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6 results for “Compact binary mergers”

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zenodo40/100

BHBH simulations from: Impact of Massive Binary Star and Cosmic Evolution on Gravitational Wave Observations II: Double Compact Object Mergers

The data for all BHBH simulations shown in "Impact of Massive Binary Star and Cosmic Evolution on Gravitational Wave Observations II: Double Compact Object Mergers".  Broekgaarden et al. (2021, submitted, preprint: <a href="https://arxiv.org/abs/2112.05763">https://arxiv.org/abs/2112.05763</a>)   Contents:  <ul> <li>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. These zip files are:  <ul> <li>fiducial.zip,  the Fiducial model (A) and Optimistic CE model (K)</li> <li>massTransferEfficiencyFixed_0_25.zip, the \(\beta\) = 0.25 model (B) </li> <li>massTransferEfficiencyFixed_0_5.zip, the \(\beta\) = 0.5 model (C) </li> <li>massTransferEfficiencyFixed_0_75.zip, the \(\beta\) = 0.75 model (D)</li> <li>unstableCaseBB.zip, the unstable case BB mass transfer model (E) and unstable case BB & optimistic CE model (F) </li> <li>alpha0_1 zip, the \(\alpha = 0.1\) model (G) </li> <li>alpha0_5.zip, the \(\alpha = 0.5\) model (H) </li> <li>alpha2_0.zip, the \(\alpha = 2.0\) model (I) </li> <li>alpha10_0.zip, the \(\alpha = 10.0\) model (J) </li> <li>rapid.zip, the rapid SN model (L) </li> <li>maxNSmass2_0.zip, the max \(m_{\rm{NS}} = 2\, \rm{M}_{\odot}\) model (M) </li> <li>maxNSmass3_0.zip, the max \(m_{\rm{NS}} = 3\, \rm{M}_{\odot}\) model (N)</li> <li>noPISN.zip, the no PISN model (O) </li> <li>ccSNkick_100km_s.zip, the \(\sigma_{\rm{cc}}\)= 100 km/s model (P) </li> <li>ccSNkick_30km_s.zip, the \(\sigma_{\rm{cc}}\)= 30 km/s model (Q)</li> <li> noBHkick.zip, the no BH SN kick model (R)</li> <li>wolf_rayet_multiplier_0_1.zip, the model with Wolf-Rayet wind factor \(f_{\rm{WR}} = 0.1\) (S)</li> <li>wolf_rayet_multiplier_5.zip, the model with Wolf-Rayet wind factor \(f_{\rm{WR}} = 5\) (T)  </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>csvFilesForFigure1_DCOpaper.zip # 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>csvFilesForFigure2_and_3_DCOpaper.zip # 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>   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>  If you use this data, please cite  Broekgaarden et al. (2021): see <a href="https://ui.adsabs.harvard.edu/abs/2021arXiv211205763B/abstract">https://ui.adsabs.harvard.edu/abs/2021arXiv211205763B/abstract</a>

opencc-by-4.0Nov 2021View details →

zenodo40/100

NSNS simulations from: Impact of Massive Binary Star and Cosmic Evolution on Gravitational Wave Observations II: Double Compact Object Mergers

