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Photometric Classification of 2315 Pan-STARRS1 Supernovae with Superphot

Hosseinzadeh, Griffin; Dauphin, Frederick; Villar, V. Ashley; Berger, Edo; Jones, David O.; Challis, Peter; Chornock, Ryan; Drout, Maria R.; Foley, Ryan J.; Kirshner, Robert P.; Lunnan, Ragnhild; Margutti, Raffaella; Milisavljevic, Dan; Pan, Yen-Chen; Rest, Armin; Scolnic, Daniel M.; Magnier, Eugene; Metcalfe, Nigel; Wainscoat, Richard; Waters, Christopher

Photometric Classification of 2315 Pan-STARRS1 Supernovae with Superphot Thumbnail


Griffin Hosseinzadeh

Frederick Dauphin

V. Ashley Villar

Edo Berger

David O. Jones

Peter Challis

Ryan Chornock

Maria R. Drout

Ryan J. Foley

Robert P. Kirshner

Ragnhild Lunnan

Raffaella Margutti

Dan Milisavljevic

Yen-Chen Pan

Armin Rest

Daniel M. Scolnic

Eugene Magnier

Richard Wainscoat

Christopher Waters


The classification of supernovae (SNe) and its impact on our understanding of explosion physics and progenitors have traditionally been based on the presence or absence of certain spectral features. However, current and upcoming wide-field time-domain surveys have increased the transient discovery rate far beyond our capacity to obtain even a single spectrum of each new event. We must therefore rely heavily on photometric classification— connecting SN light curves back to their spectroscopically defined classes. Here, we present Superphot, an opensource Python implementation of the machine-learning classification algorithm of Villar et al., and apply it to 2315 previously unclassified transients from the Pan-STARRS1 Medium Deep Survey for which we obtained spectroscopic host-galaxy redshifts. Our classifier achieves an overall accuracy of 82%, with completenesses and purities of >80% for the best classes (SNe Ia and superluminous SNe). For the worst performing SN class (SNe Ibc), the completeness and purity fall to 37% and 21%, respectively. Our classifier provides 1257 newly classified SNe Ia, 521 SNe II, 298 SNe Ibc, 181 SNe IIn, and 58 SLSNe. These are among the largest uniformly observed samples of SNe available in the literature and will enable a wide range of statistical studies of each class.


Hosseinzadeh, G., Dauphin, F., Villar, V. A., Berger, E., Jones, D. O., Challis, P., …Waters, C. (2020). Photometric Classification of 2315 Pan-STARRS1 Supernovae with Superphot. Astrophysical Journal, 905(2), Article 93.

Journal Article Type Article
Acceptance Date Oct 20, 2020
Online Publication Date Dec 17, 2020
Publication Date 2020
Deposit Date Nov 5, 2021
Publicly Available Date Nov 5, 2021
Journal Astrophysical Journal
Print ISSN 0004-637X
Publisher American Astronomical Society
Peer Reviewed Peer Reviewed
Volume 905
Issue 2
Article Number 93


Published Journal Article (9.8 Mb)

Copyright Statement
© 2020. The American Astronomical Society. All rights reserved.

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