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/lognormal 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 nonhost 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.

Keywords

• Type Ia supernovae
• Galaxies
• Computational astronomy