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removed everything except the necesarry files for installing cbc_pdet package and have it work properly
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README.md

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# cbc_pdet
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Code for compact binary mergers population anlysis
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This repository contains code for a compact binary mergers selection function for gravitational wave (GW) population analysis, used in the following paper:
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**"A physically modelled selection function for compact binary mergers in the LIGO-Virgo O3 run and beyond"**
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*Authors: Ana Lorenzo-Medina, Thomas Dent*
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DOI: [https://doi.org/10.48550/arXiv.2408.13383](https://doi.org/10.48550/arXiv.2408.13383)
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The main branch contains a python package with only the necessary files to run it. There is an example_run_script.py with the code to initialize the class Found_injections() to be able to use its methods. The class is in the o123_class_found_inj_general.py file, and the functions for dmid and emax are in fitting_functions.py. The o1 o2 and o3 folders contain the optimal values of the parameters for every combination of dmid/emax functions we have tried. They are not strictly needed to initialize the class but they are to be able to use a lot of the methods, if not given, you would need to make a fit to have them. The files that are necessary to initialize the class are the .dat files in ini_values, since they are initial points for the maximization algorithm of the likelihood. There is an option to give the class your own arrays of ini_values, if you don't want to use the ones we provide here.
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In the branch legacy we have everything produced for the paper mentioned before, as well as all the extra tests and studies we performed.
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If you find this code useful in your research, please consider citing our paper:
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@misc{lorenzomedina2024physicallymodelledselectionfunction,
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title={A physically modelled selection function for compact binary mergers in the LIGO-Virgo O3 run and beyond},
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author={Ana Lorenzo-Medina and Thomas Dent},
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year={2024},
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eprint={2408.13383},
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archivePrefix={arXiv},
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primaryClass={gr-qc},
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url={https://arxiv.org/abs/2408.13383},
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}

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