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.
Cite
@article{arxiv.2012.07180,
title = {The Dark Energy Survey Supernova Program: Modelling selection efficiency and observed core collapse supernova contamination},
author = {M. Vincenzi and M. Sullivan and O. Graur and D. Brout and T. M. Davis and C. Frohmaier and L. Galbany and C. P. Gutiérrez and S. R. Hinton and R. Hounsell and L. Kelsey and R. Kessler and E. Kovacs and S. Kuhlmann and J. Lasker and C. Lidman and A. Möller and R. C. Nichol and M. Sako and D. Scolnic and M. Smith and E. Swann and P. Wiseman and J. Asorey and G. F. Lewis and R. Sharp and B. E. Tucker and M. Aguena and S. Allam and S. Avila and E. Bertin and D. Brooks and D. L. Burke and A. Carnero Rosell and M. Carrasco Kind and J. Carretero and F. J. Castander and A. Choi and M. Costanzi and L. N. da Costa and M. E. S. Pereira and J. De Vicente and S. Desai and H. T. Diehl and P. Doel and S. Everett and I. Ferrero and P. Fosalba and J. Frieman and J. García-Bellido and E. Gaztanaga and D. W. Gerdes and D. Gruen and R. A. Gruendl and G. Gutierrez and D. L. Hollowood and K. Honscheid and B. Hoyle and D. J. James and K. Kuehn and N. Kuropatkin and M. A. G. Maia and P. Martini and F. Menanteau and R. Miquel and R. Morgan and A. Palmese and F. Paz-Chinchón and A. A. Plazas and A. K. Romer and E. Sanchez and V. Scarpine and S. Serrano and I. Sevilla-Noarbe and M. Soares-Santos and E. Suchyta and G. Tarle and D. Thomas and C. To and T. N. Varga and A. R. Walker and R. D. Wilkinson},
journal= {arXiv preprint arXiv:2012.07180},
year = {2021}
}