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29 results for “Neutron star mergers”
Binary Neutron Star Mergers: Mass Ejection, Electromagnetic Counterparts, and Nucleosynthesis
<p>We release dynamical ejecta data from binary neutron star merger simulations. The outflows are extracted at a fixed coordinate sphere with radius 300 G/c^2 Msun (= 443 km). Only material unbound according to the geodesic criterion is considered to be part of the dynamical ejecta. See [1] for more details.</p> <p>Included data:</p> <ul> <li>`Table2.txt`: Table 2 of the paper in machine readable format</li> <li>`tabulated_nucsyn.h5`: nucleosynthesis yields from pre-computed parametrized trajectories. The first three indices of each dataset are Ye, entropy, and expansion timescale tau. For example `Y_final[iYe, ientr, itau, iiso]` gives the final abundance of isotope `iiso` with `A[iiso]` and `Z[iiso]` for a trajectory with initial Ye = `Ye[iYe]`, initial entropy `s[ientr]`, and expansion timescale `tau[itau]`.</li> <li>`tabulated_rho.h5`: gives the density at T = 6 GK corresponding to the Ye, entropy, and expansion timescale used in `tabulated_nucsyn.h5`.</li> <li>`[model].tar`: ejecta data for individual simulations. The naming convention is the same as in the paper.</li> </ul> <p>For each model we provide:</p> <ul> <li>`outflow.txt`: angle integrated outflow rate and cumulated ejecta mass. Data are given in units with Msun = G = c = 1 (eg, the conversion factor for time to seconds is 4.9258e-6).</li> <li>`hist_entropy.dat`: histogram of the ejecta as a function of the entropy (in kb)</li> <li>`hist_vinf.dat`: histogram of the ejecta as a function of the asymptotic velocity (in units of c)</li> <li>`hist_ye.dat`: histogram of the ejecta as a function of the electron fraction Ye.</li> <li>`profile.txt`: time integrated ejecta profiles as a function of the polar angle.</li> <li>`hist_vinf_theta.h5`: histograms of the ejecta as a function of the asymptotic velocity and the polar angle.</li> <li>`hist_ye_theta.h5`: histograms of the ejecta as a function of the asymptotic velocity and the polar angle.</li> <li>`hist_ye_entropy_tau.h5`: histograms of the ejecta as a function of Ye, entropy, and expansion timescale tau.</li> </ul> <p>Additionally we distribute:</p> <ul> <li>Initial data generated with LORENE and associated EOS tables.</li> <li>EOS tables used for the evolution</li> <li>Parameter file used for each simulation</li> </ul> <p>For the multidimensional histograms the indices are ordered as specified in the file name, ie the file `hist_ye_theta.h5` tabulates the ejecta mass as a function of Ye (first index) and polar angle theta (second index).</p> <p><br> [1] D. Radice, A. Perego, K. Hotokezaka, S. A. Fromm, S. Bernuzzi, and L. F. Roberts, <em>Binary Neutron Star Mergers: Mass Ejection, Electromagnetic Counterparts, and Nucleosynthesis</em>, <a href="https://dx.doi.org/10.3847/1538-4357/aaf054">ApJ 869:130 (2018)</a>, <a href="https://arxiv.org/abs/1809.11161">arXiv:1809.11161</a></p>
5,000 accretion disk trajectories from a double neutron star merger from Sprouse et al. ApJ 962 79 (2024)
<p>This dataset contains 5,000 trajectories from the 1.2 second long accretion disk simulation (with central black hole) of Sprouse et al. ApJ 962 79 (2024). Individual trajectories are contained in a folder labeled "trace_{tid}" where {tid} is the unique name of the trajectory. Each of these folders contains three files.</p> <p>The "initx.dat" file:</p> <ul> <li>The "initx.dat" file provides the initial mass fraction of the ejected material at a prescribed starting temperature and density using the SFHo equation of state.</li> <li>The columns of the "initx.dat" file are: Z (proton number), A (mass number), and X (mass fraction).</li> <li>The last column, X, should sum to unity by definition.</li> </ul> <p>The "metadata.dat" file:</p> <ul> <li>The "metadata.dat" file provides additional information about the ejected material.