Host galaxy identification for supernova surveys

Ravi R. Gupta; Steve Kuhlmann; Eve Kovacs; Harold Spinka; Richard Kessler; Daniel A. Goldstein; Camille Liotine; Katarzyna Pomian; Chris B. D’Andrea; Mark Sullivan; Jorge Carretero; Francisco Javier Castander; Robert C. Nichol; David A. Finley; John A. Fischer; Ryan J. Foley; Alex G. Kim; Andreas Papadopoulos; Masao Sako; Daniel M. Scolnic; Mathew Smith; Brad E. Tucker; Syed Uddin; Rachel C. Wolf; Fang Yuan; Tim M. C. Abbott; Filipe B. Abdalla; Aurélien Benoit-lévy; Emmanuel Bertin; David Brooks; Aurelio Carnero Rosell; Matias Carrasco Kind; Carlos E. Cunha; Luiz A. N. da Costa; Shantanu Desai; Peter Doel; Tim F. Eifler; August E. Evrard; Brenna Flaugher; Pablo Fosalba; Enrique Gaztañaga; Daniel Gruen; Robert A. Gruendl; David J. James; Kyler Kuehn; Nikolay Kuropatkin; Marcio Antonio Geimba Maia; Jennifer L. Marshall; Ramon Miquel; Andrés A. Plazas; A. Kathy Romer; Eusebio Sánchez; Michael Schubnell; Ignacio Sevilla-Noarbe; Flávia Sobreira; Eric Suchyta; Molly E. C. Swanson; Gregory Tarle; Alistair R. Walker; William Wester

doi:10.3847/0004-6256/152/6/154

Host galaxy identification for supernova surveys

Ravi R. Gupta, Steve Kuhlmann, Eve Kovacs, Harold Spinka, Richard Kessler, Daniel A. Goldstein, Camille Liotine, Katarzyna Pomian, Chris B. D’Andrea, Mark Sullivan, Jorge Carretero, Francisco Javier Castander, Robert C. Nichol, David A. Finley, John A. Fischer, Ryan J. Foley, Alex G. Kim, Andreas Papadopoulos, Masao Sako, Daniel M. ScolnicMathew Smith, Brad E. Tucker, Syed Uddin, Rachel C. Wolf, Fang Yuan, Tim M. C. Abbott, Filipe B. Abdalla, Aurélien Benoit-lévy, Emmanuel Bertin, David Brooks, Aurelio Carnero Rosell, Matias Carrasco Kind, Carlos E. Cunha, Luiz A. N. da Costa, Shantanu Desai, Peter Doel, Tim F. Eifler, August E. Evrard, Brenna Flaugher, Pablo Fosalba, Enrique Gaztañaga, Daniel Gruen, Robert A. Gruendl, David J. James, Kyler Kuehn, Nikolay Kuropatkin, Marcio Antonio Geimba Maia, Jennifer L. Marshall, Ramon Miquel, Andrés A. Plazas, A. Kathy Romer, Eusebio Sánchez, Michael Schubnell, Ignacio Sevilla-Noarbe, Flávia Sobreira, Eric Suchyta, Molly E. C. Swanson, Gregory Tarle, Alistair R. Walker, William Wester

Institute of Cosmology & Gravitation

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Abstract

Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope, which will discover SNe by the thousands. Spectroscopic resources are limited, and 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.

