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49 results for “Binary neutron stars”
Data release for "Discovering neutron stars with LISA via measurements of orbital eccentricity in Galactic binaries"
<p>Posterior samples and code to reproduce all figures associated with <em>Discovering neutron stars with LISA via measurements of orbital eccentricity in Galactic binaries</em>.</p> <p>The <code>parameter_estimation</code> folder contains the following:</p> <ul> <li><code>campaigns</code>: Analyses of eccentric quasi-monochromatic binaries, gridding over gravitational-wave frequency, eccentricty, and SNR. See the <code>README</code> inside for more information. The resulting posteriors are used in Figure 3, and the fitting formula Eq. 21. </li> <li><code>fiducial_source_checks</code>: Analyses that vary parameters other than SNR and frequency to investigate the effect on the minimum eccentricity that can be recovered. Used in Figure A1. Posteriors used for Figure 4 are also found in the <code>golden_binary</code> folder. </li> <li><code>nhat_runs</code>: Various analyses used for Figures 5, 6, B1, and C1. See the <code>README</code> inside for more information. Also see the <code>README</code> in <code>eccentric_gb_scripts</code> and links therein.</li> </ul> <p>Within each parameter estimation output folder there are <code>.dat</code> files for quantities such as the source SNR, log evidence, and posterior. There are also configuration <code>.yaml</code> files which are used by the BALROG code. These contain:</p> <ul> <li><code>lisa_config</code>: Parameters describing the LISA mission, including the duration in seconds. </li> <li><code>nessai_opts</code>: Settings used by nessai (the sampler used in this work). </li> <li><code>priors</code>: Lower and upper limits used for each source parameter. </li> <li><code>sources</code>: Injected values for each source parameter.</li> </ul> <p>The <code>notebooks</code> folder contains code to produce Figures 2, 3, 4, 6, and A1. Also included are notebooks to produce the fitting formula Eq. 21 (<code>emin_grid.ipynb</code>), and to inspect analyses in the <code>campaigns</code> and <code>fiducial_source_checks</code> folders.</p> <p>The <code>eccentric_gb_scripts</code> folder contains code to produce Figures 1, 5, B1 and C1. See the <code>README</code> inside for more information.</p>
Novel modelling of ultracompact X-ray binary evolution - stable mass transfer from white dwarfs to neutron stars
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2017MNRAS.470L...6S/abstract">Novel modelling of ultracompact X-ray binary evolution - stable mass transfer from white dwarfs to neutron stars</a></p>
Light-curve and spectral properties of ultrastripped core-collapse supernovae leading to binary neutron stars
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2017MNRAS.466.2085M">Moriya et al. (2017)</a>. MESA version 7624.</p> <p>Publication DOI: <a href="https://doi.org/10.1093/mnras/stw3225">10.1093/mnras/stw3225</a></p>
Ultra-luminous X-ray sources and neutron-star-black-hole mergers from very massive close binaries at low metallicity
<p>MESA inlists, run_star_extras, and data associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2017A&A...604A..55M">Marchant et al. (2017)</a>. MESA version 8118.</p> <p>Publication DOI: <a href="https://doi.org/10.1051/0004-6361/201630188">10.1051/0004-6361/201630188</a></p> <p>Files are also available in a gihub repository <a href="https://github.com/orlox/mesa_input_data/tree/master/2016_ULX">here</a></p> <p>Upload includes post-processed simulation output in the files Z-XX.tar.xz, where XX represents the metallicity (Z-25.tar.gz is for a metallicity of log10(Z)=-2.5). Each folder inside the archive corresponds to a single MESA simulation, with the name indicating the value of log10(M_1), q=M2/M1 and the orbital period in days. For example, the directory 1.600_0.500_0.900 corresponds to the simulation with log10(M1/Msun)=1.6, M2/M1=0.5 and Porb=0.9 days. Each folder is also a MESA template folder, containing all input files neccesary to reproduce that individual simulation.</p> <p>The file summary_tables.tar.gz contains summarized information for each simulation in ascii format.</p>
Binary neutron-star simulation SXS:NSNS:0002
Simulation of a neutron-star binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Black-hole neutron-star binary simulation SXS:BHNS:0001
Simulation of a black-hole neutron-star binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Black-hole neutron-star binary simulation SXS:BHNS:0003
Simulation of a black-hole neutron-star binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Black-hole neutron-star binary simulation SXS:BHNS:0004
Simulation of a black-hole neutron-star binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Black-hole neutron-star binary simulation SXS:BHNS:0002
Simulation of a black-hole neutron-star binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Black-hole neutron-star binary simulation SXS:BHNS:0007
Simulation of a black-hole neutron-star binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
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>
Reproduction package for the paper "A strongly changing accretion morphology during the outburst decay of the neutron star X-ray binary 4U 1608-52"
<p>This is a basic reproduction package for the paper "A strongly changing accretion morphology during the outburst decay of the neutron star X-ray binary 4U 1608-52" by J. van den Eijnden et al. (2020). It provides reduced data sets, simulation scripts, X-ray spectral fits, and plotting scripts to allow the reproduction of the work performed in this paper. It also lists software used and data archives containing the public observational data. </p> <p>An open access version of the paper can be found at <a href="https://arxiv.org/abs/2002.04003">https://arxiv.org/abs/2002.04003</a>.</p>
Particle tracer and horizon data of equal-mass, binary neutron stars simulations
<p>We provide the particle tracer and black hole (BH) horizon data obtained from two binary neutron star (BNS) simulations performed with IllinoisGRMHD.</p> <p>The first dataset, MissingLink_gammalaw_particle_data.tar.bz2, contains data from a magnetized, equal-mass BNS simulation of the missing link initial data. The equation of state (EOS) used was a simple gamma-law with Gamma=2.</p> <p>The second dataset, Magnetized_equalmass_BNS_LS220_particle_data.tar.bz2, contains data from a magnetized, equal-mass BNS simulation that employs an advanced, tabulated EOS—LS220.</p> <p>Both simulations have gone through inspiral, merger, and the formation of a remnant hypermassive neutron star that eventually collapses to a BH.</p>
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>
Black-hole neutron-star binary simulation SXS:BHNS:0009
Simulation of a black-hole neutron-star binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Black-hole neutron-star binary simulation SXS:BHNS:0010
Simulation of a black-hole neutron-star binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
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>
The input files and associated data products for "Modeling High Mass X-ray Binaries to Double Neutron Stars through Common Envelope Evolution"
<p>Simulations were made using the version 12115 of the MESA code together with the x86_64-linux-20190830 MESA SDK. "template.zip" provides the MESA inlist files to reproduce our simulations. "CE_1.zip" provides our simulated results for a grid of binary systems with common envelope ejection efficiencies set to be 1.0. Different folders indicate the binary systems with different initial parameters. Inside each folder information can be found for binary properties in the "history.data" file. Each folder also contains the "result.txt" file with the terminal output of the simulation. "CE_3.zip", "CE_0.3.zip" and "CE_0.1.zip" are the same as "CE_1.zip" but with common envelope ejection efficiencies set to be 3.0, 0.3 and 0.1, respectively.</p>
Binary neutron-star simulation SXS:NSNS:0001
Simulation of a neutron-star binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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International Brain Laboratory public data
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OpenNeuro
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