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Data release for paper "Waveform systematics in identifying gravitationally lensed gravitational waves: Posterior overlap method"

<p>This is the data release for the paper &quot;Waveform systematics in identifying gravitationally lensed gravitational waves: Posterior overlap method&quot;, which is available on https://arxiv.org/abs/2306.12908.</p> <p>These results are derived from the gravitational-wave parameter-estimation results by the LIGO-Virgo-KAGRA Collaboration, released with the GWTC-1, GWTC-2, GWTC-2.1, and GWTC-3 catalogs under the following links:</p> <ul> <li>&nbsp; &nbsp; https://dcc.ligo.org/P1800370-v5/public</li> <li>&nbsp; &nbsp; https://dcc.ligo.org/P2000223-v7/public</li> <li>&nbsp; &nbsp; https://doi.org/10.5281/zenodo.6513631</li> <li>&nbsp; &nbsp; https://doi.org/10.5281/zenodo.5546663</li> </ul> <p>For the lensed-unlensed hypothesis test posterior overlap Bayes factors, we provide the following files for event pairs from within each observing run:</p> <ul> <li>&nbsp; &nbsp; blu_all_pairs_O1.txt</li> <li>&nbsp; &nbsp; blu_all_pairs_O2.txt</li> <li>&nbsp; &nbsp; blu_all_pairs_O3.txt</li> </ul> <p>In each file, the column &quot;event_pair&quot; contains the names of the two events from the pair sorted chronologically, the column &quot;data_releases&quot; contains the names of the data releases from which the posterior samples of each event were taken, the column &quot;waveform&quot; contains the name of the waveform model used in the parameter estimation for both sets of posteriors, and the column &quot;log10blu&quot; contains the log10 of the Bayes factors.</p> <p>The differences between runs for the same event pair, only including O1-O1, O2-O2, O3-O3 pairs, where at least one run gave log10blu&gt;0, are also given in the file &quot;blu_differences_pairs_with_log10blu_pos.txt&quot;. The column &quot;event_pair&quot; contains the event pairs, the columns &quot;waveform_{1,2}&quot; contain the names of the waveform models used in the parameter estimation for both sets of posteriors, the columns &quot;data_releases_{1,2}&quot; contain the the data releases from which the posterior samples of each event were taken, the columns &quot;log10blu_{1,2}&quot; contain the log10 Bayes factors, and the column &quot;difference&quot; contains the difference between &quot;log10blu_1&quot; and &quot;log10blu_2&quot;.</p> <p>We also provide the following files corresponding to the appendix of the paper, analyzing overlaps between posterior samples for individual events:</p> <ul> <li>&nbsp; &nbsp; overlap_different_runs.txt</li> <li>&nbsp; &nbsp; overlap_same_run.txt</li> <li>&nbsp; &nbsp; rescaled_difference_single_event.txt</li> </ul> <p>The file &quot;overlap_different_runs.txt&quot; contains Bayes factors for a single event, but comparing the posteriors from different runs. The file &quot;overlap_same_run.txt&quot; contains Bayes factors for the overlap of a single run on a single event with itself. The file &quot;rescaled_difference_single_event.txt&quot; contains the difference between the results contained in the file overlap_different_runs.txt and the results in overlap_same_run.txt, taking the ones that produce the biggest difference, as per equation (A.1) in the paper.</p> <p>In these files, the column &quot;event_name&quot; is the name of the event, the column &quot;data_release&quot; or &quot;data_releases&quot; contains the name(s) of the data release(s) from which the posterior samples of each run were taken, the column &quot;waveform&quot; or &quot;waveform_pair&quot; contains the name(s) of the waveform model(s) used, and the column &quot;log10blu&quot; is the log10 Bayes factor obtained. In the file &quot;rescaled_difference_single_event.txt&quot;, the columns &quot;max_run_waveform&quot; and &quot;max_run_data_release&quot; identify an entry from the &quot;overlap_same_run.txt&quot; file from which we use the &quot;log10blu&quot; to compute the value listed in the &quot;difference&quot; column using equation (A.1).<br> &nbsp;</p>

ShareScore

44/100

Overall dataset sharing score

Score breakdown

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

Stewardship
8
Harmonization
4
Access
20
Reuse readiness
8
Engagement
4

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