Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
96
datasets available to search
ShareScore release 0.7.1
Dataset results
96 results for “binary star”
Catalogs of Eclipsing Binaries with Pulsating Components, δ Scuti stars and γ Doradus stars
<p>I present a comprehensive, up-to-date catalog of <strong>3324</strong> <strong>eclipsing binary star systems containing pulsating components </strong>(not updated in this version). The initial compilation builds upon existing lists of `oscillating Algol-type eclipsing binaries' (oEA) harboring δ Scuti stars. However, the catalog expands upon this foundation to encompass a broader range of pulsating binary systems identified in recent years. This new catalog is valuable for researchers studying binary stars' evolution and pulsating stars. It incorporates various pulsating variable types across the Hertzsprung-Russell diagram, including δ Scuti stars, γ Doradus stars, β Cephei stars, Cepheids, and red giants exhibiting solar-like oscillations. However, this catalog is NOT an exhaustive list of eclipsing binaries with pulsating components of the above types and it is subject to updates. </p> <p>Many stars in this catalog are potentially interesting for further studies. Due to potential blending and contamination in TESS photometry, the binarity of a few pulsating stars could be attributed to neighboring eclipsing binaries. Follow-up studies of individual systems are necessary to resolve contamination issues and accurately identify the true source of variability. If you use part of the catalog in your research, please cite: Zhou, A.-Y., 2010, arXiv e-prints (DOI: 10.48550/arXiv.1002.2729) (ADS: https://ui.adsabs.harvard.edu/abs/2010arXiv1002.2729Z/abstract)</p> <p>In addition, I have also included the up-to-date catalogs of <strong>118,410 δ Scuti stars</strong> and <strong>41,622 γ Doradus stars</strong>, featuring thousands of unpublished discoveries. For these two catalogs, please cite: </p> <p>Zhou, Ai-Ying, 2024, New Astronomy, Volume 105, 102081 (Published: January 2024)</p> <p>Paper in ADS: https://ui.adsabs.harvard.edu/abs/2024NewA..10502081Z/abstract</p> <p>Paper in Publisher web: https://www.sciencedirect.com/science/article/pii/S1384107623000829</p> <p>Thanks for your reading. Your comments are more than welcome!</p>
SEVN parameter file from the paper "Binary neutron star populations in the Milky Way" by Sgalletta et al., 2023
<p>The repository contains the runtime parameters used in the SEVN simulations analysed in the paper "Binary neutron star populations in the Milky Way" by Sgalletta et al., 2023.</p> <p><strong>Repository content: </strong></p> <p>- <em>used_params_Sgalletta2023.txt<br> </em>The file contains all the runtime parameters used in the SEVN simulations. The parameters that have been varied in different runs are indicated with **** and the explored values are reported in the comment. See the SEVN userguide (<a href="https://gitlab.com/sevncodes/sevn/-/blob/SEVN/resources/SEVN_userguide.pdf">https://gitlab.com/sevncodes/sevn/-/blob/SEVN/resources/SEVN_userguide.pdf</a>) for the description of each parameter </p> <p> </p>
Data release for "Rapid pre-merger localization of binary neutron stars in third generation gravitational wave detectors"
<p>We publish skymap files in fits format of the simulation in our work "Rapid pre-merger localization of binary neutron stars in third generation gravitational wave detectors". There are 68000 BNS events, and results of different negative latencies are zipped in different tar files. An example jupyter notebook for using the data is provided.</p> <p> </p> <p> </p>
Evolution of binary stars on the HR diagram
