| dc.contributor.author | Chen, Mi | |
| dc.contributor.author | Souza, Rafael S. de | |
| dc.contributor.author | Xu, Quanfeng | |
| dc.contributor.author | Shen, Shiyin | |
| dc.contributor.author | Chies-Santos, Ana L. | |
| dc.contributor.author | Ye, Renhao | |
| dc.contributor.author | Canossa-Gosteinski, Marco A. | |
| dc.contributor.author | Cong, Yanping | |
| dc.date.accessioned | 2024-05-10T14:00:03Z | |
| dc.date.available | 2024-05-10T14:00:03Z | |
| dc.date.issued | 2024-04-22 | |
| dc.identifier.citation | Chen , M , Souza , R S D , Xu , Q , Shen , S , Chies-Santos , A L , Ye , R , Canossa-Gosteinski , M A & Cong , Y 2024 , ' Galmoss: A package for GPU-accelerated galaxy profile fitting ' , Astronomy and Computing , vol. 47 , 100825 , pp. 1-11 . https://doi.org/10.1016/j.ascom.2024.100825 | |
| dc.identifier.issn | 2213-1337 | |
| dc.identifier.other | ArXiv: http://arxiv.org/abs/2404.07780v1 | |
| dc.identifier.other | ORCID: /0000-0001-7207-4584/work/159376247 | |
| dc.identifier.uri | http://hdl.handle.net/2299/27863 | |
| dc.description | © 2024 The Author(s). Published by Elsevier B.V. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/ | |
| dc.description.abstract | We introduce galmoss, a python-based, torch-powered tool for two-dimensional fitting of galaxy profiles. By seamlessly enabling GPU parallelization, galmoss meets the high computational demands of large-scale galaxy surveys, placing galaxy profile fitting in the CSST/LSST-era. It incorporates widely used profiles such as the Sérsic, Exponential disk, Ferrer, King, Gaussian, and Moffat profiles, and allows for the easy integration of more complex models. Tested on 8289 galaxies from the Sloan Digital Sky Survey (SDSS) g-band with a single NVIDIA A100 GPU, galmoss completed classical Sérsic profile fitting in about 10 min. Benchmark tests show that galmoss achieves computational speeds that are 6 × faster than those of default implementations. | en |
| dc.format.extent | 11 | |
| dc.format.extent | 2695275 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | Astronomy and Computing | |
| dc.subject | GPU computing | |
| dc.subject | machine and deep learning | |
| dc.subject | Extragalactic astronomy | |
| dc.subject | Galaxies | |
| dc.subject | Data analysis – methods | |
| dc.subject | Statistical – GPU computing | |
| dc.subject | General – methods | |
| dc.subject | Astronomy and Astrophysics | |
| dc.subject | Computer Science Applications | |
| dc.subject | Space and Planetary Science | |
| dc.title | Galmoss: A package for GPU-accelerated galaxy profile fitting | en |
| dc.contributor.institution | Centre for Astrophysics Research (CAR) | |
| dc.contributor.institution | School of Physics, Engineering & Computer Science | |
| dc.contributor.institution | Department of Physics, Astronomy and Mathematics | |
| dc.description.status | Peer reviewed | |
| dc.identifier.url | http://www.scopus.com/inward/record.url?scp=85190785726&partnerID=8YFLogxK | |
| rioxxterms.versionofrecord | 10.1016/j.ascom.2024.100825 | |
| rioxxterms.type | Journal Article/Review | |
| herts.preservation.rarelyaccessed | true | |
