Host galaxy identification for supernova surveys

Romer, A Kathy and The Dark Energy Survey, et al. (2016) Host galaxy identification for supernova surveys. Astronomical Journal, 152. p. 154. ISSN 0004-6256

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Abstract

Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST), which will discover SNe by the thousands. Spectroscopic resources are limited, so in the absence of real-time SN spectra these surveys must rely on host galaxy spectra to obtain accurate redshifts for the Hubble diagram and to improve photometric classification of SNe. In addition, SN luminosities are known to correlate with host-galaxy properties. Therefore, reliable identification of host galaxies is essential for cosmology and SN science. We simulate SN events and their locations within their host galaxies to develop and test methods for matching SNe to their hosts. We use both real and simulated galaxy catalog data from the Advanced Camera for Surveys General Catalog and MICECATv2.0, respectively. We also incorporate "hostless" SNe residing in undetected faint hosts into our analysis, with an assumed hostless rate of 5%. Our fully automated algorithm is run on catalog data and matches SNe to their hosts with 91% accuracy. We find that including a machine learning component, run after the initial matching algorithm, improves the accuracy (purity) of the matching to 97% with a 2% cost in efficiency (true positive rate). Although the exact results are dependent on the details of the survey and the galaxy catalogs used, the method of identifying host galaxies we outline here can be applied to any transient survey.

Item Type: Article
Schools and Departments: School of Mathematical and Physical Sciences > Physics and Astronomy
Research Centres and Groups: Astronomy Centre
Subjects: Q Science > QB Astronomy
Depositing User: Richard Chambers
Date Deposited: 05 Dec 2016 13:08
Last Modified: 21 Aug 2017 04:16
URI: http://sro.sussex.ac.uk/id/eprint/65805

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Project NameSussex Project NumberFunderFunder Ref
STFC Consolidated Grant SupplementG1316STFC-SCIENCE AND TECHNOLOGY FACILITIES COUNCILST/M000753/1