The Dark Energy Survey supernova programme: 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 7.2 to 11.7 per cent, with an average of 8.8 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 Simulated Catalogue of Optical Transients and Correlated Hosts (SCOTCH)

“…In this work, we extend the results of Vincenzi et al (2021) by simulating additional supernovae and other non-SN transients, incorporating correlations with hosts across a wider range of properties, and separately validating hosts of different classes across these properties. We extrapolate information from archival events, mostly at low-redshift, to a high-redshift simulated sample of galaxies via associations in intrinsic-rather than observed-properties.…”

“…Our first step to realistically associate transients with hosts is to create HOSTLIBs from CosmoDC2 galaxies. In previous work, including Vincenzi et al (2021), HOSTLIBs were constructed of representative field galaxies and correlations with transient class were implemented There is a one-to-one mapping between the galaxies in the top and bottom image; each galaxy's redshift is slightly shifted, which smears out many of the non-physical tracks.…”

“…4 of Smith et al (2020). Based on the fact that few events have been observed with 𝑀 * < 10 10 and negative 𝑥 1 , we implement the following model from Vincenzi et al (2021):…”

“…Although observed samples are small, there are indications that SNe Iax occur almost exclusively in late-type, star forming galaxies (Jha 2017;Takaro et al 2020) and SNe 91bg preferentially occur in early-type, passive galaxies (van den Bergh et al 2005;Hakobyan et al 2020). Accordingly, Vincenzi et al (2021) set the SN Iax probability to the SN Ia probability in active hosts and 0 in passive hosts; conversely, they define the SN 91bg-like probability as equal to the SN Ia probability in passive hosts and 0 in active hosts. We adopt a similar approach, assuming that the peculiar SNe Ia originate from similar progenitors as normal SNe Ia but that their hosts represent opposite ends of a continuum in galaxy age and morphology.…”

“…As part of the recent Dark Energy Survey (DES) cosmology analysis using photometrically-identified SNe Ia, Vincenzi et al (2021) expanded the SNANA-specific HOSTLIB framework to realistically simulate SN host galaxies by class using a set of physically-motivated WGTMAP files. To account for contamination from non-Ia classes, their simulation includes core-collapse SNe (CC SNe, including II and Ib/c) and considers the dependence on host galaxy mass and star formation rate for each SN type.…”