The data for all NSNS simulations shown in "Impact of Massive Binary Star and Cosmic Evolution on Gravitational Wave Observations II: Double Compact Object Mergers".  Broekgaarden et al. (2021, submitted, preprint: <a href="https://arxiv.org/abs/2112.05763">https://arxiv.org/abs/2112.05763</a>)   Contents:  <ul> <li>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. These zip files are:  <ul> <li>fiducial.zip,  the Fiducial model (A) and Optimistic CE model (K)</li> <li>massTransferEfficiencyFixed_0_25.zip, the \(\beta\) = 0.25 model (B) </li> <li>massTransferEfficiencyFixed_0_5.zip, the \(\beta\) = 0.5 model (C) </li> <li>massTransferEfficiencyFixed_0_75.zip, the \(\beta\) = 0.75 model (D)</li> <li>unstableCaseBB.zip, the unstable case BB mass transfer model (E) and unstable case BB & optimistic CE model (F) </li> <li>alpha0_1 zip, the \(\alpha = 0.1\) model (G) </li> <li>alpha0_5.zip, the \(\alpha = 0.5\) model (H) </li> <li>alpha2_0.zip, the \(\alpha = 2.0\) model (I) </li> <li>alpha10_0.zip, the \(\alpha = 10.0\) model (J) </li> <li>rapid.zip, the rapid SN model (L) </li> <li>maxNSmass2_0.zip, the max \(m_{\rm{NS}} = 2\, \rm{M}_{\odot}\) model (M) </li> <li>maxNSmass3_0.zip, the max \(m_{\rm{NS}} = 3\, \rm{M}_{\odot}\) model (N)</li> <li>noPISN.zip, the no PISN model (O) </li> <li>ccSNkick_100km_s.zip, the \(\sigma_{\rm{cc}}\)= 100 km/s model (P) </li> <li>ccSNkick_30km_s.zip, the \(\sigma_{\rm{cc}}\)= 30 km/s model (Q)</li> <li> noBHkick.zip, the no BH SN kick model (R)</li> <li>wolf_rayet_multiplier_0_1.zip, the model with Wolf-Rayet wind factor \(f_{\rm{WR}} = 0.1\) (S)</li> <li>wolf_rayet_multiplier_5.zip, the model with Wolf-Rayet wind factor \(f_{\rm{WR}} = 5\) (T)  </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>csvFilesForFigure1_DCOpaper.zip # 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>csvFilesForFigure2_and_3_DCOpaper.zip # 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>   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>  If you use this data, please cite  Broekgaarden et al. (2021): see <a href="https://ui.adsabs.harvard.edu/abs/2021arXiv211205763B/abstract">https://ui.adsabs.harvard.edu/abs/2021arXiv211205763B/abstract</a>

opencc-by-4.0Aug 2021View details →

zenodo40/100

BHNS simulations from: Impact of Massive Binary Star and Cosmic Evolution on Gravitational Wave Observations II: Double Compact Object Mergers

The data for all BHNS simulations shown in "Impact of Massive Binary Star and Cosmic Evolution on Gravitational Wave Observations II: Double Compact Object Mergers".  Broekgaarden et al. (2021, submitted, preprint: <a href="https://arxiv.org/abs/2112.05763">https://arxiv.org/abs/2112.05763</a>)   Contents:  <ul> <li>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. These zip files are:  <ul> <li>fiducial.zip,  the Fiducial model (A) and Optimistic CE model (K)</li> <li>massTransferEfficiencyFixed_0_25.zip, the \(\beta\) = 0.25 model (B) </li> <li>massTransferEfficiencyFixed_0_5.zip, the \(\beta\) = 0.5 model (C) </li> <li>massTransferEfficiencyFixed_0_75.zip, the \(\beta\) = 0.75 model (D)</li> <li>unstableCaseBB.zip, the unstable case BB mass transfer model (E) and unstable case BB & optimistic CE model (F) </li> <li>alpha0_1 zip, the \(\alpha = 0.1\) model (G) </li> <li>alpha0_5.zip, the \(\alpha = 0.5\) model (H) </li> <li>alpha2_0.zip, the \(\alpha = 2.0\) model (I) </li> <li>alpha10_0.zip, the \(\alpha = 10.0\) model (J) </li> <li>rapid.zip, the rapid SN model (L) </li> <li>maxNSmass2_0.zip, the max \(m_{\rm{NS}} = 2\, \rm{M}_{\odot}\) model (M) </li> <li>maxNSmass3_0.zip, the max \(m_{\rm{NS}} = 3\, \rm{M}_{\odot}\) model (N)</li> <li>noPISN.zip, the no PISN model (O) </li> <li>ccSNkick_100km_s.zip, the \(\sigma_{\rm{cc}}\)= 100 km/s model (P) </li> <li>ccSNkick_30km_s.zip, the \(\sigma_{\rm{cc}}\)= 30 km/s model (Q)</li> <li> noBHkick.zip, the no BH SN kick model (R)</li> <li>wolf_rayet_multiplier_0_1.zip, the model with Wolf-Rayet wind factor \(f_{\rm{WR}} = 0.1\) (S)</li> <li>wolf_rayet_multiplier_5.zip, the model with Wolf-Rayet wind factor \(f_{\rm{WR}} = 5\) (T)  </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>csvFilesForFigure1_DCOpaper.zip # 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>csvFilesForFigure2_and_3_DCOpaper.zip # 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>   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>  If you use this data, please cite  Broekgaarden et al. (2021): see <a href="https://ui.adsabs.harvard.edu/abs/2021arXiv211205763B/abstract">https://ui.adsabs.harvard.edu/abs/2021arXiv211205763B/abstract</a>

