Main text figure data and scripts for "Simulating optical linear absorption for mesoscale molecular aggregates: an adaptive hierarchy of pure states approach"

(as README.txt):

Main text figure data and scripts for “Simulating optical linear absorption for mesoscale molecular aggregates: an adaptive hierarchy of pure states approach”, by Tarun Gera, Lipeng Chen, Alex Eisfeld, Jeffrey R. Reimers, Elliot J. Taffet and Doran I. G. B. Raccah.

Each directory is dedicated to a particular figure published in the paper. In each directory there are sub-directories which contains the data plotted in each panel. Each data file is a 2-D list in the format of (x,y) for each plot. There are python scripts (Fig_X.py) in each directory to plot the data.

Table of contents:

Figure_2:

    - 4_site_edge_contri.npy: Calculated edge sites contribution to the total absorption spectrum for a 4-site chain system v/s energy. 
    - 4_site_inner_contri.npy: Calculated inner sites contribution to the total absorption spectrum for a 4-site chain system v/s energy. 
    - 4_site_total_spectra.npy: Calculated total absorption spectrum for a 4-site chain system v/s energy.  

Figure_3:

Panel A:

    - Mean_Error_Edge.npy: Mean error for the edge case v/s number of trajectories.
    - Mean_Error_Inner.npy: Mean error for the inner case v/s number of trajectories.
    - Mean_Error_SS.npy: Mean error for a single site initial condition v/s number of trajectories.
    - Mean_Error_GD.npy: Mean error for a 4-site chain system with Gaussian distributed site energies v/s number of trajectories.

Panel B: 

    - Scaled_error_SS.npy:  Mean error for a single site initial condition normalized by the square-root of one v/s number of trajectories.
    - Scaled_error_PS.npy:  Mean error for a pair site initial condition normalized by the square-root of two v/s number of trajectories.
    - Scaled_error_AS.npy:  Mean error for an all site initial condition normalized by the square-root of four v/s number of trajectories.

Figure_4: 

Panel_A:

    - List_Error.npy: Calculated mean error for a 4-site chain for a set of auxiliary error bounds.

Panel_B:

    - Cw_4S_HOPS.npy: Absorption spectrum for a 4-site chain calculated using dyadic HOPS v/s energy.
    - Cw_4S_DadHOPS.npy: Absorption spectrum for a 4-site chain calculated using DadHOPS v/s energy.

Panel_C: 

    - Cw_12S_DadHOPS.npy: Absorption spectrum for a 12-site chain calculated using DadHOPS without including state adaptivity v/s energy.
    - Cw_12S_DadHOPS_SA.npy: Absorption spectrum for a 12-site chain calculated using DadHOPS with state adaptivity v/s energy.

Panel_D:

    - Aux_states_DadHOPS.npy: Number of auxiliary states required to run a DadHOPS calculation for each N-pigment system.
    - Aux_states_HOPS.npy: Number of auxiliary states required to run a dyadic HOPS calculation for each N-pigment system.
    - N_states_DadHOPS.npy: Number of site states required to run a DadHOPS calculation for each N-pigment system.
    - N_states_HOPS.npy: Number of site states required to run a dyadic HOPS calculation for each N-pigment system.

Figure_5:

Panel_C: 

    - PSI_Cw_HEOM.npy: PSI absorption spectrum calculated using HEOM v/s energy.
    - PSI_Cw_HOPS.npy: PSI absorption spectrum calculated using dyadic HOPS v/s energy.

Panel_D:

    - PSI_Error_Random.npy: Calculated mean error, where clusters of 4 were assigned randomly v/s number of trajectories.
    - PSI_Error_Coupling.npy: Calculated mean error, where clusters of 4 were assigned based on electronic coupling values v/s number of trajectories.

Figure_6:

Panel_A:

    - PBI_Exp_data_dil.npy: Experimental data for a dilute solution of PBI v/s energy.
    - PBI_Cw_DadHOPS_300.npy: Calculated spectrum for a PBI monomer with the spread in static disorder of value 300 cm^{-1} v/s energy.
    - PBI_Cw_DadHOPS_400.npy:: Calculated spectrum for a PBI monomer with the spread in static disorder of value 400 cm^{-1} v/s energy.

Panel_B:

    - PBI_Exp_data_conc.npy: Experimental data for a concentrated solution of PBI v/s energy.
    - PBI_trimer_Cw_DadHOPS.npy: Calculated spectrum for a PBI trimer using DadHOPS v/s energy.

Panel_C: 

    - Cw_PBI_monomer.npy: Calculated spectrum for a PBI monomer using DadHOPS v/s energy.
    - Cw_PBI_dimer.npy: Calculated spectrum for a PBI dimer using DadHOPS v/s energy.
    - Cw_PBI_trimer.npy: Calculated spectrum for a PBI trimer using DadHOPS v/s energy.
    - Cw_PBI_heptamer.npy: Calculated spectrum for a PBI heptamer using DadHOPS v/s energy.
    - Cw_PBI_1000mer.npy: Calculated spectrum for a PBI 1000mer using DadHOPS v/s energy.

Panel_D:

    - peak_00_position.npy: relative position of the 00 peak for different number of pigments.
    - peak_00_position_1000.npy: relative position of the 0,0 peak for a system with 1000 pigments. (Single value file)
    - peak_I_ratio.npy: ratio of intensities of peak 0,1 w.r.t peak 0,0 for different number of pigments.
    - peak_I_ratio_1000.npy: ratio of intensities of peak 0,1 w.r.t peak 0,0 for a system with 1000 pigments. (Single value file)

Figure_7:

    - PBI_N_states_DadHOPS.npy: Number of states required to run a DadHOPS calculation for each N-PBI molecules system.  
    - PBI_Aux_states_HOPS.npy: Number of auxiliary states required to run a dyadic HOPS calculation for each N-PBI molecules system.  
    - PBI_Aux_states_DadHOPS.npy: Number of auxiliary states required to run a DadHOPS calculation for each N-PBI molecules system.  

The packaged scripts may be run with Python 3.10 and the associated versions of the os, numpy, and matplotlib packages.