LF = qr.qm.ElectronicLindbladForm(HH, sbi, as_operators=True) # # Pure dephasing # p_deph = qr.qm.ElectronicPureDephasing(agg, dtype="Gaussian") # we simplify calculations by converting dephasing to # corresponding Lorentzian form p_deph.convert_to("Lorentzian") eUt = qr.qm.EvolutionSuperOperator(time2, HH, relt=LF, pdeph=p_deph, mode="all") eUt.set_dense_dt(INP.fine_splitting) print("---") # # We calculate evolution superoperator # eUt.calculate(show_progress=False) # save the evolution operator if save_eUt: eut_name = os.path.join( dname, "eUt" + "_omega2=" + str(omega) + data_descr + obj_ext) eUt.save(eut_name) # # Prepare aggregate with all states (including 2-EX band) # agg3.build(mult=2) agg3.diagonalize() agg_el.diagonalize() print("") print("Square of the transition dipoles") print(agg_el.D2) print("") print("---") # # calculation of absorption spectrum # time1 = qr.TimeAxis(0.0, 1000, 5.0) absc = qr.MockAbsSpectrumCalculator(time1, system=aggA) with qr.energy_units("1/cm"): absc.bootstrap(rwa=E0) spctrm = absc.calculate() spctrm.normalize2() with qr.energy_units("1/cm"): spctrm.plot(show=False, axis=[10500.0, 13500.0, 0.0, 1.1]) spctrm.savefig(os.path.join(dname, "abs.png")) spctrm.save_data(os.path.join(dname, "abs.dat")) pways = dict() olow_cm = omega - INP.omega_uncertainty / 2.0 ohigh_cm = omega + INP.omega_uncertainty / 2.0 olow = qr.convert(olow_cm, "1/cm", "int") ohigh = qr.convert(ohigh_cm, "1/cm", "int") for t2 in time2.data: # this could save some memory of pathways become too big pways = dict() print("T2 =", t2, "fs (of T2_max =", time2.max, "fs)") twod = msc.calculate_one_system(t2, agg3, eUt, lab, pways=pways, dtol=1.0e-12, selection=[["omega2", [olow, ohigh]]]) pws = pways[str(t2)] npa = len(pws) has_R = False has_NR = False for pw in pws: if pw.pathway_type == "NR": has_NR = True elif pw.pathway_type == "R": has_R = True if t2 in t2_save_pathways: pws_name = os.path.join( dname, "pws_t2=" + str(t2) + "_omega2=" + str(omega) + data_descr + obj_ext) qr.save_parcel(pways[str(t2)], pws_name) cont_p.set_spectrum(twod) twod = msc.calculate_one_system(t2, agg3, eUt, lab, pways=pways, dtol=1.0e-12, selection=[["omega2", [-ohigh, -olow]]]) pws = pways[str(t2)] npa = len(pws) #print(" m:", npa) has_R = False has_NR = False for pw in pws: if pw.pathway_type == "NR": has_NR = True elif pw.pathway_type == "R": has_R = True #print(" R:", has_R, ", NR:", has_NR) if t2 in t2_save_pathways: pws_name = os.path.join( dname, "pws_t2=" + str(t2) + "_omega2=" + str(-omega) + data_descr + obj_ext) qr.save_parcel(pways[str(t2)], pws_name) cont_m.set_spectrum(twod) # calculation without pre-selecting pathways twod = msc.calculate_one_system(t2, agg3, eUt, lab, pways=pways, dtol=1.0e-12) cont_tot.set_spectrum(twod) # saving total spectrum to a directory for further analysis try: saveit = INP.total_spectrum["save_it"] except: saveit = False if saveit: try: dform = INP.total_spectrum["data_format"] except: dform = "dat" try: stp = INP.total_spectrum["spectra_type"] if stp == "TOTL": stype = qr.signal_TOTL elif stp == "REPH": stype = qr.signal_REPH elif stp == "NONR": stype = qr.signal_NONR else: raise Exception("Wrong signal type") except: stype = qr.signal_REPH