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Classification of ASKAP Vast Radio Light CurvesThe VAST survey is a wide-field survey that observes with unprecedented instrument sensitivity (0.5 mJy or lower) and repeat cadence (a goal of 5 seconds) that will enable novel scientific discoveries related to known and unknown classes of radio transients and variables. Given the unprecedented observing characteristics of VAST, it is important to estimate source classification performance, and determine best practices prior to the launch of ASKAP's BETA in 2012. The goal of this study is to identify light curve characterization and classification algorithms that are best suited for archival VAST light curve classification. We perform our experiments on light curve simulations of eight source types and achieve best case performance of approximately 90% accuracy. We note that classification performance is most influenced by light curve characterization rather than classifier algorithm.
Document ID
20130000038
Document Type
Preprint (Draft being sent to journal)
External Source(s)
Authors
Rebbapragada, Umaa (Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Lo, Kitty (Sydney Univ. Australia)
Wagstaff, Kiri L. (Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Reed, Colorado (Iowa Univ. Iowa City, IA, United States)
Murphy, Tara (Sydney Univ. Australia)
Thompson, David R. (Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Date Acquired
August 27, 2013
Publication Date
January 1, 2012
Subject Category
Astronomy
Meeting Information
2011 New Horizons in Time Domain Astronomy (Proceedings IAU Symposium No. 285)(Oxford)
Distribution Limits
Public
Copyright
Other
Keywords
radio astronomy
Australian Square Kilometer Array Pathfinder (ASKAP)
data analysis
Variables and Slow Transits (VAST)
classification