Original language	English
Pages (from-to)	154-173
Number of pages	20
Journal	The Astronomical Journal
Volume	152
Issue number	6
DOIs	https://doi.org/10.3847/0004-6256/152/6/154
Publication status	Published - 10 Nov 2016

Keywords

catalogs
galaxies: general
supernovae: general
surveys
RCUK
STFC
AST-1138766

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10.3847/0004-6256/152/6/154

Gupta_2016_AJ_152_154
The final published version of this article by Ravi R. Gupta et al 2016 AJ 152 154 is available online at http://dx.doi.org/10.3847/0004-6256/152/6/154 © 2016. The American Astronomical Society. All rights reserved.
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https://researchbank.swinburne.edu.au/items/c8b565e7-6ae2-48e3-9557-dc4c8ebd489c/1/

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Gupta, R. R., Kuhlmann, S., Kovacs, E., Spinka, H., Kessler, R., Goldstein, D. A., Liotine, C., Pomian, K., D’Andrea, C. B., Sullivan, M., Carretero, J., Castander, F. J., Nichol, R. C., Finley, D. A., Fischer, J. A., Foley, R. J., Kim, A. G., Papadopoulos, A., Sako, M., ... Wester, W. (2016). Host galaxy identification for supernova surveys. The Astronomical Journal, 152(6), 154-173. https://doi.org/10.3847/0004-6256/152/6/154

@article{f2e3c250ece34f20a5fb56d532b8cf5f,

title = "Host galaxy identification for supernova surveys",

abstract = "Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope, which will discover SNe by the thousands. Spectroscopic resources are limited, and 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.",

keywords = "catalogs, galaxies: general, supernovae: general, surveys, RCUK, STFC, AST-1138766",

author = "Gupta, {Ravi R.} and Steve Kuhlmann and Eve Kovacs and Harold Spinka and Richard Kessler and Goldstein, {Daniel A.} and Camille Liotine and Katarzyna Pomian and D{\textquoteright}Andrea, {Chris B.} and Mark Sullivan and Jorge Carretero and Castander, {Francisco Javier} and Nichol, {Robert C.} and Finley, {David A.} and Fischer, {John A.} and Foley, {Ryan J.} and Kim, {Alex G.} and Andreas Papadopoulos and Masao Sako and Scolnic, {Daniel M.} and Mathew Smith and Tucker, {Brad E.} and Syed Uddin and Wolf, {Rachel C.} and Fang Yuan and Abbott, {Tim M. C.} and Abdalla, {Filipe B.} and Aur{\'e}lien Benoit-l{\'e}vy and Emmanuel Bertin and David Brooks and Rosell, {Aurelio Carnero} and Kind, {Matias Carrasco} and Cunha, {Carlos E.} and Costa, {Luiz A. N. da} and Shantanu Desai and Peter Doel and Eifler, {Tim F.} and Evrard, {August E.} and Brenna Flaugher and Pablo Fosalba and Enrique Gazta{\~n}aga and Daniel Gruen and Gruendl, {Robert A.} and James, {David J.} and Kyler Kuehn and Nikolay Kuropatkin and Maia, {Marcio Antonio Geimba} and Marshall, {Jennifer L.} and Ramon Miquel and Plazas, {Andr{\'e}s A.} and Romer, {A. Kathy} and Eusebio S{\'a}nchez and Michael Schubnell and Ignacio Sevilla-Noarbe and Fl{\'a}via Sobreira and Eric Suchyta and Swanson, {Molly E. C.} and Gregory Tarle and Walker, {Alistair R.} and William Wester",

