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opencc-by-4.0Sep 2024View details →

Parameter estimation catalogs for binary neutron star mergers detected with next-generation gravitational wave detectors

<div> 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.  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). </div> <h3>BNS merger rate</h3> 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 0.5 or 1.0.  <h3>NS mass distribution</h3> We draw the component masses of the NS binaries, M_1 and M_2, from two different mass distributions: Gaussian and uniform 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. <h3>Equation of state (EOS)</h3> Since the NS EOS affects both the GW and EM signals expected from BNS mergers, we consider two different EOSs, namely the APR4 and BLh microscopic EOSs. <h3>Detector configuration</h3> 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: <ul> <li>ET in its triangular design of 10 km arms, located in Sardinia, alone and operating together with (ET_delta_10_cryo): <ul> <li>the current ground-based network LIGO-Hanford, LIGO-Livingston, Virgo, KAGRA, LIGO-India (LVKI) </li> <li>one L-shaped CE with 40 km arms, located in the USA (1CE)</li> <li>2 CEs, both with 40 km arms, one in the USA and one in Australia (2CE)</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 (ET_2L_15_cryo_45deg). </li> </ul> We thus have eight different detector networks giving a total of 64 simulations available in this repository.  <h3>Catalog description</h3> The parameter estimation of the injected GW signals by the various detector networks is obtained through the Fisher matrix software GWFish (<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.  <ul> <li>Signals_{BNS_merger_rate}_{EOS}_{NS_mass_distribution}_{Detector_configuration}.txt  contains the parameters describing a GW event and the corresponding network signal-to-noise ratio (SNR) <ul> <li>mass_1: primary mass of the binary in [Msol] (in detector frame) (M_1)</li> <li>mass_2: secondary mass of the binary in [Msol] (in detector frame) (M_2)</li> <li>luminosity_distance: the luminosity distance of the merger in [Mpc]</li> <li>dec: declination angle in [rad]. It varies in  [−𝜋/2,+𝜋/2]</li> <li>ra: right ascension in [rad]. It varies in  [0,2/𝑝𝑖]</li> <li>theta_jn: 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 iota if the spin component is absent); it ranges in  [0,𝜋]</li> <li>psi: the polarization angle in [rad]; it ranges in  [0,𝜋]</li> <li>geocent_time: merger time as GPS time in [s]</li> <li>phase: the initial phase of the merger in [rad]; it ranges in  [0,2𝜋]</li> <li>redshift: the redshift of the merger</li> <li>lambda_1: dimensionless tidal polarizabilty of primary component</li> <li>lambda_2: dimensionless tidal polarizabilty of secondary component</li> <li>network_SNR: network SNR for a the given event</li> </ul> </li> <li>Errors_{BNS_merger_rate}_{EOS}_{NS_mass_distribution}_{Detector_configuration}.txt contains the  <div> <div>parameter errors for each event. The first column is network_SNR, the following columns repeat the injected parameters as above and the relative errors err_{parameter}. The last column is the error on sky localisation (err_sky_location) at 90% credible interval. </div> </div> </li> </ul> <h3>Further details </h3> 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 paper_plots.ipynb, to reproduce Figs. 10, 11, 13, D.1, D.5, D.6.

opencc-by-4.0Nov 2022View details →

Evolutionary Origins of Binary Neutron Star Mergers

Input and data files required to reproduce Figures 1 and 2 from Gallegos-Garcia et al 2022, Evolutionary Origins of Binary Neutron Star Mergers.

opencc-by-4.0May 2023View details →

General-Relativistic Hydrodynamics Simulation of a Neutron Star — Sub-Solar-Mass Black Hole Merger - Gravitational Waveform

This dataset contains the gravitational waveform for NSbh simulation. See the README.txt file for details. Simulations: Swami Vivekanandji Chaurasia (Stockholm University); Postprocessing: Maximiliano Ujevic (Universidade Federal do ABC) and Adrian Abac (Max Planck Institute for Gravitational Physics); Data release packaging: Ivan Markin (University of Potsdam); 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.

opencc-by-4.0Jun 2023View details →

Self-consistent MHD simulation of jet launching in a neutron star - white dwarf merger: Complimentary material

Complementary material to the paper. 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. 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. For every magnitude there are two videos (_01rsol and _003rsol) showing them in a box of 0.1 and 0.03 solar radii respectively.

opencc-by-4.0Jun 2020View details →

UV and X-ray observations of the neutron star LMXB EXO 0748-676 in its quiescent state