</li> <li>This file defines the trace id {tid}, the ejected mass, the maximum temperature reach in the simulation, the starting time, temperature, and density used to intialize the "initx.dat" file. </li> <li>The ejected mass associated with the trajectory can be used for the relative weighting of each trajectory.</li> <li>Units of associated quantities are defined in the file header (first line).</li> </ul> <p>The "trajectory.dat" file:</p> <ul> <li>The "trajectory.dat" file provides the time-dependent evolution of temperature (T), density (rho), radius (R) and electron fraction (Ye).</li> <li>This is the primary peace of information needed to run a nucleosynthesis network in post processing to determine the resultant abundances.</li> <li>Units of associated quantities are defined in the file header (first line).</li> </ul>
Observing Runs for Binary Neutron Star and Neutron Star-Black Hole mergers in the HLVK-Configuration during O4, using 20 million CBC injections (July 2024 edition)
<p>We have conducted a simulation of the HLVK configuration deployed during the ongoing O4 run. This project supports the training of kilonova regression with machine learning processes, requiring thousands of BNS to pass the threshold cutoff. Here we have 17,009 BNS passing the SNR threshold, along with 3,148 NSBH and 121,718 BBH, from 20 million CBCs injected. The upper-lower limit between NS and BH is 3 sun masses.</p> <p>However, due to size constraints, this repository contains only the simulation data and sky maps of BNS and NSBH detections that have passed the cutoff threshold. For the complete dataset, including BBH, please refer to <a href="../doi/10.5281/zenodo.12693652">https://zenodo.org/doi/10.5281/zenodo.12693652</a> .</p>
Parameter estimation catalogs for binary neutron star mergers detected with next-generation gravitational wave detectors
<div> <p>Next-generation gravitational wave (GW) observatories, such as the Einstein Telescope (ET) and the Cosmic Explorer, will provide access to the population of binary neutron star (BNS) mergers throughout cosmic history and yield precise parameter estimates. Here, we publish the results of a comprehensive study evaluating BNS merger detection prospects using the ET alone or in a network of current or next-generation detectors up to redshift equal to 1. We publicly release all the parameter estimation for 10 years of observations of BNSs in the form of catalogs. These catalogs are made available to the community for multi-messenger studies, multi-probe cosmology, and nuclear study to constrain the neutron star (NS) equation of state (EOS). They can be used to focus on specific events (for example golden events with high signal-to-noise ratio) or for statistical studies on the BNS populations. </p> <p>Our simulations assessed the perspectives for detecting the optical emission of BNS mergers in the era of next-generation detectors, considering how uncertainties in BNS population properties, NS mass distribution, and the EOS might affect the detection rate and parameter estimation. The study is published in <a href="https://arxiv.org/abs/2411.02342" target="_blank" rel="noopener">Loffredo, Hazra, Dupletsa, Branchesi et al. 2024</a> arXiv:2411.02342 (submitted to A&A).</p> </div> <h3>BNS merger rate</h3> <p>As shown in <a href="https://ui.adsabs.harvard.edu/abs/2021MNRAS.502.4877S/abstract" target="_blank" rel="noopener">Santoliquido et al. (2021)</a>, the common envelope ejection efficiency parameter, α, determines one of the main sources of uncertainty for the number of BNS mergers per year. In order to evaluate the impact of the uncertainties of the BNS merger rate normalization on our results, we generate two catalogues of BNS mergers assuming α to be either <strong>0.5</strong> or <strong>1.0</strong>. </p> <h3>NS mass distribution</h3> <p>We draw the component masses of the NS binaries, M_1 and M_2, from two different mass distributions: <strong>Gaussian</strong> and<br><strong>uniform</strong> mass distributions. The Gaussian distribution is centred at 1.33 M⊙ with a standard deviation of 0.09 M⊙. The uniform mass distribution ranges in [1.1 M⊙, M_max], where M_max depends on the selected EOS.