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Title: Host Galaxy Identification for Supernova Surveys

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 inmore » 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.« less
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Publication Date:
OSTI Identifier:
1260389
Report Number(s):
FERMILAB-PUB-16-124-AE-PPD; arXiv:1604.06138
Journal ID: ISSN 1538-3881; 1449957
DOE Contract Number:
AC02-07CH11359
Resource Type:
Journal Article
Resource Relation:
Journal Name: Astronomical Journal (Online); Journal Volume: 152; Journal Issue: 6
Publisher:
IOP Publishing
Research Org:
Argonne National Laboratory (ANL), Argonne, IL (United States); SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
Contributing Orgs:
DES
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS