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NSNS 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>NSNS&nbsp;</strong>simulations shown in<em><strong> &quot;Impact of Massive Binary Star and Cosmic Evolution on Gravitational Wave Observations II: Double Compact Object Mergers&quot;.&nbsp;&nbsp;</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>&nbsp;</p> <p><strong>Contents:&nbsp;</strong></p> <ul> <li><strong>18&nbsp;zip&nbsp;files that each contain an hdf5 file with the raw data for one of the simulations from Table 1&nbsp;in the paper. The only exception is the fiducial.zip file and the&nbsp;unstableCaseBB.zip file, which&nbsp;contain&nbsp;both the fiducial (model A) and &#39;optimistic CE&#39; (model K) data file and the &quot;unstable case BB&quot; (model E)&nbsp; and &quot;unstable case BB + optimistic CE&quot; (model F) files.</strong><br> <strong>These zip files are:&nbsp;</strong> <ul> <li><em>fiducial.zip,&nbsp;</em>&nbsp;the Fiducial model (A) and Optimistic CE model (K)</li> <li><em>massTransferEfficiencyFixed_0_25.zip,&nbsp;</em>the&nbsp;<span class="math-tex">\(\beta\)</span>&nbsp;= 0.25 model (B)&nbsp;</li> <li><em>massTransferEfficiencyFixed_0_5.zip</em>, the&nbsp;<span class="math-tex">\(\beta\)</span>&nbsp;= 0.5 model (C)&nbsp;</li> <li><em>massTransferEfficiencyFixed_0_75.zip,</em>&nbsp;the&nbsp;<span class="math-tex">\(\beta\)</span>&nbsp;= 0.75 model (D)</li> <li><em>unstableCaseBB.zip,&nbsp;</em>the unstable case BB mass transfer model (E) and unstable case BB &amp; optimistic CE model (F)&nbsp;</li> <li><em>alpha0_1 zip</em>, the&nbsp;<span class="math-tex">\(\alpha = 0.1\)</span>&nbsp;model (G)&nbsp;</li> <li><em>alpha0_5.zip</em>, the&nbsp;<span class="math-tex">\(\alpha = 0.5\)</span>&nbsp;model (H)&nbsp;</li> <li><em>alpha2_0.zip</em>, the&nbsp;<span class="math-tex">\(\alpha = 2.0\)</span>&nbsp;model (I)&nbsp;</li> <li><em>alpha10_0.zip</em>, the&nbsp;<span class="math-tex">\(\alpha = 10.0\)</span>&nbsp;model (J)&nbsp;</li> <li><em>rapid.zip</em>, the rapid SN model (L)&nbsp;</li> <li><em>maxNSmass2_0.zip,&nbsp;</em>the max&nbsp;<span class="math-tex">\(m_{\rm{NS}} = 2\, \rm{M}_{\odot}\)</span>&nbsp;model (M)&nbsp;</li> <li><em>maxNSmass3_0.zip,&nbsp;</em>the max&nbsp;<span class="math-tex">\(m_{\rm{NS}} = 3\, \rm{M}_{\odot}\)</span>&nbsp;model (N)</li> <li><em>noPISN.zip</em>, the no PISN model (O)&nbsp;</li> <li><em>ccSNkick_100km_s.zip,&nbsp;</em>the&nbsp;<span class="math-tex">\(\sigma_{\rm{cc}}\)</span>= 100 km/s model (P)&nbsp;</li> <li><em>ccSNkick_30km_s.zip,&nbsp;</em>the&nbsp;<span class="math-tex">\(\sigma_{\rm{cc}}\)</span>= 30 km/s model (Q)</li> <li>&nbsp;<em>noBHkick.zip,&nbsp;</em>the no BH SN kick model (R)</li> <li><em>wolf_rayet_multiplier_0_1.zip,&nbsp;</em>the model with Wolf-Rayet wind factor <span class="math-tex">\(f_{\rm{WR}} = 0.1\)</span>&nbsp;(S)</li> <li><em>wolf_rayet_multiplier_5.zip,&nbsp;</em>the model with Wolf-Rayet wind factor <span class="math-tex">\(f_{\rm{WR}} = 5\)</span>&nbsp;(T)<br> <br> &nbsp;</li> </ul> </li> <li>2 more&nbsp;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:&nbsp; <ul> <li><strong>csvFilesForFigure1_DCOpaper.zip&nbsp;</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&nbsp;</strong># contains the files to recreate figure 2 with the merger rates for intrinsic and GW detection weighted, containing the csv files with names:&nbsp; <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>&nbsp;</p> <p>Details of how to use the data (a readme),&nbsp; as well as scripts to reproduce all&nbsp;results, plots, and figures&nbsp;from the paper are given in the accompanying Github repository&nbsp;<a href="https://github.com/FloorBroekgaarden/Double-Compact-Object-Mergers">https://github.com/FloorBroekgaarden/Double-Compact-Object-Mergers</a>&nbsp;</p> <p>If you use this data, please cite&nbsp;</p> <p>Broekgaarden et al. (2021): see&nbsp;<a href="https://ui.adsabs.harvard.edu/abs/2021arXiv211205763B/abstract">https://ui.adsabs.harvard.edu/abs/2021arXiv211205763B/abstract</a></p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
4

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