</p> <h3>Equation of state (EOS)</h3> <p>Since the NS EOS affects both the GW and EM signals expected from BNS mergers, we consider<br>two different EOSs, namely the <strong>APR4</strong> and <strong>BLh</strong> microscopic EOSs.</p> <h3>Detector configuration</h3> <p>Given the two values of α (0.5 and 1.0), the two mass distributions (uniform and Gaussian), and the two EOSs (BLh and APR4), we have a total of 8 different population sets, which constitute our injections for the gravitational signal analysis. For each of these datasets, we consider the following GW detector configurations:</p> <ul> <li>ET in its triangular design of 10 km arms, located in Sardinia, alone and operating together with (<strong>ET_delta_10_cryo</strong>): <ul> <li>the current ground-based network LIGO-Hanford, LIGO-Livingston, Virgo, KAGRA, LIGO-India (<strong>LVKI</strong>) </li> <li>one L-shaped CE with 40 km arms, located in the USA (<strong>1CE</strong>)</li> <li>2 CEs, both with 40 km arms, one in the USA and one in Australia (<strong>2CE</strong>)</li> </ul> </li> <li>ET in its 2L-shaped interferometer configuration of 15 km arms misaligned at 45 deg (one located in Sardinia and the other in the Netherlands); we consider the same networks as above, using the 2L-configuration instead of the triangular one (<strong>ET_2L_15_cryo_45deg</strong>). </li> </ul> <p>We thus have eight different detector networks giving a total of 64 simulations available in this repository. </p> <h3>Catalog description</h3> <p>The parameter estimation of the injected GW signals by the various detector networks is obtained through the Fisher matrix software <strong>GWFish</strong> (<a href="https://ui.adsabs.harvard.edu/abs/2023A%26C....4200671D/abstract" target="_blank" rel="noopener">Dupletsa et al. 2023</a>). The Fisher analysis method approximates the likelihood with a multivariate Gaussian distribution. All the parameters [M_1, M_2, dL, ι, RA, DEC, Ψ, phase, tc, Λ_1, Λ_2] are considered for the Fisher matrix derivation. The uncertainties on parameters coming from the covariance matrix (the inverse of the Fisher matrix) are given at 1σ. We implement a duty cycle of 85% for each of the L-shaped detectors, and for each of the three nested detectors composing the triangle. </p> <ul> <li><strong>Signals_<em>{BNS_merger_rate}</em>_<em>{EOS}</em>_<em>{NS_mass_distribution}</em>_<em>{Detector_configuration}</em>.txt </strong>contains the parameters describing a GW event and the corresponding network signal-to-noise ratio (SNR) <ul> <li><strong>mass_1: </strong>primary mass of the binary in [Msol] (in detector frame) (M_1)</li> <li><strong>mass_2:</strong> secondary mass of the binary in [Msol] (in detector frame) (M_2)</li> <li><strong>luminosity_distance:</strong> the luminosity distance of the merger in [Mpc]</li> <li><strong>dec:</strong> declination angle in [rad]. It varies in [−𝜋/2,+𝜋/2]</li> <li><strong>ra:</strong> right ascension in [rad]. It varies in [0,2/𝑝𝑖]</li> <li><strong>theta_jn:</strong> the angle between the line of observation and the total angular momentum (orbital, spin and GR corrections) of the binary [rad] (it reduces to the so-called inclination angle or <strong>iota</strong> if the spin component is absent); it ranges in [0,𝜋]</li> <li><strong>psi:</strong> the polarization angle in [rad]; it ranges in [0,𝜋]</li> <li><strong>geocent_time:</strong> merger time as GPS time in [s]</li> <li><strong>phase:</strong> the initial phase of the merger in [rad]; it ranges in [0,2𝜋]</li> <li><strong>redshift: </strong>the redshift of the merger</li> <li><strong>lambda_1: </strong>dimensionless tidal polarizabilty of primary