<p>We studied the evolution of different classes of binary objects that can be observed in a typical stellar cluster, using a grid of detailed massive binary evolution models (Wang et al. 2020) with an initial metallicity of that of the Small Magellanic Cloud (SMC). To compute the models, we use the 1D stellar evolution code MESA (Modules for Experiments in Stellar Astrophysics, Paxton et al. 2011, 2013, 2015, 2018, version 8845).</p> <p>Our grid consists of 2078 binary models with initial primary masses greater than 5 MSun. This translates to a total cluster mass of ∼10^5 MSun in stars between 0.1 to 100 MSun (assuming a binary fraction of 1. The grid covers an initial mass ratio (mass of secondary over the mass of primary, hence always less than 1) range of 0.3-0.95 and orbital periods of 1 day to 8.6 yrs. In this range of masses, mass ratios, and orbital periods, a Monte Carlo method was used to sample initial binary model parameters assuming a Saltpeter initial mass function (IMF) (Salpeter 1955), a flat distribution of mass ratios and logarithm of initial orbital periods.</p> <p>Translucent grey circles indicate pre-interaction binaries - binaries that have not yet undergone a mass transfer phase via Roche Lobe overflow. Hence, the grey line traced on the HRD by the collection of pre-interaction binaries together essentially denotes the Single Star Isochrone (SSI). Grey squares indicate the merger product when we expect a binary to merge during the Case A mass transfer phase. We note that we only model and follow the evolution of Main Sequence mergers and not the mergers coming from the Case B channel. As such, the number of mergers in each frame is likely to be the lower limit to the number of merger products. Single star tracks at SMC metallicity are also plotted in the background from 5-100 MSun. When any component of a binary system completes core carbon burning at a certain cluster age (or helium-burning for the most massive stars), we mark the occurrence of a supernova by putting an ‘*’ symbol in the HRD, that fades over three time steps in the animation.</p> <p>Mass donors and accretors are shown with triangles and diamonds respectively. The binaries that are interacting or have interacted during their Main Sequence lifetime (i.e. the Case A models) are shown in colour, with the colour coding describing the rotation of the component stars (v rot /v crit ) of the binary. All donors and accretors of binaries that have interacted via Case B/C are shown in greyscale. A black frame around the triangles for the mass donor indicates that the surface Hydrogen mass fraction is less than 0.1. Similarly, a black frame around the diamonds for the mass accretors indicates that the surface Helium mass fraction is greater than 0.3. The current age of the cluster is displayed in the center bottom with a time bar that fills up as the animation moves forward in time.</p> <p>In the table above the legend, (from top) we indicate the number of Algol systems i.e. in the nuclear timescale slow Case A mass transfer phase, the number of Main Sequence merger products that are still burning hydrogen at the core, and the number of cool red supergiants (log T e f f < 3.7) at the respective time frames. Moreover, in the next two rows, we denote the number of OB stars that has a neutron star or black hole companion, arising from Case A and Case B evolution channels, at that cluster age. In the next row, we indicate the number of supernovae that have already happened until the current cluster age of the animation. We report the numbers of supernovae occurring from Case A and Case B donors separately from the other progenitors as we expect that the donor stars that have interacted via the Case A or Case B channels will be highly stripped of their envelopes and will likely be progenitors to stripped-envelope supernova (of type Ib and IIb) while the remaining will be progenitors to type IIp/n. The last line gives the number of pre-interacting binaries having luminosity lesser than the brightest non-interacted binary component by up to 1.5 dex.</p> <p>The individual components of the binaries that are in the semi-detached configuration and are interacting via the nuclear timescale slow Case A phase are joined together with solid black lines with an arrow indicating the direction of mass transfer (donor to the accretor). On the other hand, the individual components that have interacted in the past via Case A or B mass transfer are connected to each other with grey dotted lines. These are usually the systems where the donor star is a post-Main Sequence helium star and the accretor is a rejuvenated star still burning hydrogen at the core. The black and white dots over the Case A and B accretors denote that the donors of those binaries have imploded/exploded to form a black hole or neutron star respectively.</p>
