Numerical Relativity Simulations of the Neutron Star Merger GW170817: Long-term Remnant Evolutions, Winds, Remnant Disks, and Nucleosynthesis

Abstract

We present a systematic numerical relativity study of the dynamical ejecta, winds, and nucleosynthesis in neutron star (NS) merger remnants. Binaries with the chirp mass compatible with GW170817, different mass ratios, and five microphysical equations of state (EOSs) are simulated with an approximate neutrino transport and a subgrid model for magnetohydrodynamic turbulence up to 100 ms postmerger. Spiral density waves propagating from the NS remnant to the disk trigger a wind with mass flux ∼0.1–0.5 M ⊙ s−1, which persists for the entire simulation as long as the remnant does not collapse to a black hole. This wind has average electron fraction ≳0.3 and average velocity ∼0.1–0.17 c and thus is a site for the production of weak r-process elements (mass number A < 195). Disks around long-lived remnants have masses ∼0.1–0.2 M ⊙, temperatures peaking at ≲10 MeV near the inner edge, and a characteristic double-peak distribution in entropy resulting from shocks propagating through the disk. The dynamical and spiral-wave ejecta computed in our targeted simulations are not compatible with those inferred from AT2017gfo using two-components kilonova models. Rather, they indicate that multicomponent kilonova models including disk winds are necessary to interpret AT2017gfo. The nucleosynthesis in the combined dynamical ejecta and spiral-wave wind in the long-lived mergers of comparable mass robustly accounts for all the r-process peaks, from mass number ∼75 to actinides in terms of solar abundances. Total abundances are weakly dependent on the EOS, while the mass ratio affects the production of first-peak elements.

Dynamical ejecta of neutron star mergers with nucleonic weak processes I: nucleosynthesis

“…In recent years, a variety of publications have focused on the dynamically ejected material from NS-NS mergers (e.g. Wanajo et al 2014 ;Palenzuela et al 2015 ;Sekiguchi et al 2015 ;Foucart et al 2016Foucart et al , 2020Lehner et al 2016 ;Bovard et al 2017 ;Martin et al 2018 ;Radice et al 2018a ;Nedora et al 2021a ). Ho we ver, only a subset of the simulations available in the literature includes neutrino absorption and in addition performs r-process nucleosynthesis network calculations.…”

“…In our simulations, we perform one r-process calculation per unbound SPH mass element, following its detailed expansion history. A subset of models by Radice et al ( 2018a ) as well as Nedora et al ( 2021a ) employs general-relativistic large eddy simulations (GRLES) calibrated to mimic viscosity due to magnetohydrodynamic turbulence. Since the GRLES simulations of Radice et al ( 2018a ) do not include neutrino absorption, we only compare to the calculations without GRLES in the following.…”

The Challenges Ahead for Multimessenger Analyses of Gravitational Waves and Kilonova: A Case Study on GW190425

“…Since lanthanides have many absorption lines, this will cause the ejecta to be very opaque, and so we will use an effective gray 18 opacity for this component between 1 and 10 cm 2 g −1 for both BHNS and BNS systems. However, for (especially symmetric) BNS mergers, the dynamical ejecta includes shock heated ejecta on top of the tidal tail that are predicted to have a lower lanthanide fraction, and thus a lower opacity (see, e.g., Sekiguchi et al 2016;Dietrich & Ujevic 2017;Tanaka et al 2020;Nedora et al 2021). For simplicity, we assume that this component does not contribute significantly compared to the tidal tail.…”

Machine Learning for Conservative-to-Primitive in Relativistic Hydrodynamics

“…In this section we present comparative timing and accuracy tests of the developed NNs. Section 3.1 directly considers different C2P algorithms using NNs and compares them against a standard algorithm for the C2P used in current numerical relativity simulations of neutron stars spacetimes [17][18][19]. Sections 3.2 and 3.3 consider the use of different C2P algorithms with NNs in two standard 1D benchmarks for relativistic hydrodynamics implementations: a relativistic shock tube (problem 1 of [1]) and the evolution of a smooth density profile.…”

“…For example, general relativistic simulation of neutron star mergers with microphysics typically employ a C2P procedure composed of two nested root finders (Newton-Raphson algorithms) during which 3D interpolations of EOS tables are performed to find the searched-for variable (e.g., the pressure p(ρ, T, Y e )), e.g., [15][16][17]. This procedure is called at each grid point for each time subcycle, resulting in more than 10 9 calls per millisecond of evolution in simulations that currently span up to hundreds of milliseconds [17][18][19]. The computational cost of the C2P amounts up to ∼18% of the total cost for computing the r.h.s.…”