The numerical solution of relativistic hydrodynamics equations in conservative form requires root-finding algorithms that invert the conservative-to-primitive variables map. These algorithms employ the equation of state of the fluid and can be comput
ationally demanding for applications involving sophisticated microphysics models. This work explores the use of machine learning methods to speed up the recovery of primitives in relativistic hydrodynamics. Artificial neural networks are trained to replace either the interpolations of a tabulated equation of state or directly the conservative-to-primitive map. The application of these neural networks to simple benchmark problems show that both approaches improve over traditional root finders with tabular equation-of-state and multi-dimensional interpolations. In particular, the neural networks for the conservative-to-primitive map accelerate the variable recovery by more than an order of magnitude over standard methods while maintaining accuracy. Neural networks are thus an interesting option to improve the speed and robustness of relativistic hydrodynamics algorithms.
We present ${tt bajes}$, a parallel and lightweight framework for Bayesian inference of multimessenger transients. ${tt bajes}$ is a Python modular package with minimal dependencies on external libraries adaptable to the majority of the Bayesian mode
ls and to various sampling methods. We describe the general workflow and the parameter estimation pipeline for compact-binary-coalescence gravitational-wave transients. The latter is validated against injections of binary black hole and binary neutron star waveforms, including confidence interval tests that demonstrates the inference is well-calibrated. Binary neutron star postmerger injections are also studied using a network of five detectors made of LIGO, Virgo, KAGRA and Einstein Telescope. Postmerger signals will be detectable for sources at ${lesssim}80,$Mpc, with Einstein Telescope contributing over 90% of the total signal-to-noise ratio. As a full scale application, we re-analyze the GWTC-1 black hole transients using the effective-one-body ${tt TEOBResumS}$ approximant, and reproduce selected results with other approximants. ${tt bajes}$ inferences are consistent with previous results; the direct comparison of ${tt bajes}$ and ${tt bilby}$ analyses of GW150914 shows a maximum Jensen-Shannon divergence of $5.2{times}10^{-4}$. GW170817 is re-analyzed using ${tt TaylorF2}$ with 5.5PN point-mass and 7.5PN tides, ${tt TEOBResumSPA}$, and ${tt IMRPhenomPv2_NRTidal}$ with different cutoff-frequencies of $1024,$Hz and $2048,$Hz. We find that the former choice minimizes systematics on the reduced tidal parameter, while a larger amount of tidal information is gained with the latter choice. ${tt bajes}$ can perform these analyses in about 1~day using 128 CPUs.
The joint detection of the gravitational wave GW170817, of the short $gamma$-ray burst GRB170817A and of the kilonova AT2017gfo, generated by the the binary neutron star merger observed on August 17, 2017, is a milestone in multimessenger astronomy a
nd provides new constraints on the neutron star equation of state. We perform Bayesian inference and model selection on AT2017gfo using semi-analytical, multi-components models that also account for non-spherical ejecta. Observational data favor anisotropic geometries to spherically symmetric profiles, with a log-Bayes factor of ${sim}10^{4}$, and favor multi-component models against single-component ones. The best fitting model is an anisotropic three-component composed of dynamical ejecta plus neutrino and viscous winds. Using the dynamical ejecta parameters inferred from the best-fitting model and numerical-relativity relations connecting the ejecta properties to the binary properties, we constrain the binary mass ratio to $q<1.54$ and the reduced tidal parameter to $120<tildeLambda<1110$. Finally, we combine the predictions from AT2017gfo with those from GW170817, constraining the radius of a neutron star of $1.4~{rm M}_odot$ to $12.2pm0.5~{rm km}$ ($1sigma$ level). This prediction could be further strengthened by improving kilonova models with numerical-relativity information.
We present fitting formulae for the dynamical ejecta properties and remnant disk masses from a large sample of numerical relativity simulations. The considered data include some of the latest simulations with microphysical nuclear equations of state
(EOS) and neutrino transport as well as other results with polytropic EOS available in the literature. Our analysis indicates that the broad features of the dynamical ejecta and disk properties can be captured by fitting expressions that depend on mass ratio and reduced tidal parameter. The comparative analysis of literature data shows that microphysics and neutrino absorption have a significant impact on the dynamical ejecta properties. Microphysical nuclear equations of state lead to average velocities smaller than polytropic EOS, while including neutrino absorption results in larger average ejecta masses and electron fractions. Hence, microphysics and neutrino transport are necessary to obtain quantitative models of the ejecta in terms of the binary parameters.
We present new numerical relativity results of neutron star mergers with chirp mass $1.188M_odot$ and mass ratios $q=1.67$ and $q=1.8$ using finite-temperature equations of state (EOS), approximate neutrino transport and a subgrid model for magnetohy
drodynamics-induced turbulent viscosity. The EOS are compatible with nuclear and astrophysical constraints and include a new microphysical model derived from ab-initio calculations based on the Brueckner-Hartree-Fock approach. We report for the first time evidence for accretion-induced prompt collapse in high-mass-ratio mergers, in which the tidal disruption of the companion and its accretion onto the primary star determine prompt black hole formation. As a result of the tidal disruption, an accretion disc of neutron-rich and cold matter forms with baryon masses ${sim}0.15M_odot$, and it is significantly heavier than the remnant discs in equal-masses prompt collapse mergers. Massive dynamical ejecta of order ${sim}0.01M_odot$ also originate from the tidal disruption. They are neutron rich and expand from the orbital plane with a crescent-like geometry. Consequently, bright, red and temporally extended kilonova emission is predicted from these mergers. Our results show that prompt black hole mergers can power bright electromagnetic counterparts for high-mass-ratio binaries, and that the binary mass ratio can be in principle constrained from multimessenger observations.