Constraining the properties of dense neutron star cores: The case of the transient low-mass X-ray binary HETE J1900.1-2455
<p>This is a basic reproduction package for the paper "Constraining the properties of dense neutron star cores: The case of the transient low-mass X-ray binary HETE J1900.1-2455" by <a href="https://doi.org/10.1093/mnras/stab2202">N. Degenaar et al. (2021)</a>. It provides reduced data products, simulated data and 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>
Optical polarimetric observations of the black hole binary star Cyg X-1 with RoboPol
<p>The dataset contains raw FITS images of the black hole X-ray binary star <a href="https://simbad.cds.unistra.fr/simbad/sim-id?Ident=%402905066&Name=HD%20226868&submit=submit">Cyg X-1</a>, raw FITS images of a nearby field star used for the interstellar polarization correction and processed measurements of polarimetric standards used for the instrumental polarization correction. The dataset was obtained with the <a href="http://robopol.org">RoboPol</a> optical polarimeter in the R-band mounted at the 1.3 m telescope of the Skinakas Observatory, Greece. The data were collected between 13 May and 1 June 2022.<br> </p>
An observed population of intermediate-mass helium stars that have been stripped in binaries - theoretical, computational and observational data
<p>This Zenodo repository contains the observational and computational data presented in the manuscript "An observed population of intermediate-mass helium stars stripped in binaries" by Drout, Götberg, Ludwig, Groh, de Mink, O'Grady and Smith.</p><p>We organize the data as follows:</p><ul><li>The stacked spectra presented in Figures S16-S21 are located in stacked_spectra.tar.gz, which contains a text file for each star. The text files have three columns that correspond to wavelength in Angstrom, normalized counts, and errors, respectively.<br> </li><li>The spectral model grid computed based on binary evolutionary model output and presented in detail in the Supplementary information section S1.2.1, is labeled with names starting S121. The file S121_evol_based_006_absolute_magnitudes.txt contains the absolute AB magnitudes for the models in UV and optical filters. The .tar.gz S121_evol_based_006_spectra.tar.gz contains files with the full spectral energy distribution and normalized spectra of each model. The .tar.gz S121_evol_based_006_complete_models.tar.gz contains the full CMFGEN models.<br> </li><li>For the stellar atmosphere model grid presented in Supplementary material section S1.2.2, we refer to the Zenodo repository 10.5281/zenodo.7976200, which is made available in association with the second paper in our series. We note that we used a subset of that grid in the article associated with this Zenodo repository. We refer to section S1.2.2 for more details.<br> </li><li>The spectral models demonstrating the mass loss rate variations in Supplementary information section S1.2.3 are presented here with names starting with S123. There is one file containing the absolute magnitudes (S123_mdot_variation_absolute_magnitudes.txt), the S123_mdot_variation_spectra.tar.gz contains the spectral energy distributions and normalized spectra for each of the models, and the S123_mdot_variation_complete_models.tar.gz contains the full CMFGEN models.<br> </li><li>The spectral model grid computed based on main-sequence evolutionary model output and presented in detail in the Supplementary information section S1.3.1, is labeled with names starting S131. The file S131_MS_evol_based_006_absolute_magnitudes.tar.gz contains three files with the absolute AB magnitudes for the models in the UV and optical filters, each file corresponding to either 20%, 60%, or 90% through the main-sequence evolution and labeled f20, f60, and f90, respectively. S131_MS_evol_based_006_spectra.tar.gz contains three folders labeled f20, f60 and f90, which each contains the SEDs (in Flambda and ABmag) and normalized spectra for the corresponding models. The files S131_MS_evol_based_006_complete_models_fX0.tar.gz contain the complete CMFGEN models.