Author: J. K. Patel
Date: 04/11/2024

Title: Description of setup details and files contained in the Section 3: TRIM dataset.

This dataset contains the configuration files used to perform Monte-Carlo simulations using SRIM v2013.0 TRIM software (see www.srim.org), as well as a subset of the 
generated simulation data, and a Python analysis script used to obtain the energy deposition curves in each active layer of RCF and scintillating fibber layers 
corresponding to the experimental setup. These deposition curves are then used to calculate the absolute energy deposition in the scintillating fiber layers, and to
reconstruct the profiles obtained with the SciFi BPM in the analysis script in the 'Section 3 dataset/Combined analysis' directory.

Files:
./Configuration Files/TRIM.IN		
		This configuration file is used by the TRIM software in SRIM-2013 to define the material composition, density and layer depth for modelling the detectors and
        filtering used in the experimental work presented in Section 3 of the main article. In this case we model the experimental setup with a layer of aluminium foil, 
        five layers of HDV2 RCF each composed of a Mylar support layer and a cellulose acetate active layer, and finally two 500 um polystyrene layers to model the 
        scintillating fibers of the SciFi BPM. 
		This file should be placed in the SRIM-2013 install directory to configure the setup and outputs of the TRIM simulation.

./Simulation Data/Section_3_TRIM_data.csv   
        A subset of the simulation data generated from running the TRIM simulation. This is used to obtain the energy deposition in each RCF and scintillating fiber 
        detector layer.

./Analysis/TRIM_Analysis.py
        This is an analysis script which processes the TRIM simulation data to obtain the peak and full-width at half maximum (FWHM) of the deposition curves for each 
        detector layer. These are output to the TRIM_RCF_processed_data.pkl and TRIM_SciFi_processed_data.pkl files for further analysis in the 
        'Section 3 dataset/Combined analysis' directory, where we use this data to generate Figure 5 of the main article. 
        This script was run using Python 3.9.19 and uses python packages: numpy-1.24.3, pandas-2.0.3, scipy-1.9.3.
        and tifffile-2023.8.30.

./Analysis/TRIM_Analysis.ipynb
        This contains the same analysis as the TRIM_Analysis.py script, but can be run in an interactive manner, and includes some plotting visualisations to aid understanding.
        It requires the additional python package: matplotlib-3.8.0.


