Neutron stars mergers in a stochastic chemical evolution model: impact of time delay distributions. Issue 1 (3rd February 2021)

• Record Type: Journal Article
• Authors: Cavallo, L; Cescutti, G; Matteucci, F
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 503:Issue 1(2021)
• Page Start: 1
• Page End: 12
• Publication Date: 2021-02-03
• Subjects: nuclear reactions, nucleosynthesis, abundances -- stars: abundances -- binaries: close -- stars: neutron -- Galaxy: evolution -- Galaxy: halo; Astronomy -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnras/stab281
• Languages: English
• ISSNs: 0035-8711

Abstract

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 ∝ t −1.5, (ii) an $M_{\boldsymbol{ Eu}}= 3 \times 10^{-6} \, \boldsymbol{M}_{\odot }$ per event, (iii) progenitors of neutron stars in the range $9\!-\!50\, \boldsymbol{M}_{\odot}$, 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.