<br> </li><li>The custom index files we use for astrometry.net in section S3.1.1 are located in the zip file called S311_astrometry_index_files.zip. This information was used to recalculate the astrometry on the Swift UVOT images of the Magellanic Clouds.<br> </li><li>To make Figure 2B, we calculated the equivalent widths for a set of models assuming a signal-to-noise ratio of 35. This procedure is described in Section S3.7.2. In Figure2B_Model_EWs.zip, we provide three files that each contain these modeled equivalent widths for (1) stripped star models, (2) OB star models, and (3) composite models. <br> </li><li>To make Figure S7 (see also Sections S1.2.3 and S2.2), which is similar to Figure 2B, but presents the effects of varying the wind mass loss of stripped stars, we used a similar set of modeled equivalent widths as when we produced Figure 2B. These modeled equivalent widths are provided in FigureS7_Model_EWs.zip. <br> </li><li>To make Figure 3, we calculated equivalent widths for the model grid described in Section S1.2.2 and the TLUSTY OB star grids (see Section S1.3.2) assuming a signal-to-noise ratio of 100. These model equivalent widths are provided in the file called Figure3_Model_EWs.zip. </li></ul>
Contact tracing of binary stars: Pathways to stellar mergers (online data)
<p><strong># Data for Henneco et al. (2024)</strong></p> <p>This repository contains the input files required to reproduce the MESAbinary models from Henneco et al. (2024). It also contains the full machine-readable version of Table G.1. For an overview of the quantities in each column, we refer to the notes underneath Table G.1 in the paper.</p> <p>MESA r12778<br>MESA SDK 20.3.2</p> <p><strong>## MESA_inlists</strong></p> <p>- <strong>inlist1</strong>: inlist for the initially more massive primary star</p> <p>- <strong>inlist2</strong>: inlist for the initially less massive secondary star</p> <p>-<strong> inlist_project</strong>: inlist for the binary system</p> <p> </p> <p><strong>## run_extras</strong></p> <p>- <strong>run_star_extras.f</strong>: subroutines and functions for the individual stars</p> <p>- <strong>run_binary_extras.f</strong>: subroutines and functions for the binary system</p> <p> </p> <p><strong>## MESA_ZAMS_models</strong></p> <p>Precomputed ZAMS models read in through <strong>inlist1</strong> and <strong>inlist2</strong>.</p> <p> </p> <p><strong>## table_G1_full.txt</strong></p> <p>Full machine-readable version of Table G.1.<br> </p> <p><strong>## MESA_models_output</strong></p> <p>Detailed output of the MESAbinary calculations. <em>Will be added in due time.</em></p>
Stellar properties of observed stars stripped in binaries in the Magellanic Clouds - Observations and Results
<p>This Zenodo repository is one of three Zenodo repositories related to the article "Stellar properties of observed stars stripped in binaries in the Magellanic Clouds" by Y. Götberg, M.R. Drout, A.P. Ji, J.H. Groh, B.A. Ludwig, P.A. Crowther, N. Smith, A. de Koter, and S.E. de Mink. In the article, we analyze the optical spectra of ten stars and measure their stellar properties using spectral fitting. This repository contains observational data and the resulting measurements for the stellar properties of the stars analyzed in the article, along with best fit spectral models and spectral models used to estimate the wind mass loss rate of the stars. Below, we describe the content in more detail:</p> <ul> <li><strong>0_ReadMe.txt</strong>: A text file where we describe some more details regarding the content.</li> <li><strong>S2_stacked_stellar_spectra.tar.gz (4.6 MB):</strong> The spectra we use for obtaining stellar properties for the observed stars.</li> <li><strong>Table2.txt</strong>: the apparent AB magnitudes with associated errors for the stars we analyze in the paper.</li> <li><strong>Table3.txt</strong>: the stellar properties for the stars we analyze in the paper. These parameters are obtained by spectral fitting.