Estimating Transient Rates from Cosmological Simulations and BPASS

TL;DR

This paper predicts electromagnetic and gravitational wave transient rates over cosmic history by combining BPASS results with various star formation histories, highlighting the impact of metallicity evolution and the choice of star formation models.

Contribution

It introduces a comprehensive analysis of transient rate predictions using multiple cosmic star formation histories and emphasizes the importance of realistic metallicity evolution models.

Findings

Star formation history choice significantly affects transient rate predictions.

Long-delay transients depend heavily on metallicity evolution.

Simple metallicity models are inadequate for long-delay, metallicity-sensitive events.

Abstract

The detection rate of electromagnetic (EM) and gravitational wave (GW) transients is growing exponentially. As the accuracy of the transient rates will significantly improve over the coming decades, so will our understanding of their evolution through cosmic history. To this end, we present predicted rates for EM and GW transients over the age of the Universe using Binary Population and Spectral Synthesis (BPASS) results combined with four cosmic star formation histories (SFH). These include a widely used empirical SFH of Madau & Dickinson and those from three cosmological simulations: MilliMillennium, EAGLE and IllustrisTNG. We find that the choice of SFH significantly changes our predictions: transients with short delay times are most affected by the star formation rate, while long-delay time events tend to depend on the metallicity evolution of star formation. Importantly we find that the cosmological simulations have very different metallicity evolution that cannot be reproduced by the widely used metallicity model of Langer & Norman, which impacts the binary black hole merger and stripped-envelope supernovae rates in the local Universe most acutely. We recommend against using simple prescriptions for the metallicity evolution of the Universe when predicting the rates of events that can have long delay times and that are sensitive to metallicity evolution.