With the first observation of a binary neutron star merger through gravitational waves and light GW170817, compact binary mergers have now taken the center stage in nuclear astrophysics. They are thought to be one of the main astrophysical sites of p
roduction of r-process elements, and merger observations have become a fundamental tool to constrain the properties of matter. Here, we review our current understanding of the dynamics of neutron star mergers, in general, and of GW170817 in particular. We discuss the physical processes governing the inspiral, merger, and postmerger evolution, and we highlight the connections between these processes, the dynamics, and the multimessenger observables. Finally, we discuss open questions and issues in the field and the need to address them through a combination of better theoretical models and new observations.
The gravitational-wave GW170817 is associated to the inspiral phase of a binary neutron star coalescence event. The LIGO-Virgo detectors sensitivity at high frequencies was not sufficient to detect the signal corresponding to the merger and post-merg
er phases. Hence, the question whether the merger outcome was a prompt black hole formation or not must be answered using either the pre-merger gravitational wave signal or electromagnetic counterparts. In this work we present two methods to infer the probability of prompt black hole formation, using the analysis of the inspiral gravitational-wave signal. Both methods combine the posterior distribution from the gravitational-wave data analysis with numerical relativity results. One method relies on the use of phenomenological models for the equation of state and on the estimate of the collapse threshold mass. The other is based on the estimate of the tidal polarizability parameter $tilde{Lambda}$ that is correlated in an equation-of-state agnostic way with the prompt BH formation. We analyze GW170817 data and find that the two methods consistently predict a probability of ~ 50-70% for prompt black-hole formation, which however may significantly decrease below 10% if the maximum mass constraint from PSR J0348+0432 or PSR J0740+6620 is imposed.
Observations of gravitational waves and their electromagnetic counterparts may soon uncover the existence of coalescing compact binary systems formed by a stellar-mass black hole and a neutron star. These mergers result in a remnant black hole, possi
bly surrounded by an accretion disk. The mass and spin of the remnant black hole depend on the properties of the coalescing binary. We construct a map from the binary components to the remnant black hole using a sample of numerical-relativity simulations of different mass ratios $q$, (anti-)aligned dimensionless spins of the black hole $a_{rm BH}$, and several neutron star equations of state. Given the binary total mass, the mass and spin of the remnant black hole can therefore be determined from the three parameters $(q,a_{rm BH},Lambda)$, where $Lambda$ is the tidal deformability of the neutron star. Our models also incorporate the binary black hole and test-mass limit cases and we discuss a simple extension for generic black hole spins. We combine the remnant characterization with recent population synthesis simulations for various metallicities of the progenitor stars that generated the binary system. We predict that black-hole-neutron-star mergers produce a population of remnant black holes with masses distributed around $7M_odot$ and $9M_odot$. For isotropic spin distributions, nonmassive accretion disks are favoured: no bright electromagnetic counterparts are expected in such mergers.
We present TEOBResumS, a new effective-one-body (EOB) waveform model for nonprecessing (spin-aligned) and tidally interacting compact binaries.Spin-orbit and spin-spin effects are blended together by making use of the concept of centrifugal EOB radiu
s. The point-mass sector through merger and ringdown is informed by numerical relativity (NR) simulations of binary black holes (BBH) computed with the SpEC and BAM codes. An improved, NR-based phenomenological description of the postmerger waveform is developed.The tidal sector of TEOBResumS describes the dynamics of neutron star binaries up to merger and incorporates a resummed attractive potential motivated by recent advances in the post-Newtonian and gravitational self-force description of relativistic tidal interactions. Equation-of-state dependent self-spin interactions (monopole-quadrupole effects) are incorporated in the model using leading-order post-Newtonian results in a new expression of the centrifugal radius. TEOBResumS is compared to 135 SpEC and 19 BAM BBH waveforms. The maximum unfaithfulness to SpEC data $bar{F}$ -- at design Advanced-LIGO sensitivity and evaluated with total mass $M$ varying between $10M_odot leq M leq 200 M_odot$ --is always below $2.5 times 10^{-3}$ except for a single outlier that grazes the $7.1 times 10^{-3}$ level. When compared to BAM data, $bar{F}$ is smaller than $0.01$ except for a single outlier in one of the corners of the NR-covered parameter space, that reaches the $0.052$ level.TEOBResumS is also compatible, up to merger, to high end NR waveforms from binary neutron stars with spin effects and reduced initial eccentricity computed with the BAM and THC codes. The model is designed to generate accurate templates for the analysis of LIGO-Virgo data through merger and ringdown. We demonstrate its use by analyzing the publicly available data for GW150914.
We present the Computational Relativity CoRe collaborations public database of gravitational waveforms from binary neutron star mergers. The database currently contains 367 waveforms from numerical simulations that are consistent with general relativ
ity and that employ constraint satisfying initial data in hydrodynamical equilibrium. It spans 164 physically distinct configuration with different binary parameters (total binary mass, mass-ratio, initial separation, eccentricity, and stars spins) and simulated physics. Waveforms computed at multiple grid resolutions and extraction radii are provided for controlling numerical uncertainties. We also release an exemplary set of 18 hybrid waveforms constructed with a state-of-art effective-one-body model spanning the frequency band of advanced gravitational-wave detectors. We outline present and future applications of the database to gravitational-wave astronomy.