</li> <li><strong>S5_spectra_best_fit_models.tar.gz (14 MB):</strong> The spectral energy distributions and normalized spectra for the best-fit models, recomputed such that the radius and bolometric luminosity also matches. This tarball contains best-fit spectra for all of the stars in text-files labeled with the format SED_StarX_xxx.txt (~70 MB when inflated). The stellar parameters are presented in Section 5.</li> <li><strong>S5_full_best_fit_models.tar.gz (1.9 GB):</strong> The full CMFGEN version of the best-fit models for each individual star. This tarball contains a tarball for each star, which when inflated becomes ~250-550 MB each. </li> <li><strong>S7_spectra_mdot_models (31 MB): </strong>The spectral energy distributions and normalized spectra for the models used in the mass-loss analysis that we present in Section 7.</li> <li><strong>S7_full_mdot_models (3.5 GB):</strong> The full CMFGEN version of the spectral models used for the mass-loss rate variation presented in section 7 (excluding the best-fit models, which are provided separately).</li> </ul>
A seven-Earth-radius helium-burning star inside a 20.5-min detached binary
<p><strong>2024-02-19 updated for including the full MESA inlists of evolutionary models.</strong></p> <p><strong>MESA_inlist.zip</strong> -<strong> </strong>the full MESA inlists of evolutionary models (including evolutions of single stars and binaries).</p> <p>_____________________________________________________________________________________________________________________</p> <p>This record contains the data of spectra, photometries and models used for the paper <em><strong>A seven-Earth-radius helium-burning star inside a 20.5-min detached binary</strong>,<a href="https://www.nature.com/articles/s41550-023-02188-2"> click here</a></em></p> <p><strong>J0526_fchart.png</strong> - the finder chart of J0526;</p> <p><strong>J0526_Keck_[0-5].spec </strong> (in Keck_ori_spectra.zip)<strong> </strong>- Keck I/LRIS spectra of J0526;</p> <p><strong>J0526_GTC_[0-6].spec </strong> (in GTC_ori_spectra.zip)<strong> </strong>- GTC/OSIRIS spectra of J0526;</p> <p><strong>J0526_GTC_syn_[0-6].spec </strong> (in GTC_spectra_models.zip)<strong> </strong>- GTC/OSIRIS spectra and their best-fit TLUSTY/Synspec spectra;</p> <p><strong>J0526_RV_bary_corrected.dat</strong> - the barycenter-corrected radial velocities derived from LRIS and OSIRIS spectra;</p> <p><strong>J0526_SED.dat</strong> - the photometric fluxes in the broad-band SED and corresponding synthetic fluxes from the best-fit model spectrum;</p> <p><strong>ZTF_J0526_[r,g].dat </strong>(in light_curves.zip) - ZTF <em>r</em>-/<em>g</em>-band light cuvrs of J0526, the raw data were provided by NASA/IPAC Infrared Science Archive (<a href="https://irsa.ipac.caltech.edu/">https://irsa.ipac.caltech.edu</a> );</p> <p><strong>Lijiang_J0526_[r,g].dat </strong>(in light_curves.zip) - LJT <em>r</em>-/<em>g</em>-band light cuvrs of J0526;</p> <p><strong>TMTS_J0526_L.dat </strong>(in light_curves.zip) - LJT <em>L</em>-band light cuvrs of J0526;</p> <p><strong>CHeB_c[0.32,0.33,0.34]+H1e-6.track</strong> (in MESA_models.zip) - the evolutionary tracks for core helium-burning stars with He-core mass of [0.32,0.33,0.34] M<sub>sun</sub> and H-envelope mass of 1e-6 M<sub>sun</sub>;</p> <p><strong>ZAHeMS_H0_sequence.dat</strong> (in MESA_models.zip) - the zero-age He-star sequence (without H envelope);</p> <p><strong>ZAHeMS_H1e-6_sequence.dat</strong> (in MESA_models.zip) - the zero-age He-star sequence (with H-envelope mass of 1e-6 M_sun );</p> <p><strong>binary_0.33+0.735.dat </strong> (in MESA_models.zip) - the binary evolutionary track for a core helium-burning star (M<sub>core</sub>=0.33 M_sun, M<sub>env</sub>=1e-6 M_sun ) and a CO WD (M=0.735 M_sun);</p> <p><strong>binary_0.36+0.735.dat </strong> (in MESA_models.zip) - the binary evolutionary track for a core helium-burning star (M<sub>core</sub>=0.36 M_sun, M<sub>env</sub>=1e-6 M_sun ) and a CO WD (M=0.735 M_sun);</p> <p><strong>J0526_[SED, RV, lc]_fit_corner.png</strong> - the corner plots for [SED, RV, light curve] MCMC fit.</p>
