Abstract

ABSTRACT Constraining the delay time distribution (DTD) of different supernova (SN) types can shed light on the time-scales of galaxy chemical enrichment and feedback processes affecting galaxy dynamics, and SN progenitor properties. Here, we present an approach to recover SN DTDs based on integral-field spectroscopy (IFS) of their host galaxies. Using a statistical analysis of a sample of 116 SNe in 102 galaxies, we evaluate different DTD models for SN types Ia (73), II (28), and Ib/c (15). We find the best SN Ia DTD fit to be a power law with an exponent α = −1.1 ± 0.3 (50 per cent confidence interval (C.I.)), and a time delay (between star formation and the first SNe) $\Delta = 50^{+100}_{-35}~\mathrm{Myr}$ (50 per cent C.I.). For core collapse (CC) SNe, both of the Zapartas et al. DTD models for single and binary stellar evolution are consistent with our results. For SNe II and Ib/c, we find a correlation with a Gaussian DTD model with $\sigma = 82^{+129}_{-23}~\mathrm{Myr}$ and $\sigma = 56^{+141}_{-9}~\mathrm{Myr}$ (50 per cent C.I.), respectively. This analysis demonstrates that IFS opens a new way of studying SN DTD models in the local Universe.

Highlights

  • Supernovae (SNe) represent an important source of stellar feedback and chemical enrichment of the interstellar medium

  • We will consider six probability maps for each galaxy: four of them are expected to correlate with the core collapse (CC) SN rate (SNR), and two of them correspond to the expected rate of Ia SN events

  • In the Gaussian delay-time distribution (DTD) model we vary the σ of the distribution from 10 to 700 Myr, and the Za and the Zab probability maps correspond to the SNR calculated from the Zapartas et al (2017) DTD models

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Summary

INTRODUCTION

Supernovae (SNe) represent an important source of stellar feedback and chemical enrichment of the interstellar medium. The DTD is the hypothetical SNR that would follow an instantaneous burst of star formation (the expected number of SNe as a function of time per unit stellar mass formed). De Donder & Vanbeveren 2003; Eldridge et al 2015; Schady et al 2019; Zapartas 2019) have explored the impact of CCSNe on the DTD We expect that these massive stars interact with their companions, transferring mass through Roche-lobe overflow (Poelarends et al 2017; Iłkiewicz et al 2019; Naiman et al 2020), common-envelope phases (Lohev et al 2019; Grichener & Soker 2019), or mergers.

DATA SAMPLE
Reconstruction of the star formation history
Delay time distribution
STATISTICAL ANALYSIS
Probability maps
Fiducial parameters
Cumulative distribution
STATISTICAL ANALYSIS SIMULATIONS
DISCUSSION AND CONCLUSIONS
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