Pith. sign in

REVIEW 1 cited by

The Core-collapse rate from the Supernova Legacy Survey

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 0904.1066 v1 pith:JYSJN4XO submitted 2009-04-07 astro-ph.CO

classification astro-ph.CO
keywords supernovacore-collapseratelegacymeasureredshiftssniasnls
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
abstract

We use three years of data from the Supernova Legacy Survey (SNLS) to study the general properties of core-collapse and type Ia supernovae. This is the first such study using the "rolling search" technique which guarantees well-sampled SNLS light curves and good efficiency for supernovae brighter than $i^\prime\sim24$. Using host photometric redshifts, we measure the supernova absolute magnitude distribution down to luminosities $4.5 {\rm mag}$ fainter than normal SNIa. Using spectroscopy and light-curve fitting to discriminate against SNIa, we find a sample of 117 core-collapse supernova candidates with redshifts $z<0.4$ (median redshift of 0.29) and measure their rate to be larger than the type Ia supernova rate by a factor $4.5\pm0.8(stat.) \pm0.6 (sys.)$. This corresponds to a core-collapse rate at $z=0.3$ of $[1.42\pm 0.3(stat.) \pm0.3(sys.)]\times10^{-4}\yr^{-1}(h_{70}^{-1}\Mpc)^{-3}$.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. On the cosmological performance of photometrically classified supernovae with machine learning

    astro-ph.CO 2019-08 conditional novelty 5.0 of 10

    Machine-learning classification of simulated photometric supernovae retains up to 75 percent of cosmological information with SALT2 features and roughly one third with Newling or wavelet features.

Pith tools