A unified explanation for the supernova rate-galaxy mass dependence based on supernovae detected in Sloan galaxy spectra

Abstract

Using a method to discover and classify supernovae (SNe) in galaxy spectra, we detect 91 Type Ia SNe (SNe Ia) and 16 Type II SNe (SNe II) among ∼ 740 000 galaxies of all types and ∼ 215 000 star-forming galaxies without active galactic nuclei, respectively, in Data Release 9 of the Sloan Digital Sky Survey. Of these SNe, 15 SNe Ia and 8 SNe II are new discoveries reported here for the first time. We use our SN samples to measure SN rates per unit mass as a function of galaxy stellar mass, star-formation rate (SFR), and specific SFR (sSFR), as derived by the MPA-JHU Galspec pipeline. We show that correlations between SN Ia and SN II rates per unit mass and galaxy stellar mass, SFR, and sSFR can be explained by a combination of the respective SN delay-time distributions (the distributions of times that elapse between the formation of a stellar population and all ensuing SNe), the ages of the surveyed galaxies, the redshifts at which they are observed, and their star-formation histories. This model was first suggested by Kistler et al. for the SN Ia rate-mass correlation, but is expanded here to SNe II and to correlations with galaxy SFR and sSFR. Finally, we measure a volumetric SN II rate at redshift 0.075 of R II,V = 0.621

Revisiting the Lick Observatory Supernova Search Volume-limited Sample: Updated Classifications and Revised Stripped-envelope Supernova Fractions

“…Several recent large-scale SN data releases have re- lied on SNID classifications using relatively stringent requirements for a robust identification, requiring a high rlap value for the top match (rlap is a quality parameter used by SNID -a higher value corresponds to a more trustworthy classification) and that the first few matches be of the same subtype (e.g., Silverman et al 2012;Graur & Maoz 2013;Modjaz et al 2014;Graur et al 2015). We follow these methods whenever possible, and for most of the SNe in our sample they clearly indicate a single type and subtype.…”

The weirdest SDSS galaxies: results from an outlier detection algorithm

“…SDSS J080821. 09+005035.3 (4745-55892-0018) is reported here for the first time since the galaxy is part of DR10, while Graur, Bianco & Modjaz (2015) worked with the DR9 galaxy sample. We present in figure 18 the galaxy spectrum and its best SDSS model (left panel) where one can notice additional, broad, features that the best SDSS model does not account for.…”

“…supernovae detection is then carried out on the residual between the galaxy spectrum and its best eigenspectra fit, using various methods of template fitting: Madgwick et al (2003) order to obtain a residual which is noiseless, and then crosscorrelated it with a set of type Ia spectral templates. Tu et al (2010); Krughoff et al (2011);Graur & Maoz (2013);Graur, Bianco & Modjaz (2015) used PCA or singular value decomposition (SVD) of supernovae spectroscopic templates to fit the residual. In all of these cases, it was necessary to use both galaxy and supernovae templates in order to detect the supernovae.…”

A Dependence of the Tidal Disruption Event Rate on Global Stellar Surface Mass Density and Stellar Velocity Dispersion

“…The latter value corresponds to a specific star formation rate of  --10 yr 11 1 , below which galaxies are usually considered to be "quiescent" (e.g., Elbaz et al 2011;Graur et al 2015). d H A was not corrected for emission-line filling, but the Hα EW was corrected for stellar absorption, since these effects are expected to be negligible and significant, respectively, in quiescent Balmer-strong galaxies.…”