Data used in the manuscript "UV and X-ray observations of the neutron star LMXB EXO 0748-676 in its quiescent state" submitted to MNRAS

opencc-by-4.0Nov 2023View details →

GP ensemble of neutron star equations of state

GP ensemble of neutron star equations of state used in arXiv:2303.11356

opencc-by-4.0Nov 2024View details →

Black hole - neutron star initial data sequences

Black hole - neutron star initial data sequences, obtained as solutions to the constraint equations in the eXtended Conformal Thin-Sandwich formulation under the assumption of quasi-equilibrium. The data has been obtained using the v2 version of the publically available elliptic data solver FUKA.  Update as of 10th Feb 2025: Equations of state used to produce the QE sequences (and necessary for the reader executable) have been added.

opencc-by-4.0Nov 2021View details →

Datasets of GRMHD Simulations of Accreting Neutron Stars with Non-Dipole Fields

Datasets for GRMHD Simulations of Accreting Neutron Stars with Non-Dipole Fields

opencc-by-4.0Feb 2023View details →

Heat transport and convective velocities in compositionally-driven convection in neutron star and white dwarf interiors

MESA (version r22.11.1) inlists and source code used for the paper "Heat transport and convective velocities in compositionally-driven convection in neutron star and white dwarf interiors". cool_wd.zip contains the MESA files to reproduce the results discussed in section 4 of the paper. A Python-based Dedalus v3 script to reproduce the 3D numerical simulations presented in section 3 of the paper is included as Compositionally_driven_convection_3D_shell.py.

opencc-by-4.0Jan 2020View details →

Graphics: Evolutionary pathways leading to Double Neutron Star formation

Schematical representations of the evolutionary pathways leading to Double Neutron Stars formation as presented in the paper "Common–Envelope Episodes that lead to Double Neutron Star formation" (<a href="https://arxiv.org/abs/2001.09829">arXiv:2001.09829).</a> Contents: ./Channel_I/  - 00_Channel_I_circular.pdf     - 00_Channel_I_circular.png    - 00_Channel_I_vertical.jpg  - 00_Channel_I_vertical.pdf  - 00_Channel_I_horizontal.pdf      - 00_Channel_I_horizontal.jpg    - Channel_I_individual_pdfs.tar.gz  - Channel_I_individual_pngs.tar.gz ./Channel_II/  - 00_Channel_II_circular.jpg     - 00_Channel_II_circular.pdf      - 00_Channel_II_vertical.jpg  - 00_Channel_II_vertical.pdf  - 00_Channel_II_horizontal.jpg      - 00_Channel_II_horizontal.pdf      - Channel_II_individual_pdfs.tar.gz  - Channel_II_individual_pngs.tar.gz 00_Channel_*_circular.*, 00_Channel_*_vertical.* and 00_Channel_*_horizontal.* contain the figure of the specified formation channel in the specified format in a circular/vertical/horizontal direction. Channel_*_individual_*.tar.gz contain the individual figures for each formation channel in the specified format. If you use these illustrations please kindly include a citation to: A. Vigna-Gómez, M. MacLeod, C. J. Neijssel, F. S. Broekgaarden, S. Justham, G. Howitt, S. E. de Mink, S. Vinciguerra, and I. Mandel. Common envelope episodes that lead to doubleneutron star formation. PASA, 37:e038, Jan. 2020 (<a href="https://ui.adsabs.harvard.edu/abs/2020PASA...37...38V/abstract">ADS</a>)

opencc-by-4.0Oct 2020View details →

Multi-messenger constraints on the neutron-star equation of state and the Hubble constant -- Data and Codes

This repository contains the data and the codes used to produce the results presented in the article: "Multi-messenger constraints on the neutron-star equation of state and the Hubble constant " by Dietrich et al., arXiv:2002.11355 .  The uploaded software packages are snapshots of actively developed code. We refer to the original repositories: https://git.ligo.org/lscsoft/bilby https://git.ligo.org/lscsoft/parallel_bilby/  https://github.com/mcoughlin/gwemlightcurves https://git.ligo.org/lscsoft and to the original works for further details. In addition, we ask people to cite the original articles mentioned on the code repositories if some of the software packages are used. license: GNU General Public License agreement.

opencc-by-4.0Nov 2024View details →

The input files and associated data products for "Modeling High Mass X-ray Binaries to Double Neutron Stars through Common Envelope Evolution"

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.

opencc-by-4.0Dec 2018View details →

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>.