Resolving Pleiades Binary Stars with Gaia and Speckle Interferometric Observations
<p>These supplementary data accompany the paper "Resolving Pleiades Binary Stars with Gaia and Speckle Interferometric Observations", <a href="https://iopscience.iop.org/article/10.3847/1538-3881/ada564" target="_blank" rel="noopener">published by the Astronomical Journal</a>. Table data are also available through the <a href="https://vizier.cds.unistra.fr/viz-bin/VizieR?-source=J/AJ/169/145" target="_blank" rel="noopener">VizieR service</a>. <br><a href="https://ui.adsabs.harvard.edu/abs/2025AJ....169..145C/abstract" target="_blank" rel="noopener">ADS: 2025AJ....169..145C</a>, <a href="https://arxiv.org/abs/2412.20986" target="_blank" rel="noopener">arXiv: 2412.20986</a></p> <p>Observations were obtained with the Speckle Polarimeter (SPP) instrument of the 2.5-m telescope of the Caucasian Observatory of the SAI MSU.</p> <p>Full versions of Table 5 and Table 6, containing binarity information and detection limits, are stored in "table5.mrt" and "table6.mrt". Contrast curves and autocorrelation functions for all observed objects are stored in "acfs/" folder inside "SPP_contrastCurves_ACFs_Pleiades.zip". These plots can be accessed directly with filename search by Gaia DR3 source identifier. The csv-table "contrastCurves_ACFs_filenames_info.csv" contains additional information about observations - date of observation, passband, seeing, comments etc. We provide a small Jupyter notebook script "display_contrastCurves_ACFs.ipynb" to display available observations along with fragments of Table 5 and Table 6 for specified object.</p>
BHBH simulations from: Impact of Massive Binary Star and Cosmic Evolution on Gravitational Wave Observations II: Double Compact Object Mergers
<p>The data for all <strong>BHBH </strong>simulations shown in<em><strong> "Impact of Massive Binary Star and Cosmic Evolution on Gravitational Wave Observations II: Double Compact Object Mergers". </strong>Broekgaarden et al. (2021, submitted, preprint: <a href="https://arxiv.org/abs/2112.05763">https://arxiv.org/abs/2112.05763</a>)</em></p> <p> </p> <p><strong>Contents: </strong></p> <ul> <li><strong>18 zip files that each contain an hdf5 file with the raw data for one of the simulations from Table 1 in the paper. The only exception is the fiducial.zip file and the unstableCaseBB.zip file, which contain both the fiducial (model A) and 'optimistic CE' (model K) data file and the "unstable case BB" (model E) and "unstable case BB + optimistic CE" (model F) files.</strong><br> <strong>These zip files are: </strong> <ul> <li><em>fiducial.zip, </em> the Fiducial model (A) and Optimistic CE model (K)</li> <li><em>massTransferEfficiencyFixed_0_25.zip, </em>the <span class="math-tex">\(\beta\)</span> = 0.25 model (B) </li> <li><em>massTransferEfficiencyFixed_0_5.zip</em>, the <span class="math-tex">\(\beta\)</span> = 0.5 model (C) </li> <li><em>massTransferEfficiencyFixed_0_75.zip,</em> the <span class="math-tex">\(\beta\)</span> = 0.75 model (D)</li> <li><em>unstableCaseBB.zip, </em>the unstable case BB mass transfer model (E) and unstable case BB & optimistic CE model (F) </li> <li><em>alpha0_1 zip</em>, the <span class="math-tex">\(\alpha = 0.1\)</span> model (G) </li> <li><em>alpha0_5.zip</em>, the <span class="math-tex">\(\alpha = 0.5\)</span> model (H) </li> <li><em>alpha2_0.zip</em>, the <span class="math-tex">\(\alpha = 2.0\)</span> model (I) </li> <li><em>alpha10_0.zip</em>, the <span class="math-tex">\(\alpha = 10.0\)</span> model (J) </li> <li><em>rapid.zip</em>, the rapid SN model (L) </li> <li><em>maxNSmass2_0.zip, </em>the max <span class="math-tex">\(m_{\rm{NS}} = 2\, \rm{M}_{\odot}\)</span> model (M) </li> <li><em>maxNSmass3_0.zip, </em>the max <span class="math-tex">\(m_{\rm{NS}} = 3\, \rm{M}_{\odot}\)</span> model (N)</li> <li><em>noPISN.zip</em>, the no PISN model (O) </li> <li><em>ccSNkick_100km_s.zip, </em>the <span class="math-tex">\(\sigma_{\rm{cc}}\)</span>= 100 km/s model (P) </li> <li><em>ccSNkick_30km_s.zip, </em>the <span class="math-tex">\(\sigma_{\rm{cc}}\)</span>= 30 km/s model (Q)</li> <li> <em>noBHkick.zip, </em>the no BH SN kick model (R)</li> <li><em>wolf_rayet_multiplier_0_1.zip, </em>the model with Wolf-Rayet wind factor <span class="math-tex">\(f_{\rm{WR}} = 0.1\)</span> (S)</li> <li><em>wolf_rayet_multiplier_5.zip, </em>the model with Wolf-Rayet wind factor <span class="math-tex">\(f_{\rm{WR}} = 5\)</span> (T)<br> <br> </li> </ul> </li> <li>2 more zip files containing csv files with the summarized rates to create Figures 1, 2 and 3, which do not require downloading the entire dataset, but instead use these csv files with the summarized rates: <ul> <li><strong>csvFilesForFigure1_DCOpaper.zip </strong># contains the files to recreate figure 1 with the merger rates per metallicity for BH-BH, BH-NS and NS-NS: <ul> <li>formationRatesTotalAndPerChannel_BHBH_.csv</li> <li>formationRatesTotalAndPerChannel_BHNS_.csv</li> <li>formationRatesTotalAndPerChannel_NSNS_.csv</li> </ul> </li> <li><strong>csvFilesForFigure2_and_3_DCOpaper.zip </strong># contains the files to recreate figure 2 with the merger rates for intrinsic and GW detection weighted, containing the csv files with names: <ul> <li>rates_MSSFR_Models_BHBH_AllDCOsimulation.csv</li> <li>rates_MSSFR_Models_NSNS_AllDCOsimulation.csv</li> <li>rates_MSSFR_Models_BHNS_AllDCOsimulation.csv</li> </ul> </li> </ul> </li> </ul> <p> </p> <p>Details of how to use the data (a readme), as well as scripts to reproduce all results, plots, and figures from the paper are given in the accompanying Github repository <a href="https://github.com/FloorBroekgaarden/Double-Compact-Object-Mergers">https://github.com/FloorBroekgaarden/Double-Compact-Object-Mergers</a> </p> <p>If you use this data, please cite </p> <p>Broekgaarden et al. (2021): see <a href="https://ui.adsabs.harvard.edu/abs/2021arXiv211205763B/abstract">https://ui.adsabs.harvard.edu/abs/2021arXiv211205763B/abstract</a></p>
NMMA: A nuclear-physics and multi-messenger astrophysics framework to analyze binary neutron star mergers
<p>Data release associated with the preprint "<em>NMMA: A nuclear-physics and multi-messenger astrophysics framework to analyze binary neutron star mergers</em>"</p> <p>Data includes:</p> <p>EOS files:</p> <ul> <li>5000 eos files with radius (km), mass (Msun), and tidal deformability as columns stored under eos/eos_data</li> <li>prior probabilities for the EOSs are stored in eos/eos_prior_probability.dat</li> </ul> <p>Posterior samples:</p> <ul> <li>Posterior samples based on the analysis of GW170817 and AT2017gfo stored in posterior_samples/GW170817-AT2017gfo_posterior_samples.dat</li> <li>Posterior samples based on the analysis of GW170817, AT2017gfo, and the afterglow of GRB170817A are stored in posterior_samples/GW170817-AT2017gfo-GRB170817A_afterglow_posterior_samples.dat</li> </ul> <p> </p>
Dataset from: Multi-messenger observations of binary neutron star mergers in the O4 run
<p>The binary neutron stars population data from the paper <strong><em>"Multi-messenger observations of binary neutron star mergers in the O4 run" </em>(<a href="https://arxiv.org/abs/2204.07592">https://arxiv.org/abs/2204.07592</a>).</strong></p> <p>Details of how to use the data, as well as the scripts to reproduce the figures of the main text of the paper are given in the accompanying Github repository <a href="https://github.com/acolombo140/O4NSNS">https://github.com/acolombo140/O4NSNS</a></p> <p>If you use this data, please cite the above manuscript.</p> <p> </p>
Black-hole neutron-star binary simulation SXS:BHNS:0001
<p>Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.</p>
Black-hole neutron-star binary simulation SXS:BHNS:0003
<p>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>.</p>
Black-hole neutron-star binary simulation SXS:BHNS:0002
<p>Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.</p>
Binary neutron-star simulation SXS:NSNS:0002
<p>Simulation of a neutron-star binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.</p>
Black-hole neutron-star binary simulation SXS:BHNS:0006
<p>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>.</p>
Black-hole neutron-star binary simulation SXS:BHNS:0004
<p>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>.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.