This repository contains functions, objects, and scripts for modeling dynamic spectra of dispersed astrophysical signals at radio frequencies.
Currently, fitburst can be installed by cloning the repo and running pip in the following way:
pc> git clone git@github.com:CHIMEFRB/fitburst.git
pc> cd fitburst
pc/fitburst> pip install . # add the --user option if you're looking to install in your local environment.
Please refer to the documentation linked above to find desciptions on the codebase and examples for interacting with it.
The theory behind the modeling and analysis routines is presented in a publication currently under review, but available on the arXiv. This publication includes a variety of fitting examples and discussions on the treatment of biasing effects (e.g., intra-channel smearing from pulse dispersion) that can be accounted for within fitburst. If you use this codebase and publish results obtained with it, we ask that you cite the fitburst publication using the following BibTex entry:
@article{fpb+23,
author = {{Fonseca}, Emmanuel and {Pleunis}, Ziggy and {Breitman}, Daniela and {Sand}, Ketan R. and {Kharel}, Bikash and {Boyle}, Patrick J. and {Brar}, Charanjot and {Giri}, Utkarsh and {Kaspi}, Victoria M. and {Masui}, Kiyoshi W. and {Meyers}, Bradley W. and {Patel}, Chitrang and {Scholz}, Paul and {Smith}, Kendrick},
title = "{Modeling the Morphology of Fast Radio Bursts and Radio Pulsars with fitburst}",
journal = {arXiv e-prints},
keywords = {Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics},
year = 2023,
month = nov,
eid = {arXiv:2311.05829},
pages = {arXiv:2311.05829},
doi = {10.48550/arXiv.2311.05829},
archivePrefix = {arXiv},
eprint = {2311.05829},
primaryClass = {astro-ph.HE},
adsurl = {https://ui.adsabs.harvard.edu/abs/2023arXiv231105829F},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}All authors of the fitburst papers are the founding developers of fitburst, with Emmanuel Fonseca leading the development team. We welcome novel and meaningful contributions from interested users!
This package was built using namoona.