Neutron stars mergers in a stochastic chemical evolution model: impact of time delay distributions

TL;DR

This paper models the evolution of europium to iron ratios in the Galactic halo using a stochastic chemical evolution model with neutron star merger delay times, successfully reproducing observed data and dispersions.

Contribution

It introduces a stochastic model with a power-law delay time distribution for neutron star mergers, improving understanding of europium enrichment in the galaxy.

Findings

The model reproduces the observed [Eu/Fe] trend and spread.

A delay time distribution proportional to t^{-1.5} fits the data.

A variable fraction of neutron star progenitors explains dispersion.

Abstract

We study the evolution of the [Eu/Fe] ratio in the Galactic halo by means of a stochastic chemical evolution model considering merging neutron stars as polluters of europium. We improved our previous stochastic chemical evolution model by adding a time delay distribution for the coalescence of the neutron stars, instead of constant delays. The stochastic chemical evolution model can reproduce the trend and the observed spread in the [Eu/Fe] data with neutron star mergers as unique producers if we assume: i) a delay time distribution $\propto t^{-1.5}$, ii) a $M_{Eu}= 1.5$x$10^{-6} M_{\odot}$ per event, iii) progenitors of neutron stars in the range $9-50M_{\odot}$ and iv) a constant fraction of massive stars in the initial mass function (0.02) that produce neutron star mergers. Our best model is obtained by relaxing point iv) and assuming a fraction that varies with metallicity. We confirm that the mixed scenario with both merging neutron stars and supernovae as europium producers can provide a good agreement with the data relaxing the constraints on the distribution time delays for the coalescence of neutron stars. Adopting our best model, we also reproduce the dispersion of [Eu/Fe] at a given metallicity, which depends on the fraction of massive stars that produce neutron star mergers. Future high-resolution spectroscopic surveys, such as 4MOST and WEAVE, will produce the necessary statistics to constrain at best this parameter.