The Dark Energy Survey Supernova Program: Modelling selection efficiency and observed core collapse supernova contamination

Abstract

The analysis of current and future cosmological surveys of type Ia supernovae (SNe Ia) at high-redshift depends on the accurate photometric classification of the SN events detected. Generating realistic simulations of photometric SN surveys constitutes an essential step for training and testing photometric classification algorithms, and for correcting biases introduced by selection effects and contamination arising from core collapse SNe in the photometric SN Ia samples. We use published SN time-series spectrophotometric templates, rates, luminosity functions and empirical relationships between SNe and their host galaxies to construct a framework for simulating photometric SN surveys. We present this framework in the context of the Dark Energy Survey (DES) 5-year photometric SN sample, comparing our simulations of DES with the observed DES transient populations.We demonstrate excellent agreement in many distributions, including Hubble residuals, between our simulations and data. We estimate the core collapse fraction expected in the DES SN sample after selection requirements are applied and before photometric classification. After testing different modelling choices and astrophysical assumptions underlying our simulation, we find that the predicted contamination varies from 5.8 to 9.3 per cent, with an average of 7.0 per cent and r.m.s. of 1.1 per cent. Our simulations are the first to reproduce the observed photometric SN and host galaxy properties in high-redshift surveys without fine-tuning the input parameters. The simulation methods presented here will be a critical component of the cosmology analysis of the DES photometric SN Ia sample: correcting for biases arising from contamination, and evaluating the associated systematic uncertainty.

The dark energy survey 5-yr photometrically identified type Ia supernovae

“…SN hosts in OzDES were observed up to a limiting 𝑟 magnitude of ≈ 24. Further details on host galaxy association can be found in Gupta et al (2016); Vincenzi et al (2020).…”

“…We select transients that have redshifts obtained from spectra from either the SN or its host galaxy (Lidman et al 2020) using quality tags in Vincenzi et al (2020). In this work, we also include lower resolution redshifts from PRIMUS since they are precise enough for photometric classification 1 .…”

“…Detailed information on the inputs necessary to obtain realistic DES-SN simulations can be found in Kessler et al (2019b). We also make use of recent updates in the library of simulated host galaxies for DES-SN as introduced by Vincenzi et al (2020). This host galaxy library includes the dependence of SN rates on galaxy properties such as stellar mass and galaxy star formation rate.…”

“…We simulate a variety of SNe using volumetric rates and input parameters as described in Vincenzi et al (2020). Our simulations are performed over a redshift range 0.05 < 𝑧 < 1.3.…”

“…Contamination is distributed differently when using a fixed or SNphoto-z. liar SNe Ia (Vincenzi et al 2020). The HQ cuts are: −3.0 < x1 < 3.0, −0.3 < c < 0.3, and σ x1 < 1 and σ t 0 < 2.…”