save_spectra(cont_tot, ext=dform, dir=dname, stype=stype) # # Save aggregate when a single calculation is done # if save_eUt: fname = os.path.join(dname, "aggregate.qrp") agg3.save(fname) # # Window function for subsequenty FFT # window = func.Tukey(time2, r=INP.tukey_window_r, sym=False) # # FFT with the window function # # Specify REPH, NONR or `total` to get different types of spectra # print("Calculating FFT of the 2D maps") #fcont = cont.fft(window=window, dtype=stype) #, dpart="real", offset=0.0) fcont_p_re = cont_p.fft(window=window, dtype=qr.signal_REPH) fcont_p_nr = cont_p.fft(window=window, dtype=qr.signal_NONR) fcont_p_to = cont_p.fft(window=window, dtype=qr.signal_TOTL) if normalize_maps_to_maximu: fcont_p_re.normalize2(dpart=qr.part_ABS) fcont_p_nr.normalize2(dpart=qr.part_ABS) fcont_p_to.normalize2(dpart=qr.part_ABS) fcont_m_re = cont_m.fft(window=window, dtype=qr.signal_REPH) fcont_m_nr = cont_m.fft(window=window, dtype=qr.signal_NONR) fcont_m_to = cont_m.fft(window=window, dtype=qr.signal_TOTL) if normalize_maps_to_maximu: fcont_m_re.normalize2(dpart=qr.part_ABS) fcont_m_nr.normalize2(dpart=qr.part_ABS) fcont_m_to.normalize2(dpart=qr.part_ABS) if trim_maps: twin = INP.trim_maps_to with qr.energy_units("1/cm"): fcont_p_re.trimall_to(window=twin) fcont_p_nr.trimall_to(window=twin) fcont_p_to.trimall_to(window=twin) show_omega = omega with qr.frequency_units("1/cm"): sp1_p_re, show_Npoint1 = fcont_p_re.get_nearest(show_omega) sp2_p_re, show_Npoint2 = fcont_p_re.get_nearest(-show_omega) sp1_p_nr, show_Npoint1 = fcont_p_nr.get_nearest(show_omega) sp2_p_nr, show_Npoint2 = fcont_p_nr.get_nearest(-show_omega) sp1_p_to, show_Npoint1 = fcont_p_to.get_nearest(show_omega) sp2_p_to, show_Npoint2 = fcont_p_to.get_nearest(-show_omega) sp1_m_re, show_Npoint1 = fcont_m_re.get_nearest(show_omega) sp2_m_re, show_Npoint2 = fcont_m_re.get_nearest(-show_omega) sp1_m_nr, show_Npoint1 = fcont_m_nr.get_nearest(show_omega) sp2_m_nr, show_Npoint2 = fcont_m_nr.get_nearest(-show_omega) sp1_m_to, show_Npoint1 = fcont_m_to.get_nearest(show_omega) sp2_m_to, show_Npoint2 = fcont_m_to.get_nearest(-show_omega) sstm = platform.system() #print(sstm) if sstm != "Windows": import resource memo = resource.getrusage( resource.RUSAGE_SELF).ru_maxrss / (1024 * 1024) print("Memory usage: ", memo, "in MB") return (sp1_p_re, sp1_p_nr, sp2_m_re, sp2_m_nr)
PL.set_dipole(0,1, dPL) BL.set_dipole(0,1, [ 0.7782, 0.5332, 0.3317]) BM.set_dipole(0,1, [-0.9681, 0.1107, 0.2249]) HL.set_dipole(0,1, dHL) HM.set_dipole(0,1, dHM) # # CT states are dark # PCT_M.set_dipole(1, 0, [0.0, 0.0, 0.0]) PCT_L.set_dipole(1, 0, [0.0, 0.0, 0.0]) molecules = [PM, PL, BM, BL, HL, HM, PCT_M, PCT_L] # saving molecules without environment qr.save_parcel(molecules, os.path.join(pre_out,"molecules.qrp")) # # Here we build the RC as an aggregate of molecules # mol3 = [PM, PL, BM] agg = qr.Aggregate(molecules=mol3) # # Exciton interaction matrix # # values from Ref. 1 JP_77K_Jordanides = 575.0 JP_77K = JP_77K_Jordanides
