The volumetric rate of superluminous supernovae at z ∼ 1

S. Prajs*, M. Sullivan, M. Smith, A. Levan, N. V. Karpenka, T. D.P. Edwards, C. R. Walker, W. M. Wolf, C. Balland, R. Carlberg, D. A. Howell, C. Lidman, R. Pain, C. Pritchet, V. Ruhlmann-Kleider

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

71 Citations (Scopus)

Abstract

We present a measurement of the volumetric rate of superluminous supernovae (SLSNe) at z ∼ 1.0, measured using archival data from the first four years of the Canada-France-Hawaii Telescope Supernova Legacy Survey (SNLS). We develop a method for the photometric classification of SLSNe to construct our sample. Our sample includes two previously spectroscopically identified objects, and a further new candidate selected using our classification technique. We use the point-source recovery efficiencies from Perrett et al. and a Monte Carlo approach to calculate the rate based on our SLSN sample. We find that the three identified SLSNe from SNLS give a rate of 91+7636 SNe yr−1 Gpc−3 at a volume-weighted redshift of z = 1.13. This is equivalent to 2.2+1089 × 10−4 of the volumetric core-collapse supernova rate at the same redshift. When combined with other rate measurements from the literature, we show that the rate of SLSNe increases with redshift in a manner consistent with that of the cosmic star formation history. We also estimate the rate of ultra-long gamma-ray bursts based on the events discovered by the Swift satellite, and show that it is comparable to the rate of SLSNe, providing further evidence of a possible connection between these two classes of events. We also examine the host galaxies of the SLSNe discovered in SNLS, and find them to be consistent with the stellar-mass distribution of other published samples of SLSNe.

Original languageEnglish
Pages (from-to)3568-3579
Number of pages12
JournalMonthly Notices of the Royal Astronomical Society
Volume464
Issue number3
DOIs
Publication statusPublished - 1 Jan 2017
Externally publishedYes

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