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ML framework to estimate Bayesian posteriors of galaxy morphological parameters

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Status of Build and Tests Workflow Documentation Status Python Version 3.7 and above GitHub license image Code DOI Publication DOI arXiv


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The Galaxy Morphology Posterior Estimation Network (GaMPEN) is a novel machine learning framework for estimating the Bayesian posteriors (i.e., values + uncertainties) of morphological parameters for arbitrarily large numbers of galaxies. GaMPEN also automatically crops input galaxy images to an optimal size before morphological parameter estimation.

GaMPEN's predicted uncertainties have been shown to be upto ~60% more accurate compared to traditional light-profile fitting codes. GaMPEN can be adapted to work on both ground and space-based imaging; and to predict both parametric and non-parametric estimates of morphology.

Once trained, it takes GaMPEN less than a milli-second to perform a single model evaluation on a CPU. Thus, GaMPEN's posterior prediction capabilities are ready for large galaxy samples expected from upcoming large imaging surveys, such as Rubin-LSST, Euclid, and NGRST.

For a quick read-through of why GaMPEN was developed, what challenges it addresses, and how it works see this link

Documentation

GaMPEN's documentation is available in this repository and also hosted on readthedocs.io . Although the documentation is fairly complete; if you are trying to use GaMPEN and run into issues, please get in touch with us!

Publication

GaMPEN was initially introduced in this ApJ paper

An updated record of GaMPEN's trained models and catalogs produced are maintained here

Attribution Info.

Please cite the above-mentioned publication if you make use of this software module or some code herein.

@article{Ghosh2022,
author = {Aritra Ghosh and C. Megan Urry and Amrit Rau and Laurence Perreault-Levasseur and Miles Cranmer and Kevin Schawinski and Dominic Stark and Chuan Tian and Ryan Ofman and Tonima Tasnim Ananna and Connor Auge and Nico Cappelluti and David B. Sanders and Ezequiel Treister},
doi = {10.3847/1538-4357/ac7f9e},
issn = {0004-637X},
issue = {2},
journal = {The Astrophysical Journal},
month = {8},
pages = {138},
title = {GaMPEN: A Machine-learning Framework for Estimating Bayesian Posteriors of Galaxy Morphological Parameters},
volume = {935},
year = {2022},
}

License

Copyright 2022 Aritra Ghosh, Amrit Rau & contributors

Made available under a GNU GPL v3.0 license.

Contributors

GaMPEN was initially developed by Amrit Rau and Aritra Ghosh

The initial documentation was developed by Aayush Mishra and Aritra Ghosh

For an updated list of all current contributors, please see here

Getting Help/Contributing

If you have a question, please send me an e-mail at this aritraghsh09@xxxxx.com GMail address.

If you have spotted a bug in the code/documentation or you want to propose a new feature, please feel free to open an issue/a pull request on GitHub.