PL.set_dipole(0, 1, dPL) BL.set_dipole(0, 1, [0.7782, 0.5332, 0.3317]) BM.set_dipole(0, 1, [-0.9681, 0.1107, 0.2249]) HL.set_dipole(0, 1, dHL) HM.set_dipole(0, 1, dHM) # # CT states are dark # PCT_M.set_dipole(1, 0, [0.0, 0.0, 0.0]) PCT_L.set_dipole(1, 0, [0.0, 0.0, 0.0]) molecules = [PM, PL, BM, BL, HL, HM, PCT_M, PCT_L] # saving molecules without environment qr.save_parcel(molecules, os.path.join(pre_out, "molecules.qrp")) # # Here we build the RC as an aggregate of molecules # mol3 = [PM, PL, BM] agg = qr.Aggregate(molecules=mol3) # # Exciton interaction matrix # # values from Ref. 1 JP_77K_Jordanides = 575.0 JP_77K = JP_77K_Jordanides
mod_BL.set_HR(1, HRF) if include_second_B and vib_at_second_B: BM.add_Mode(mod_BM) mod_BM.set_nmax(0, Nmax_g) mod_BM.set_nmax(1, Nmax_e) mod_BM.set_HR(1, HRF) # In[30]: print(BL) # In[31]: #frac.save("fraction_45_2_vibrations_CT_unbuilt.hdf5") qr.save_parcel( frac, os.path.join(pre_out, "fraction_45_2_vibrations_CT_unbuilt.qrp")) # In[32]: # # Building the aggregate with approximations in vibrational manifold # frac.build(vibgen_approx="NPA", Nvib=2, mult=2) # NPA with Nvib=2 is equivalent to vibgen_approx="TPA" frac_electronic.build(mult=2) # In[33]: print("Total number of states:", frac.Ntot) print("Dim :", frac.get_Hamiltonian().data.shape) print("Total number of electronic states:", frac.Nel, frac_electronic.Ntot)
for mol_name in transition_widths: width = qr.convert(transition_widths[mol_name], "1/cm", "int") mol = agg2.get_Molecule_by_name(mol_name) mol.set_transition_width((0,1), width) print("Aggregate has ", agg2.nmono, "single excited electronic states") agg2.build(mult=2, vibgen_approx="TPA") print("and ", agg2.Ntot, " (electro-vibrational) states in total") print("Number of single exciton states :", agg2.Nb[0]+agg2.Nb[1]) qr.save_parcel(agg2, os.path.join(pre_out,"agg2_built.qrp")) # # Electronic aggregate is built with single exciton states only # for mol_name in transition_widths: width = qr.convert(transition_widths[mol_name], "1/cm", "int") mol = agg_el.get_Molecule_by_name(mol_name) mol.set_transition_width((0,1), width) print("Aggregate has ", agg_el.nmono, "single excited electronic states") agg_el.build(mult=1) HHe = agg_el.get_Hamiltonian()
def run(omega, HR, dE, JJ, rate, vib_loc="up", use_vib=True, stype=qr.signal_REPH, make_movie=False): """Runs a complete set of simulations for a single set of parameters """ # # FIXED PARAMETERS # E0 = 10000.0 dip1 = [1.5, 0.0, 0.0] dip2 = [-1.0, -1.0, 0.0] width = 100.0 #rate = 1.0/50.0 normalize_maps_to_maximu = False trim_maps = False units = "1/cm" with qr.energy_units(units): data_descr = "_dO="+str(dE-omega)+"_HR="+str(HR)+"_J="+str(JJ) if use_vib: sys_char = "_vib" else: sys_char = "_ele" data_ext = sys_char+".png" obj_ext = sys_char+".qrp" # # Model system is a dimer of molecules # with qr.energy_units("1/cm"): mol1 = qr.Molecule([0.0, E0]) mol2 = qr.Molecule([0.0, E0+dE]) mod1 = qr.Mode(omega) mod2 = qr.Mode(omega) mol1.set_transition_width((0,1), qr.convert(width, "1/cm", "int")) mol1.set_dipole(0,1, dip1) mol2.set_transition_width((0,1), qr.convert(width, "1/cm", "int")) mol2.set_dipole(0,1, dip2) agg = qr.Aggregate([mol1, mol2]) with qr.energy_units("1/cm"): agg.set_resonance_coupling(0,1,JJ) # # Electronic only aggregate # agg_el = agg.deepcopy() # # if nuclear vibrations are to be added, do it here # if use_vib: if vib_loc == "down": set_vib = [True, False] elif vib_loc == "up": set_vib = [False, True] elif vib_loc == "both": set_vib = [True, True] else: raise Exception("Unknown location of the vibrations") if set_vib[0]: mol1.add_Mode(mod1) mod1.set_nmax(0, 3) mod1.set_nmax(1, 3) mod1.set_HR(1, HR) if set_vib[1]: mol2.add_Mode(mod2) mod2.set_nmax(0, 3) mod2.set_nmax(1, 3) mod2.set_HR(1, HR) agg3 = agg.deepcopy() agg.build(mult=1) agg_el.build(mult=1) HH = agg.get_Hamiltonian() He = agg_el.get_Hamiltonian() with qr.energy_units("1/cm"): with qr.eigenbasis_of(He): Ep_l = He.data[1,1] Ep_u = He.data[2,2] Ep = numpy.zeros((4,2)) Ep[0,0] = Ep_l Ep[0,1] = Ep_l Ep[1,0] = Ep_l Ep[1,1] = Ep_u Ep[2,0] = Ep_u Ep[2,1] = Ep_l Ep[3,0] = Ep_u Ep[3,1] = Ep_u # # Laboratory setup # lab = qr.LabSetup() lab.set_polarizations(pulse_polarizations=[X,X,X], detection_polarization=X) time2 = qr.TimeAxis(0.0, 100, 10.0) cont_p = qr.TwoDResponseContainer(t2axis=time2) cont_m = qr.TwoDResponseContainer(t2axis=time2) # # spectra will be indexed by the times in the time axis `time2` # cont_p.use_indexing_type(time2) # # We define two-time axes, which will be FFTed and will define # the omega_1 and omega_3 axes of the 2D spectrum # t1_N_steps = 100 t1_time_step = 10.0 t3_N_steps = 100 t3_time_step = 10.0 t1axis = qr.TimeAxis(0.0, t1_N_steps, t1_time_step) t3axis = qr.TimeAxis(0.0, t3_N_steps, t3_time_step) # # This calculator calculated 2D spectra from the effective width # msc = qr.MockTwoDResponseCalculator(t1axis, time2, t3axis) with qr.energy_units("1/cm"): msc.bootstrap(rwa=E0, shape="Gaussian") # # System-bath interaction including vibrational states # operators = [] rates = [] with qr.eigenbasis_of(He): operators.append(qr.qm.ProjectionOperator(1, 2, dim=He.dim)) rates.append(rate) sbi = qr.qm.SystemBathInteraction(sys_operators=operators, rates=rates) sbi.set_system(agg) # # Liouville form for relaxation # LF = qr.qm.ElectronicLindbladForm(HH, sbi, as_operators=True) # # Pure dephasing # p_deph = qr.qm.ElectronicPureDephasing(agg, dtype="Gaussian") eUt = qr.qm.EvolutionSuperOperator(time2, HH, relt=LF, pdeph=p_deph, mode="all") eUt.set_dense_dt(10) # # We calculate evolution superoperator # eUt.calculate(show_progress=False) # # Prepare aggregate with all states (including 2-EX band) # agg3.build(mult=2) agg3.diagonalize() pways = dict() t2_save_pathways = [300.0] olow = qr.convert(omega-30.0, "1/cm", "int") ohigh = qr.convert(omega+30.0, "1/cm", "int") for t2 in time2.data: # this could save some memory of pathways become too big pways = dict() print("t2 =", t2) twod = msc.calculate_one_system(t2, agg3, eUt, lab, pways=pways, selection=[["omega2",[olow, ohigh]]]) print("Number of pathways used for omega2 =",omega,":", len(pways[str(t2)])) if t2 in t2_save_pathways: pws_name = os.path.join("sim_"+vib_loc, "pws_t2="+str(t2)+ "_omega2="+str(omega)+data_descr+data_ext) qr.save_parcel(pways[str(t2)], pws_name) cont_p.set_spectrum(twod) twod = msc.calculate_one_system(t2, agg3, eUt, lab, pways=pways, selection=[["omega2",[-ohigh, -olow]]]) print("Number of pathways used for omega2 =",-omega,":", len(pways[str(t2)])) if t2 in t2_save_pathways: pws_name = os.path.join("sim_"+vib_loc, "pws_t2="+str(t2)+ "_omega2="+str(-omega)+data_descr+data_ext) qr.save_parcel(pways[str(t2)], pws_name) cont_m.set_spectrum(twod) if make_movie: with qr.energy_units("1/cm"): cont_p.make_movie("mov.mp4") fname = os.path.join("sim_"+vib_loc, "pways.qrp") qr.save_parcel(pways, fname) fname = os.path.join("sim_"+vib_loc, "aggregate.qrp") agg3.save(fname) # # Window function for subsequenty FFT # window = func.Tukey(time2, r=0.3, sym=False) # # FFT with the window function # # Specify REPH, NONR or `total` to get different types of spectra # print("\nCalculating FFT of the 2D maps") #fcont = cont.fft(window=window, dtype=stype) #, dpart="real", offset=0.0) fcont_p_re = cont_p.fft(window=window, dtype=qr.signal_REPH) fcont_p_nr = cont_p.fft(window=window, dtype=qr.signal_NONR) fcont_p_to = cont_p.fft(window=window, dtype=qr.signal_TOTL) if normalize_maps_to_maximu: fcont_p_re.normalize2(dpart=qr.part_ABS) fcont_p_nr.normalize2(dpart=qr.part_ABS) fcont_p_to.normalize2(dpart=qr.part_ABS) fcont_m_re = cont_m.fft(window=window, dtype=qr.signal_REPH) fcont_m_nr = cont_m.fft(window=window, dtype=qr.signal_NONR) fcont_m_to = cont_m.fft(window=window, dtype=qr.signal_TOTL) if normalize_maps_to_maximu: fcont_m_re.normalize2(dpart=qr.part_ABS) fcont_m_nr.normalize2(dpart=qr.part_ABS) fcont_m_to.normalize2(dpart=qr.part_ABS) if trim_maps: twin = [9500, 11000, 9500, 11000] with qr.energy_units("1/cm"): fcont_p_re.trimall_to(window=twin) fcont_p_nr.trimall_to(window=twin) fcont_p_to.trimall_to(window=twin) show_omega = omega # # Have a look which frequencies we actually have # # Ndat = len(fcont_re.axis.data) # print("\nNumber of frequency points:", Ndat) # print("In 1/cm they are:") # with qr.energy_units("1/cm"): # for k_i in range(Ndat): # print(k_i, fcont_re.axis.data[k_i]) with qr.frequency_units("1/cm"): sp1_p_re, show_Npoint1 = fcont_p_re.get_nearest(show_omega) sp2_p_re, show_Npoint2 = fcont_p_re.get_nearest(-show_omega) sp1_p_nr, show_Npoint1 = fcont_p_nr.get_nearest(show_omega) sp2_p_nr, show_Npoint2 = fcont_p_nr.get_nearest(-show_omega) sp1_p_to, show_Npoint1 = fcont_p_to.get_nearest(show_omega) sp2_p_to, show_Npoint2 = fcont_p_to.get_nearest(-show_omega) sp1_m_re, show_Npoint1 = fcont_m_re.get_nearest(show_omega) sp2_m_re, show_Npoint2 = fcont_m_re.get_nearest(-show_omega) sp1_m_nr, show_Npoint1 = fcont_m_nr.get_nearest(show_omega) sp2_m_nr, show_Npoint2 = fcont_m_nr.get_nearest(-show_omega) sp1_m_to, show_Npoint1 = fcont_m_to.get_nearest(show_omega) sp2_m_to, show_Npoint2 = fcont_m_to.get_nearest(-show_omega) # units = "1/cm" # with qr.energy_units(units): # # data_descr = "_dO="+str(dE-omega)+"_HR="+str(HR)+"_J="+str(JJ) # # if use_vib: # sys_char = "_vib" # else: # sys_char = "_ele" # data_ext = sys_char+".png" # obj_ext = sys_char+".qrp" with qr.energy_units(units): print("\nPlotting and saving spectrum at frequency:", fcont_p_re.axis.data[show_Npoint1], units) fftf_1 = os.path.join("sim_"+vib_loc, "twod_fft"+data_descr+ "_stype=REPH"+"_omega="+str(omega)+data_ext) sp1_p_re.plot(Npos_contours=10, spart=qr.part_ABS, label="Rephasing\n $\omega="+str(omega)+ "$ cm$^{-1}$", text_loc=[0.05,0.1], show_states=[Ep_l, Ep_u, Ep_u+numpy.abs(omega)], show_diagonal="-k") sp1_p_re.savefig(fftf_1) print("... saved into: ", fftf_1) fftf_2 = os.path.join("sim_"+vib_loc, "twod_fft"+data_descr+ "_stype=NONR"+"_omega="+str(omega)+data_ext) sp1_p_nr.plot(Npos_contours=10, spart=qr.part_ABS, label="Non-rephasing\n $\omega="+str(omega)+ "$ cm$^{-1}$", text_loc=[0.05,0.1], show_states=[Ep_l, Ep_u, Ep_u+numpy.abs(omega)], show_diagonal="-k") sp1_p_nr.savefig(fftf_2) print("... saved into: ", fftf_2) fftf_3 = os.path.join("sim_"+vib_loc, "twod_fft"+data_descr+ "_stype=tot"+"_omega="+str(omega)+data_ext) sp1_p_to.plot(Npos_contours=10, spart=qr.part_ABS, label="Total\n $\omega="+str(omega)+ "$ cm$^{-1}$", text_loc=[0.05,0.1], show_states=[Ep_l, Ep_u, Ep_u+numpy.abs(omega)], show_diagonal="-k") sp1_p_to.savefig(fftf_3) print("... saved into: ", fftf_3) # # Point evolutions at the expected peak positions # if show_plots: for ii in range(4): points = fcont_p_re.get_point_evolution(Ep[ii,0], Ep[ii,1], fcont_p_re.axis) points.apply_to_data(numpy.abs) if ii >= 3: points.plot(show=True) else: points.plot(show=False) print("\nPlotting and saving spectrum at frequency:", fcont_m_re.axis.data[show_Npoint2], units) fftf_4 = os.path.join("sim_"+vib_loc, "twod_fft"+data_descr+ "_stype=REPH"+"_omega="+str(-omega)+data_ext) sp2_m_re.plot(Npos_contours=10, spart=qr.part_ABS, label="Rephasing\n $\omega="+str(-omega)+ "$ cm$^{-1}$", text_loc=[0.05,0.1], show_states=[Ep_l, Ep_u, Ep_u+numpy.abs(omega)], show_diagonal="-k") sp2_m_re.savefig(fftf_4) print("... saved into: ", fftf_4) fftf_5 = os.path.join("sim_"+vib_loc, "twod_fft"+data_descr+ "_stype=NONR"+"_omega="+str(-omega)+data_ext) sp2_m_nr.plot(Npos_contours=10, spart=qr.part_ABS, label="Non-rephasing\n $\omega="+str(-omega)+ "$ cm$^{-1}$", text_loc=[0.05,0.1], show_states=[Ep_l, Ep_u, Ep_u+numpy.abs(omega)], show_diagonal="-k") sp2_m_nr.savefig(fftf_5) print("... saved into: ", fftf_5) fftf_6 = os.path.join("sim_"+vib_loc, "twod_fft"+data_descr+ "_stype=tot"+"_omega="+str(-omega)+data_ext) sp2_m_to.plot(Npos_contours=10, spart=qr.part_ABS, label="Total\n $\omega="+str(-omega)+ "$ cm$^{-1}$", text_loc=[0.05,0.1], show_states=[Ep_l, Ep_u, Ep_u+numpy.abs(omega)], show_diagonal="-k") sp2_m_to.savefig(fftf_6) print("... saved into: ", fftf_6) if show_plots: # # Point evolutions at the expected peak positions # for ii in range(4): points = fcont_p_re.get_point_evolution(Ep[ii,0], Ep[ii,1], fcont_m_re.axis) points.apply_to_data(numpy.abs) if ii >= 3: points.plot(show=True) else: points.plot(show=False) #points.apply_to_data(numpy.abs) #points.plot() # saving containers # fname = os.path.join("sim_"+vib_loc,"fcont_re"+data_descr+obj_ext) # print("Saving container into: "+fname) # fcont_p_re.save(fname) # fname = os.path.join("sim_"+vib_loc,"fcont_nr"+data_descr+obj_ext) # print("Saving container into: "+fname) # fcont_p_nr.save(fname) # fname = os.path.join("sim_"+vib_loc,"fcont_to"+data_descr+obj_ext) # print("Saving container into: "+fname) # fcont_p_to.save(fname) fname = os.path.join("sim_"+vib_loc,"cont_p"+data_descr+obj_ext) print("Saving container into: "+fname) cont_p.save(fname) fname = os.path.join("sim_"+vib_loc,"cont_m"+data_descr+obj_ext) print("Saving container into: "+fname) cont_m.save(fname) return (sp1_p_re, sp1_p_nr, sp2_m_re, sp2_m_nr)