Neutrinos are copiously emitted by neutron star mergers, due to the high temperatures reached by dense matter during the merger and its aftermath. Neutrinos influence the merger dynamics and shape the properties of the ejecta, including the resulting
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Abstract r process nucleosynthesis and kilonova emission. In this work, we analyse neutrino emission from a large sample of binary neutron star merger simulations in Numerical Relativity, covering a broad range of initial masses, nuclear equation of state and viscosity treatments. We extract neutrino luminosities and mean energies, and compute quantities of interest such as the peak values, peak broadnesses, time averages and decrease time scales. We provide a systematic description of such quantities, including their dependence on the initial parameters of the system. We find that for equalmass systems the total neutrino luminosity (several ) decreases as the reduced tidal deformability increases, as a consequence of the less violent merger dynamics. Similarly, tidal disruption in asymmetric mergers leads to systematically smaller luminosities. Peak luminosities can be twice as large as the average ones. Electron antineutrino luminosities dominate (initially by a factor of 23) over electron neutrino ones, while electron neutrinos and heavy flavour neutrinos have similar luminosities. Mean energies are nearly constantmore »$$10^{53}{\hbox {erg}~{\hbox {s}}^{1}}$$ ${10}^{53}\text{erg}\phantom{\rule{0ex}{0ex}}{\text{s}}^{1}$ 
ABSTRACT We develop a method to compute synthetic kilonova light curves that combine numerical relativity simulations of neutron star mergers and the SNEC radiation–hydrodynamics code. We describe our implementation of initial and boundary conditions, rprocess heating, and opacities for kilonova simulations. We validate our approach by carefully checking that energy conservation is satisfied and by comparing the SNEC results with those of two semianalytic lightcurve models. We apply our code to the calculation of colour light curves for three binaries having different mass ratios (equal and unequal mass) and different merger outcome (shortlived and longlived remnants). We study the sensitivity of our results to hydrodynamic effects, nuclear physics uncertainties in the heating rates, and duration of the merger simulations. We find that hydrodynamics effects are typically negligible and that homologous expansion is a good approximation in most cases. However, pressure forces can amplify the impact of uncertainties in the radioactive heating rates. We also study the impact of shocks possibly launched into the outflows by a relativistic jet. None of our models match AT2017gfo, the kilonova in GW170817. This points to possible deficiencies in our merger simulations and kilonova models that neglect nonLTE effects and possible additional energy injection frommore »

ABSTRACT We present a new momentbased energyintegrated neutrino transport code for neutron star merger simulations in general relativity. In the merger context, ours is the first code to include Doppler effects at all orders in υ/c, retaining all nonlinear neutrino–matter coupling terms. The code is validated with a stringent series of tests. We show that the inclusion of full neutrino–matter coupling terms is necessary to correctly capture the trapping of neutrinos in relativistically moving media, such as in differentially rotating merger remnants. We perform preliminary simulations proving the robustness of the scheme in simulating abinitio mergers to black hole collapse and longterm neutron star remnants up to ${\sim }70\,$ ms. The latter is the longest dynamical spacetime, 3D, general relativistic simulations with full neutrino transport to date. We compare results obtained at different resolutions and using two different closures for the moment scheme. We do not find evidences of significant outofthermodynamic equilibrium effects, such as bulk viscosity, on the postmerger dynamics or gravitational wave emission. Neutrino luminosities and average energies are in good agreement with theory expectations and previous simulations by other groups using similar schemes. We compare dynamical and early wind ejecta properties obtained with M1 and with ourmore »

ABSTRACT Strong magnetic fields play an important role in powering the emission of neutron stars. Nevertheless, a full understanding of the interior configuration of the field remains elusive. In this work, we present general relativistic magnetohydrodynamics (MHD) simulations of the magnetic field evolution in neutron stars lasting ${\sim } {880}\,$ms (∼6.5 Alfvén crossing periods) and up to resolutions of $0.1155\,$km using Athena++. We explore two different initial conditions, one with purely poloidal magnetic field and the other with a dominant toroidal component, and study the poloidal and toroidal field energies, the growth times of the various instabilitydriven oscillation modes, and turbulence. We find that the purely poloidal setup generates a toroidal field, which later decays exponentially reaching $1{{\ \rm per\ cent}}$ of the total magnetic energy, showing no evidence of reaching equilibrium. The initially stronger toroidal field setup, on the other hand, loses up to 20 per cent of toroidal energy and maintains this state till the end of our simulation. We also explore the hypothesis, drawn from previous MHD simulations, that turbulence plays an important role in the quasiequilibrium state. An analysis of the spectra in our higher resolution setups reveals, however, that in most cases we are not observing turbulence atmore »

The numerical solution of relativistic hydrodynamics equations in conservative form requires rootfinding algorithms that invert the conservativetoprimitive variables map. These algorithms employ the equation of state of the fluid and can be computationally demanding for applications involving sophisticated microphysics models, such as those required to calculate accurate gravitational wave signals in numerical relativity simulations of binary neutron stars. 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 conservativetoprimitive map. The application of these neural networks to simple benchmark problems shows that both approaches improve over traditional root finders with tabular equationofstate and multidimensional interpolations. In particular, the neural networks for the conservativetoprimitive 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.

Using a data set of approximately 2 million phenomenological equations of state consistent with observational constraints, we construct new equationofstateinsensitive universal relations that exist between the multipolar tidal deformability parameters of neutron stars, Λl, for several highorder multipoles (l=5,6,7,8), and we consider finitesize effects of these highorder multipoles in waveform modeling. We also confirm the existence of a universal relation between the radius of the 1.4M⊙ NS, R1.4 and the reduced tidal parameter of the binary, Λ˜, and the chirp mass. We extend this relation to a large number of chirp masses and to the radii of isolated NSs of different mass M, RM. We find that there is an optimal value of M for every M such that the uncertainty in the estimate of RM is minimized when using the relation. We discuss the utility and implications of these relations for the upcoming LIGO O4 run and thirdgeneration detectors.