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arxiv: 1901.09938 · v2 · pith:HQC2X6YRnew · submitted 2019-01-28 · 🌌 astro-ph.GA · astro-ph.HE· astro-ph.SR

The chemical evolution of r-process elements from neutron star mergers: the role of a 2-phase interstellar medium

classification 🌌 astro-ph.GA astro-ph.HEastro-ph.SR
keywords phaseyieldsalphamodelsccsnechemicalcoldelements
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Neutron star mergers (NM) are a plausible source of heavy r-process elements such as Europium, but previous chemical evolution models have either failed to reproduce the observed Europium trends for Milky Way thick disc stars (with [Fe/H] ~ -1) or have done so only by adopting unrealistically short merger timescales. Using analytic arguments and numerical simulations, we demonstrate that models with a single-phase interstellar medium (ISM) and metallicity-independent yields cannot reproduce observations showing [Eu/alpha] > 0 or [Eu/Fe] > [alpha/Fe] for alpha-elements such as Mg and Si. However, this problem is easily resolved if we allow for a 2-phase ISM, with hot-phase cooling times \tau_{cool} of order 1 Gyr and a larger fraction of NM yields injected directly into the cold star-forming phase relative to alpha-element yields from core collapse supernovae (ccSNe). We find good agreement with observations in models with a cold phase injection ratio f_{c,NM}/f_{c,ccSN} of order 2, and a characteristic merger timescale \tau_NM=150 Myr. We show that the observed super-solar [Eu/alpha] at intermediate metallicities implies that a significant fraction of Eu originates from NM or another source besides ccSNe, and that these non-ccSN yields are preferentially deposited in the star-forming phase of the ISM at early times.

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  1. Inferring the role of binary neutron star mergers in r-process nucleosynthesis with multi-messenger observations using Cosmic Explorer and Einstein Telescope

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    A new redshift-correlation technique with third-generation GW detectors can constrain the BNS contribution to cosmic r-process nucleosynthesis to 5-6% precision via Fisher forecasts on mock bright- and dark-siren data.