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 J. 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 N.Da Costa; Shantanu Desai; Peter Doel; Tim F. Eifler; August E. Evrard; Brenna Flaugher; Pablo Fosalba; Enrique Gaztaaga; Daniel Gruen; Robert Gruendl; David J. James; Kyler Kuehn; Nikolay Kuropatkin; Marcio A.G. 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 J. 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 N.Da Costa, Shantanu Desai, Peter Doel, Tim F. Eifler, August E. Evrard, Brenna Flaugher, Pablo Fosalba, Enrique Gaztaaga, Daniel Gruen, Robert Gruendl, David J. James, Kyler Kuehn, Nikolay Kuropatkin, Marcio A.G. 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

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© 2016. The American Astronomical Society. All rights reserved. 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.

Idioma original	Anglès
Número d’article	154
Revista	Astronomical Journal
Volum	152
Número	6
DOIs	https://doi.org/10.3847/0004-6256/152/6/154
Estat de la publicació	Publicada - 1 de des. 2016

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10.3847/0004-6256/152/6/154

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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. Astronomical Journal, 152(6), Article 154. https://doi.org/10.3847/0004-6256/152/6/154

@article{51f3e2d0170b4e2c97098462c406f455,

title = "HOST GALAXY IDENTIFICATION for SUPERNOVA SURVEYS",

abstract = "{\textcopyright} 2016. The American Astronomical Society. All rights reserved. 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",

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'Andrea, {Chris B.} and Mark Sullivan and Jorge Carretero and Castander, {Francisco J.} 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 N.Da} and Shantanu Desai and Peter Doel and Eifler, {Tim F.} and Evrard, {August E.} and Brenna Flaugher and Pablo Fosalba and Enrique Gaztaaga and Daniel Gruen and Robert Gruendl and James, {David J.} and Kyler Kuehn and Nikolay Kuropatkin and Maia, {Marcio A.G.} 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 = dec,

day = "1",

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

language = "English",

volume = "152",

journal = "Astronomical Journal",

issn = "0004-6256",

number = "6",

}

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, LND, Desai, S, Doel, P, Eifler, TF, Evrard, AE, Flaugher, B, Fosalba, P, Gaztaaga, E, Gruen, D, Gruendl, R, 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', Astronomical Journal, vol. 152, núm. 6, 154. 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 J.

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 N.Da

AU - Desai, Shantanu

AU - Doel, Peter

AU - Eifler, Tim F.

AU - Evrard, August E.

AU - Flaugher, Brenna

AU - Fosalba, Pablo

AU - Gaztaaga, Enrique

AU - Gruen, Daniel

AU - Gruendl, Robert

AU - James, David J.

AU - Kuehn, Kyler

AU - Kuropatkin, Nikolay

AU - Maia, Marcio A.G.

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 - 2016/12/1

Y1 - 2016/12/1

N2 - © 2016. The American Astronomical Society. All rights reserved. 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 - © 2016. The American Astronomical Society. All rights reserved. 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

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

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

M3 - Article

SN - 0004-6256

VL - 152

JO - Astronomical Journal

JF - Astronomical Journal

IS - 6

M1 - 154

ER -

HOST GALAXY IDENTIFICATION for SUPERNOVA SURVEYS

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