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A statistical approach to identify superluminous supernovae and probe their diversity

A statistical approach to identify superluminous supernovae and probe their diversity
A statistical approach to identify superluminous supernovae and probe their diversity
We investigate the identification of hydrogen-poor superluminous supernovae (SLSNe I) using a photometric analysis, without including an arbitrary magnitude threshold. We assemble a homogeneous sample of previously classified SLSNe I from the literature, and fit their light curves using Gaussian processes. From the fits, we identify four photometric parameters that have a high statistical significance when correlated, and combine them in a parameter space that conveys information on their luminosity and color evolution. This parameter space presents a new definition for SLSNe I, which can be used to analyse existing and future transient datasets. We find that 90% of previously classified SLSNe I meet our new definition. We also examine the evidence for two subclasses of SLSNe I, combining their photometric evolution with spectroscopic information, namely the photospheric velocity and its gradient. A cluster analysis reveals the presence of two distinct groups. ‘Fast’ SLSNe show fast light curves and color evolution, large velocities, and a large velocity gradient. ‘Slow’ SLSNe show slow light curve and color evolution, small expansion velocities, and an almost non-existent velocity gradient. Finally, we discuss the impact of our analyses in the understanding of the powering engine of SLSNe, and their implementation as cosmological probes in current and future surveys.
0004-637X
1-12
Inserra, Cosimo
004da73f-5b5e-43f4-b1a7-aaa0e579672e
Prajs, Szymon
84bb5d78-0e3f-4ce9-9dd2-de5479b03aaa
Gutierrez Avendano, Claudia Patrici
14464da3-b453-4980-bff2-b22afa4b4366
Angus, Charlotte
7a190f2d-9816-4960-8695-e694c39f099c
Smith, Mathew
8bdc74e1-a37b-434d-ae75-82763109bf7a
Sullivan, Mark
2f31f9fa-8e79-4b35-98e2-0cb38f503850
Inserra, Cosimo
004da73f-5b5e-43f4-b1a7-aaa0e579672e
Prajs, Szymon
84bb5d78-0e3f-4ce9-9dd2-de5479b03aaa
Gutierrez Avendano, Claudia Patrici
14464da3-b453-4980-bff2-b22afa4b4366
Angus, Charlotte
7a190f2d-9816-4960-8695-e694c39f099c
Smith, Mathew
8bdc74e1-a37b-434d-ae75-82763109bf7a
Sullivan, Mark
2f31f9fa-8e79-4b35-98e2-0cb38f503850

Inserra, Cosimo, Prajs, Szymon, Gutierrez Avendano, Claudia Patrici, Angus, Charlotte, Smith, Mathew and Sullivan, Mark (2018) A statistical approach to identify superluminous supernovae and probe their diversity. The Astrophysical Journal, 854 (175), 1-12. (doi:10.3847/1538-4357/aaaaaa).

Record type: Article

Abstract

We investigate the identification of hydrogen-poor superluminous supernovae (SLSNe I) using a photometric analysis, without including an arbitrary magnitude threshold. We assemble a homogeneous sample of previously classified SLSNe I from the literature, and fit their light curves using Gaussian processes. From the fits, we identify four photometric parameters that have a high statistical significance when correlated, and combine them in a parameter space that conveys information on their luminosity and color evolution. This parameter space presents a new definition for SLSNe I, which can be used to analyse existing and future transient datasets. We find that 90% of previously classified SLSNe I meet our new definition. We also examine the evidence for two subclasses of SLSNe I, combining their photometric evolution with spectroscopic information, namely the photospheric velocity and its gradient. A cluster analysis reveals the presence of two distinct groups. ‘Fast’ SLSNe show fast light curves and color evolution, large velocities, and a large velocity gradient. ‘Slow’ SLSNe show slow light curve and color evolution, small expansion velocities, and an almost non-existent velocity gradient. Finally, we discuss the impact of our analyses in the understanding of the powering engine of SLSNe, and their implementation as cosmological probes in current and future surveys.

Text A STATISTICAL APPROACH TO IDENTIFY SUPERLUMINOUS SUPERNOVAE AND PROBE THEIR - Accepted Manuscript
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Accepted/In Press date: 23 January 2018
e-pub ahead of print date: 20 February 2018
Published date: 26 February 2018

Identifiers

Local EPrints ID: 417210
URI: https://eprints.soton.ac.uk/id/eprint/417210
ISSN: 0004-637X
PURE UUID: b9829167-03c0-4a69-8157-4041b874c5fa
ORCID for Cosimo Inserra: ORCID iD orcid.org/0000-0002-3968-4409
ORCID for Mark Sullivan: ORCID iD orcid.org/0000-0001-9053-4820

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Date deposited: 25 Jan 2018 17:30
Last modified: 06 Jun 2018 12:28

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Contributors

Author: Cosimo Inserra ORCID iD
Author: Szymon Prajs
Author: Claudia Patrici Gutierrez Avendano
Author: Charlotte Angus
Author: Mathew Smith
Author: Mark Sullivan ORCID iD

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