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Challenges in the automated classification of variable stars in large databases

Graham, Matthew and Drake, Andrew and Djorgovski, S. G. and Mahabal, Ashish and Donalek, Ciro (2017) Challenges in the automated classification of variable stars in large databases. EPJ Web of Conferences, 152 . Art. No. 03001. ISSN 2100-014X. doi:10.1051/epjconf/201715203001.

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With ever-increasing numbers of astrophysical transient surveys, new facilities and archives of astronomical time series, time domain astronomy is emerging as a mainstream discipline. However, the sheer volume of data alone - hundreds of observations for hundreds of millions of sources – necessitates advanced statistical and machine learning methodologies for scientific discovery: characterization, categorization, and classification. Whilst these techniques are slowly entering the astronomer’s toolkit, their application to astronomical problems is not without its issues. In this paper, we will review some of the challenges posed by trying to identify variable stars in large data collections, including appropriate feature representations, dealing with uncertainties, establishing ground truths, and simple discrete classes.

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Graham, Matthew0000-0002-3168-0139
Djorgovski, S. G.0000-0002-0603-3087
Mahabal, Ashish0000-0003-2242-0244
Additional Information:© 2017 The Authors, published by EDP Sciences. This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Published online: 8 September 2017. This work was supported in part by the NSF grants AST-1413600 and AST-1518308.
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Record Number:CaltechAUTHORS:20180322-091256983
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Official Citation:Challenges in the automated classification of variable stars in large databases. Matthew Graham, Andrew Drake, S.G. Djorgovski, Ashish Mahabal, Ciro Donalek. EPJ Web Conf. 152 03001 (2017). DOI: 10.1051/epjconf/201715203001
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:85411
Deposited By: Tony Diaz
Deposited On:26 Mar 2018 13:41
Last Modified:15 Nov 2021 20:28

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