year = "2016",

month = nov,

day = "10",

doi = "10.3847/0004-6256/152/6/154",

language = "English",

volume = "152",

pages = "154--173",

journal = "The Astronomical Journal",

issn = "0004-6256",

publisher = "IOP Publishing",

number = "6",

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Gupta, RR, Kuhlmann, S, Kovacs, E, Spinka, H, Kessler, R, Goldstein, DA, Liotine, C, Pomian, K, D’Andrea, CB, Sullivan, M, Carretero, J, Castander, FJ, Nichol, RC, Finley, DA, Fischer, JA, Foley, RJ, Kim, AG, Papadopoulos, A, Sako, M, Scolnic, DM, Smith, M, Tucker, BE, Uddin, S, Wolf, RC, Yuan, F, Abbott, TMC, Abdalla, FB, Benoit-lévy, A, Bertin, E, Brooks, D, Rosell, AC, Kind, MC, Cunha, CE, Costa, LAND, Desai, S, Doel, P, Eifler, TF, Evrard, AE, Flaugher, B, Fosalba, P, Gaztañaga, E, Gruen, D, Gruendl, RA, James, DJ, Kuehn, K, Kuropatkin, N, Maia, MAG, Marshall, JL, Miquel, R, Plazas, AA, Romer, AK, Sánchez, E, Schubnell, M, Sevilla-Noarbe, I, Sobreira, F, Suchyta, E, Swanson, MEC, Tarle, G, Walker, AR & Wester, W 2016, 'Host galaxy identification for supernova surveys', The Astronomical Journal, vol. 152, no. 6, pp. 154-173. https://doi.org/10.3847/0004-6256/152/6/154

TY - JOUR

T1 - Host galaxy identification for supernova surveys

AU - Gupta, Ravi R.

AU - Kuhlmann, Steve

AU - Kovacs, Eve

AU - Spinka, Harold

AU - Kessler, Richard

AU - Goldstein, Daniel A.

AU - Liotine, Camille

AU - Pomian, Katarzyna

AU - D’Andrea, Chris B.

AU - Sullivan, Mark

AU - Carretero, Jorge

AU - Castander, Francisco Javier

AU - Nichol, Robert C.

AU - Finley, David A.

AU - Fischer, John A.

AU - Foley, Ryan J.

AU - Kim, Alex G.

AU - Papadopoulos, Andreas

AU - Sako, Masao

AU - Scolnic, Daniel M.

AU - Smith, Mathew

AU - Tucker, Brad E.

AU - Uddin, Syed

AU - Wolf, Rachel C.

AU - Yuan, Fang

AU - Abbott, Tim M. C.

AU - Abdalla, Filipe B.

AU - Benoit-lévy, Aurélien

AU - Bertin, Emmanuel

AU - Brooks, David

AU - Rosell, Aurelio Carnero

AU - Kind, Matias Carrasco

AU - Cunha, Carlos E.

AU - Costa, Luiz A. N. da

AU - Desai, Shantanu

AU - Doel, Peter

AU - Eifler, Tim F.

AU - Evrard, August E.

AU - Flaugher, Brenna

AU - Fosalba, Pablo

AU - Gaztañaga, Enrique

AU - Gruen, Daniel

AU - Gruendl, Robert A.

AU - James, David J.

AU - Kuehn, Kyler

AU - Kuropatkin, Nikolay

AU - Maia, Marcio Antonio Geimba

AU - Marshall, Jennifer L.

AU - Miquel, Ramon

AU - Plazas, Andrés A.

AU - Romer, A. Kathy

AU - Sánchez, Eusebio

AU - Schubnell, Michael

AU - Sevilla-Noarbe, Ignacio

AU - Sobreira, Flávia

AU - Suchyta, Eric

AU - Swanson, Molly E. C.

AU - Tarle, Gregory

AU - Walker, Alistair R.

AU - Wester, William

PY - 2016/11/10

Y1 - 2016/11/10

N2 - Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope, which will discover SNe by the thousands. Spectroscopic resources are limited, and 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.

AB - Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope, which will discover SNe by the thousands. Spectroscopic resources are limited, and 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.

KW - catalogs

KW - galaxies: general

KW - supernovae: general

KW - surveys

KW - RCUK

KW - STFC

KW - AST-1138766

UR - https://researchbank.swinburne.edu.au/items/c8b565e7-6ae2-48e3-9557-dc4c8ebd489c/1/

U2 - 10.3847/0004-6256/152/6/154

DO - 10.3847/0004-6256/152/6/154

M3 - Article

SN - 0004-6256

VL - 152

SP - 154

EP - 173

JO - The Astronomical Journal

JF - The Astronomical Journal

IS - 6

ER -

Host galaxy identification for supernova surveys

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Keywords

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