The Reliability of Type Ia Supernovae Delay Time Distributions Recovered from Galaxy Star Formation Histories

Abstract

We present a numerical analysis investigating the reliability of type Ia supernova (SN~Ia) delay-time distributions recovered from individual host galaxy star-formation histories. We utilize star-formation histories of mock samples of galaxies generated from the IllustrisTNG simulation at two redshifts to recover delay-time distributions. The delay-time distributions are constructed through piecewise constants as opposed to typically employed parametric forms such as power-laws or Gaussian or skew/log-normal functions. The SN~Ia delay-time distributions are recovered through a Markov Chain Monte Carlo exploration of the likelihood space by comparing the expected SN Ia rate within each mock galaxy to the observed rate. We show that a reduced representative sample of \emph{non-host} galaxies is sufficient to reliably recover delay-time distributions while simultaneously reducing the computational load. We also highlight a potential systematic between recovered delay-time distributions and the mass-weighted ages of the underlying host galaxy stellar population.