component</li> <li><strong>lambda_2:</strong> dimensionless tidal polarizabilty of secondary component</li> <li><strong>network_SNR:</strong> network SNR for a the given event</li> </ul> </li> <li><strong>Errors_<em>{BNS_merger_rate}</em>_<em>{EOS}</em>_<em>{NS_mass_distribution}</em>_<em>{Detector_configuration}</em>.txt </strong>contains the <div> <div>parameter errors for each event. The first column is <strong>network_SNR</strong>, the following columns repeat the injected parameters as above and the relative errors <strong>err_<em>{parameter}</em></strong><em>. </em>The last column is the error on sky localisation (<strong>err_sky_location</strong>) at 90% credible interval. </div> </div> </li> </ul> <h3>Further details </h3> <p>Further details on the assumptions we made to produce these catalogs can be found in <a href="https://arxiv.org/abs/2411.02342" target="_blank" rel="noopener">Loffredo et al. 2024</a>, while further details on GWFish can be found on <a href="https://colab.research.google.com/github/janosch314/GWFish/blob/main/gwfish_tutorial.ipynb" target="_blank" rel="noopener">this tutorial</a>. We also provide the jupyter notebook <strong>paper_plots.ipynb</strong>, to reproduce Figs. 10, 11, 13, D.1, D.5, D.6. </p>
Evolutionary Origins of Binary Neutron Star Mergers
<p>Input and data files required to reproduce Figures 1 and 2 from Gallegos-Garcia et al 2022, Evolutionary Origins of Binary Neutron Star Mergers.</p>
General-Relativistic Hydrodynamics Simulation of a Neutron Star — Sub-Solar-Mass Black Hole Merger - Gravitational Waveform
<p>This dataset contains the gravitational waveform for NSbh simulation. See the README.txt file for details.</p> <p>Simulations: Swami Vivekanandji Chaurasia (Stockholm University);</p> <p>Postprocessing: Maximiliano Ujevic (Universidade Federal do ABC) and Adrian Abac (Max Planck Institute for Gravitational Physics);</p> <p>Data release packaging: Ivan Markin (University of Potsdam);</p> <p>Simulations for the project have been performed on the national supercomputer HPE Apollo Hawk at the High Performance Computing (HPC) Center Stuttgart (HLRS) under the grant number GWanalysis/44189, on the GCS Supercomputer SuperMUC NG at the Leibniz Supercomputing Centre (LRZ) [project pn29ba], and on the HPC systems Lise/Emmy of the North German Supercomputing Alliance (HLRN) [project bbp00049] for the final production runs. The particular simulation has been run on HLRN.</p>
Self-consistent MHD simulation of jet launching in a neutron star - white dwarf merger: Complimentary material
<p>Complementary material to the paper.</p> <p>Movies showing different magnitudes during the evolution of the neutron-star white-dwarf merger. All the movies show slices through the orbital plane (on the left) and perpendicular to the orbital plane (on the right right) centred on the neutron star. The region where the gravitational potential is softened around the neutron star is outlined by a black-dashed line.<br> The different videos show the following magnitudes: the ratio between the magnetic pressure and gas pressure (beta), the density, the entropy, the absolute value of the magnetic field, the radial velocity with respect to the neutron-star and the temperature.</p> <p>For every magnitude there are two videos (_01rsol and _003rsol) showing them in a box of 0.1 and 0.03 solar radii respectively.</p>
Black Hole - Neutron Star Binary Mergers
Gravitational radiation waveforms for black hole-neutron star coalescence calculations. The physical input is Newtonian physics, an ideal gas equation of state with varying compressibility (through the index gamma), and point-mass gravitational radiation back reaction, which is switched off in the simulation once the star is tidally disrupted. All the simulations are 3D, done using SPH.
Binary Neutron Star Merger
Numerically-generated gravitational waveforms for binary neutron stars.
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