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7 results for “deep coalescence”
GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run - Data Quality Products for GW Searches
<p>This material is part of several data products associated with GWTC-2.1, the deep extended catalog of compact binary coalescences observed by the <a href="https://www.ligo.org/">LIGO</a> Scientific Collaboration and the <a href="https://www.virgo-gw.eu/">Virgo</a> Collaboration during the first half of the third observing run. For further information, see the paper (<a href="https://dcc.ligo.org/LIGO-P2100063/public">dcc.ligo.org/LIGO-P2100063/public</a>), the related material linked from this page, and the GWTC-2.1 data release documentation (<a href="https://www.gw-openscience.org/GWTC-2.1/">www.gw-openscience.org/GWTC-2.1/</a>).</p> <p>This release contains data quality products that are used by search analyses to help mitigate non-Gaussian noise in the detector data.</p> <p><strong>Renormalized iDQ timeseries</strong></p> <p>This release contains the renormalized iDQ timeseries data quality product used within the GstLAL search to generate results for GWTC-2.1 as described in <a href="https://arxiv.org/abs/2010.15282">Goodwin <em>et al</em>. 2020</a>. This data product was found to be statistically helpful in improving data quality within the GstLAL search. For further information about iDQ see <a href="https://iopscience.iop.org/article/10.1088/2632-2153/abab5f">Essick <em>et al</em>. 2020</a>.</p> <p>The file </p> <ul> <li>H1L1-IDQ_TIMESERIES-1238166018-15843600.h5</li> </ul> <p>contains a time series for each LIGO detector related to the probability of a glitch in the strain data given the behavior in the analyzed auxiliary channels which monitor the behavior of the detectors and their environment.</p> <p>The HDF5-formatted file contains two groups, H1 and L1, corresponding to LIGO Hanford and LIGO Livingston, respectively. Each group contains several datasets; the data dataset corresponds to the renormalized iDQ log-likelihoods, as described in Godwin <em>et al</em>. 2020, and the time dataset corresponds to the times associated with the renormalized iDQ log-likelihoods in the data dataset.</p> <p> </p> <p>For more general background on gravitational-wave data quality, try the materials from a <a href="https://www.gw-openscience.org/workshops/">GW Open Data Workshop</a> or the guide to <a href="https://doi.org/10.1088/1361-6382/ab685e">LIGO-Virgo data analysis</a>.</p>
GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run - Parameter Estimation Data Release
<p>This material is part of several data products associated with GWTC-2.1, an update to the second Gravitational-Wave Transient Catalog from the <a href="https://www.ligo.org/">LIGO</a> Scientific Collaboration, the <a href="https://www.virgo-gw.eu/">Virgo</a> Collaboration, and the <a href="https://gwcenter.icrr.u-tokyo.ac.jp/en/">KAGRA</a> Collaboration. For more information, see the paper (<a href="https://dcc.ligo.org/LIGO-P2100063/public">https://dcc.ligo.org/LIGO-P2100063/public</a>), the related material linked from this page, and the GWTC-2.1 data release documentation (<a href="https://www.gw-openscience.org/GWTC-2.1/">https://www.gw-openscience.org/GWTC-2.1/</a>).</p> <p><strong>Parameter estimation data release</strong></p> <p>This data release contains posterior samples (*.h5) for gravitational-wave candidates through the first part of the third observing run (O3a). We provide results for the 44 candidates that have a probability of astrophysical origin of over 0.5 from O3 as well as the 10 previously-reported binary-black-hole candidates from GWTC-1 (this excludes GW170817). There are two .h5 files per event</p> <ul> <li> <p>Cosmologically reweighted (*cosmo.h5)</p> </li> <li> <p>Not cosmologically reweighted (*nocosmo.h5)</p> </li> </ul> <p>The cosmologically reweighted posteriors are reweighted to have a luminosity-distance prior that has a uniform merger rate in the source's comoving frame. Each .h5 file contains samples for multiple runs with keys C01:RUN_NAME, where RUN_NAME is the waveform used for the run (and additional prior-choice information if necessary) or Mixed, indicating an equal mixture of samples from runs with similar physics if they exist. In cases where only one waveform was used, the Mixed dataset is simply a resampling of those results . GW190425 does not have Mixed samples. See the <a href="https://dcc.ligo.org/LIGO-P2100063/public">paper</a> appendices for further information. In addition to containing the posterior samples, the .h5 files also contain metadata about the analyses including the configuration files (which specify details such as the detector data analyzed), noise power spectral densities (potentially for a superset of the detectors used in the analysis) and calibration uncertainty envelopes.</p> <p>The python notebook explains how to use the posterior samples. This data release also contains .FITS skymap files, which can be read with <a href="https://lscsoft.docs.ligo.org/ligo.skymap/#">ligo.skymap</a>, and skymap statistics in *.txt files.</p> <p>The inference of the source parameters were performed with <a href="https://lscsoft.docs.ligo.org/bilby/">Bilby</a>, <a href="https://lscsoft.docs.ligo.org/parallel_bilby/">Parallel Bilby</a> and <a href="https://git.ligo.org/richard-oshaughnessy/research-projects-RIT/tree/temp-RIT-Tides">RIFT</a>. The results are formatted using <a href="https://lscsoft.docs.ligo.org/pesummary/">PESummary</a>.