opencc-by-4.0Aug 2021View details →

zenodo40/100

Daset from the paper "Compact object mergers: exploring uncertainties from stellar and binary evolution with SEVN"

This repository contains the dataset produced by the population-synthesis code SEVN   for the paper: "Compact object mergers: exploring uncertainties from stellar and binary evolution with SEVN" In this paper, we exploit the SEVN code (publicly available at <a href="https://gitlab.com/sevncodes/sevn">https://gitlab.com/sevncodes/sevn</a>) to analyse the formation and properties of binary compact objects. The repository also includes the initial condistions used as input and the SEVN version used to run the simulations. #Content The repository contains the following folders: - data_from_simulations: the folder contains all the data produced by the simulations and used in the Iorio+22 paper - InitialConditions: the folder contains all the intial conditions (and the code to generate them) that have been used for the Iorio+22 paper - SEVN_iorio22: this folder contains the version of the SEVN code that has been used to run the simulations in the Iorio+22 paper Each folder contains a specific README with additional information   #Contatcts giuliano.iorio.astro@gmail.com

opencc-by-4.0Oct 2022View details →

zenodo36/100

gwastro/1-ogc: v1.0 of the 1-OGC Catalog of Compact Binary Merger Candidates

Introduction This repository contains the first Open Gravitational-wave Catalog (1-OGW), which is obtained by using the public data from Advanced LIGO's first observing run to search for compact-object binary mergers. Our analysis is based on new methods that improve the separation between signals and noise in matched-filter searches for gravitational waves from the merger of compact objects. We make available our complete catalog of events, including the sub-threshold population of candidates. The catalog contains approximately 150,000 candidate events. We note that since the vast majority of the events in the catalog are likely to be noise, we have provided information to rank and select candidate events. The three most significant signals in our catalog correspond to the binary black hole mergers <a href="https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.116.061102">GW150914</a>, <a href="https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.116.241103">GW151226</a>, and <a href="https://journals.aps.org/prd/abstract/10.1103/PhysRevD.93.122003">LVT151012</a>, respectively. We observe these signals at a true discovery rate of 99.92%. We find that LVT151012 alone has a 97.6% probability of being astrophysical in origin. No other significant binary black hole candidates are found, nor did we observe any significant binary neutron star or neutron star--black hole candidates. The catalog is stored in the file '1-OGC.hdf'. There are a variety of tools to access <a href="https://www.hdfgroup.org/">hdf files</a> from numerous computing languages. Here we will focus on access through python and <a href="www.h5py.org">h5py</a>. Analysis Details Details of the analysis are available in this <a href="https://arxiv.org/abs/1811.01921">preprint paper</a> and the configuration files needed to create the analysis workflows are provided in the <a href="https://github.com/gwastro/1-ogc/tree/master/workflow/configuration">workflow/configuration</a> directory.

openother-openNov 2018View details →

zenodo32/100

Population synthesis data of massive binaries: NS/BH-core mergers and double compact objects formation and mergers

Binary population synthesis data generated using the rapid population synthesis code COMPAS. Contains: 1. Full COMPAS output in (.csv format) for running massive binaries varying the common envelope efficiency parameter and the metallicity. 2. Identifying seeds of systems that result in neutron star (NS)/black hole (BH)-core mergers, binary NSs, binary BHs and NS-BH binaries.

opencc-by-4.0May 2024View details →

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