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Automated probabilistic classification of transients and variables

Mahabal, A. and Djorgovski, S. G. and Turmon, M. and Jewell, J. and Williams, R. R. and Drake, A. J. and Graham, M. G. and Donalek, C. and Glikman, E. (2008) Automated probabilistic classification of transients and variables. Astronomische Nachrichten, 329 (3). pp. 288-291. ISSN 0004-6337. https://resolver.caltech.edu/CaltechAUTHORS:20100722-100956038

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Abstract

There is an increasing number of large, digital, synoptic sky surveys, in which repeated observations are obtained over large areas of the sky in multiple epochs. Likewise, there is a growth in the number of (often automated or robotic) follow-up facilities with varied capabilities in terms of instruments, depth, cadence, wavelengths, etc., most of which are geared toward some specific astrophysical phenomenon. As the number of detected transient events grows, an automated, probabilistic classification of the detected variables and transients becomes increasingly important, so that an optimal use can be made of follow-up facilities, without unnecessary duplication of effort. We describe a methodology now under development for a prototype event classification system; it involves Bayesian and Machine Learning classifiers, automated incorporation of feedback from follow-up observations, and discriminated or directed follow-up requests. This type of methodology may be essential for the massive synoptic sky surveys in the future.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1002/asna.200710943 DOIArticle
ORCID:
AuthorORCID
Mahabal, A.0000-0003-2242-0244
Djorgovski, S. G.0000-0002-0603-3087
Turmon, M.0000-0002-6463-063X
Glikman, E.0000-0003-0489-3750
Additional Information:© 2008 Wiley. Received 2007 Sep 1; accepted 2007 Nov 27; Published online 2008 Feb 25. We are grateful to the members of the PQ survey team, and to the staff of Palomar Observatory. This work was supported in part by the NSF grants AST-0407448, AST-0326524, and CNS-0540369, and by the Ajax Foundation. SGD acknowledges a stimulating atmosphere of the Aspen Center for Physics. Finally, we thank the workshop organizers for an excellent and productive meeting.
Funders:
Funding AgencyGrant Number
NSFAST-0407448
NSFAST-0326524
NSFCNS-0540369
Ajax FoundationUNSPECIFIED
Subject Keywords:astronomical databases: miscellaneous; methods: data analysis; methods: statistical; surveys
Issue or Number:3
Record Number:CaltechAUTHORS:20100722-100956038
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20100722-100956038
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:19159
Collection:CaltechAUTHORS
Deposited By: Jason Perez
Deposited On:30 Jul 2010 17:49
Last Modified:03 Oct 2019 01:53

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