</p> <p><a href="https://zenodo.org/record/5546663#.YnAAcvPMKqC">A similar release has been made to accompany GWTC-3</a> for results from the second part of the third observing run.</p> <p><strong>How to download all files from this page</strong></p> <p>If you would like to download all files on this page, we recommend <a href="https://gitlab.com/dvolgyes/zenodo_get">zenodo_get</a>:</p> <pre><code class="language-bash">pip install zenodo_get zenodo-get RECORD_ID_OR_DOI </code></pre> <p>where the record ID for the most recent version of this page is 5117702 and IDs for other versions can be found in the Versions section at the side of this page.</p> <p>For more general background on gravitational-wave parameter estimation, try the materials from a <a href="https://www.gw-openscience.org/workshops/">GW Open Data Workshop</a> or the <a href="https://doi.org/10.1088/1361-6382/ab685e">guide to LIGO–Virgo data analysis</a>.</p>
GWTC-2.1: Deep extended-catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run - Sensitivity of search pipelines to simulated signals
<p>Results of search pipelines (GSTLAL, MBTA, PYCBC, PYCBC BBH) used to identify candidates in <a href="https://dcc.ligo.org/LIGO-P2100063/public">GWTC-2.1</a> on a set of simulated signals corresponding to binary neutron star (BNS), neutron star black holes (NSBH), and binary black holes (BBH) signals. Additionally, we include a README file which provides information on how to read these files.</p>
GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run - Candidate Data Release
<p>Data associated with candidates in <a href="https://dcc.ligo.org/LIGO-P2100063/public">GWTC-2.1</a>. These are gravitational-wave candidates from the first half of the third observing run (O3a) of the Advanced LIGO and Virgo detectors that pass a false alarm rate threshold of 2/day. We upload a tar file (search_data_GWTC2p1.tar.gz) containing all the data and a python notebook (search_data.ipynb) which provides description on how to use the files contained in the dataset.</p>
GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run - Glitch modelling for events
<p>This material is part of several data products associated with GWTC-2.1, the deep extended catalog of compact binary coalescences observed by the <a href="https://www.ligo.org/">LIGO</a> Scientific Collaboration and the <a href="https://www.virgo-gw.eu/">Virgo</a> Collaboration during the first half of the third observing run. For further information, see the paper (<a href="https://dcc.ligo.org/LIGO-P2100063/public">dcc.ligo.org/LIGO-P2100063/public</a>), the related material linked from this page, and the GWTC-2.1 data release documentation (<a href="https://www.gw-openscience.org/GWTC-2.1/">www.gw-openscience.org/GWTC-2.1/</a>).</p> <p><strong>Glitch model for GWTC-2.1 events</strong></p> <p>Glitch model for events in the GWTC_2.1 catalog that used <a href="https://git.ligo.org/lscsoft/bayeswave">BayesWave</a> glitch subtraction. This includes LIGO Livingston Observatory (L1) data for the following events:</p> <ul> <li>GW190413_134308</li> <li>GW190425_081805</li> <li>GW190503_185404</li> <li>GW190513_205428</li> <li>GW190514_065416</li> <li>GW190701_203306</li> <li>GW190924_021846</li> </ul> <p>Each data file contains three channels:</p> <ol> <li>the calibrated strain data, including any glitches that are present,</li> <li>a model of the glitches, produced using the BayesWave algorithm,</li> <li>the calibrated data with the glitch model subtracted, used for parameter estimation</li> </ol> <p>For the L1 data for all events, these channels have the following names and sample rates (in Hz):</p> <ol> <li>L1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01 16384</li> <li>L1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01_glitch 16384</li> <li>L1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01_T1700406_v4 16384</li> </ol> <p><strong>How to download all files from this page</strong></p> <p>If you would like to download all files on this page we recommend <a href="https://gitlab.com/dvolgyes/zenodo_get">zenodo_get</a>:</p> <pre><code class="language-bash">pip install zenodo_get zenodo-get RECORD_ID_OR_DOI</code></pre> <p>where the record ID for the most recent version of this page is 6477075 and IDs for other versions can be found in the Versions section at the side of this page.</p> <p> </p> <p>For more general background on gravitational-wave data quality, try the materials from a <a href="https://www.gw-openscience.org/workshops/">GW Open Data Workshop</a> or the guide to <a href="https://doi.org/10.1088/1361-6382/ab685e">LIGO-Virgo data analysis</a>.</p>
Data for: Phylogenomic and population genomic analyses of ultraconserved elements reveal deep coalescence and introgression shaped diversification patterns in Lamprologine cichlids of the Congo River
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Test sets and results for paper 'Rapid localization of gravitational wave sources from compact binary coalescences using deep learning'
<p>This folder contains the input data (signal-to-noise ratio time series for gravitational wave detections) and results (sky localization areas) obtained from the deep learning based sky localization model 'GW-SkyLocator', and the rapid online gravitational wave sky localization tool 'BAYESTAR' on a set of injections of gravitational wave signals from compact binary mergers.</p> <p>For details of the work, please refer to the paper, 'Rapid localization of gravitational wave sources from compact binary coalescences using deep learning' (https://arxiv.org/abs/2207.14522).</p>
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