| _version_ | 1866902183528628224 |
|---|---|
| author | Phukon, Khun Sang Schmidt, Patricia Morrás, Gonzalo Pratten, Geraint |
| author_facet | Phukon, Khun Sang Schmidt, Patricia Morrás, Gonzalo Pratten, Geraint |
| contents | <p>Data behind the figures in Phukon et al., arxiv:2512.10803, and the scripts to generate them. </p> <p>Figure 1:</p> <ul> <li>Data files: <code>Eccentric_template_bank_GW200105_search.hdf</code>, <code>Quasicircular_template_bank_GW200105_search.hdf</code> </li> <li>Description of files: The file <code>Eccentric_template_bank_GW200105_search.hdf</code> contains the parameters of the template bank used in the eccentric search. The waveforms of templates are modeled by the TaylorF2Ecc approximant. The datasets with keys <code>mass1</code>, <code>mass2</code>, <code>spin1z</code>, <code>spin2z,</code> and <code>eccentricity</code> provide parameter values for the masses, spins of the components of non-precessing templates, and eccentricity, respectively. Existing datasets in the quasicircular template bank in <code>Quasicircular_template_bank_GW200105_search.hdf</code> hold the same meaning as in the eccentric bank.</li> <li>Plotting script, <code>fig1.py</code>: Figure 1 is made using the eccentric template bank, best-fit eccentric template parameters with GW200105 provided in Table II of Phukon et al., arxiv:2512.10803, and the median values of posteriors for GW200105 from Morras et al., arxiv:2503.15393.</li> </ul> <p>Figures 2 and 3: </p> <ul> <li>Data files: <p><code>H1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_ECCENTRIC_SEARCH.hdf</code>, <code>L1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1V1-EXCLUDE_ZEROLAG_FULL_DATA_3DET_ECCENTRIC_SEARCH.hdf</code>, <code>H1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1L1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>L1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1L1V1-EXCLUDE_ZEROLAG_FULL_DATA_3DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1_triggers_with_background_eccentric_search.hdf</code> (not provided here), <code>L1_triggers_with_background_eccentric_search.hdf</code> (not provided here), <code>V1_triggers_with_background_eccentric_search.hdf</code> (not provided here), <code>H1_triggers_with_background_quasicircular_search.hdf</code> (not provided here), <code>L1_triggers_with_background_quasicircular_search.hdf</code> (not provided here), <code>V1_triggers_with_background_quasicircular_search.hdf</code> (not provided here),<span class="Apple-converted-space"> </span><code>H1L1V1_INJ_FIND_ECCENTRIC_INJECTIONS_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1V1_INJ_FIND_ECCENTRIC_INJECTIONS_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1L1V1_INJ_FIND_QUASICIRCULAR_INJECTIONS_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1V1_INJ_FIND_QUASICIRCULAR_INJECTIONS_QUASICIRCULAR_SEARCH.hdf</code></p> </li> <li>Description of files: In files <code>DETECTOR_COMBINATION-EXCLUDE_ZEROLAG_FULL_DATA_#DET_SEARCH-TYPE.hdf</code>, clustered triggers used in background constructions for various detector combinations for searches are provided. Here <code>DETECTOR_COMBINATION</code> represents H1, L1, V1, H1L1, H1V1, L1V1, H1L1V1 with the corresponding number of detectors <code>#DET</code> in the file name string for respective searches <code>#DET_SEARCH-TYPE</code>. The files that contain summary statistics of eccentric and quasi-circular injection recovery in both searches are given by <code>H1L1V1_INJ_FIND_INJECTIONS-TYPE_SEARCH-TYPE.hdf</code>, where <code>INJECTIONS-TYPE</code> specifies either <code>ECCENTRIC_INJECTIONS</code> and <code>QUASICIRCULAR_INJECTIONS</code>, and <code>SEARCH-TYPE</code> is for <code>ECCENTRIC_SEARCH</code> and <code>QUASICIRCULAR_SEARCH.</code> The single detector trigger files with noise triggers, i.e. <code>DETECTOR_triggers_with_background_SEARCH-TYPE.hdf</code> are not provided in this repository as those exceed the size quota. In the filename string, <code>DETECTOR</code> and <code>SEARCH-TYPE</code> are dummies for H1, L1, V1, and eccentric_search, quasicircular search, respectively. </li> <li>Plotting scripts, <code>fig2.py</code> and <code>fig3.py</code>: The script fig2.py mainly compares chi-square and SNR values of noise triggers and eccentric injection triggers in both eccentric and quasi-circular searches. While fig3.py compares chi-square and SNR values of noise triggers and quasicircular injection triggers in both searches. </li> </ul> <p> Figure 4: </p> <ul> <li>Data files: <code>H1L1V1_INJ_FIND_ECCENTRIC_INJECTIONS_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1V1_INJ_FIND_ECCENTRIC_INJECTIONS_QUASICIRCULAR_SEARCH.hdf</code> </li> <li>Description of files: Each HDF file contains the parameters of the eccentric injections used in both searches, statistics associated with recovered injections, and information on missed injections. From each file, the relevant data group about found injections is <code>found_after_vetoes,</code> and about missed injections is <code>missed/after_vetoes</code>. All injection parameters used in this study are stored in the group <code>injections</code> .</li> <li>Plotting script, <code>fig4.py</code> : The sensitive volumes are computed using the pylal-based method with 200 bins at different IFAR thresholds. </li> </ul> <p>Figure 5: </p> <ul> <li>Data files: <p><code>H1L1V1-COMBINE_STATMAP_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1V1-COMBINE_STATMAP_QUASICIRCULAR_SEARCH.hdf</code>, <code>L1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_ECCENTRIC_SEARCH.hdf</code>, <code>H1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1V1-EXCLUDE_ZEROLAG_FULL_DATA_3DET_ECCENTRIC_SEARCH.hdf</code>, <code>V1-EXCLUDE_ZEROLAG_FULL_DATA_1DET_ECCENTRIC_SEARCH.hdf</code>, <code>L1-EXCLUDE_ZEROLAG_FULL_DATA_1DET_ECCENTRIC_SEARCH.hdf</code>, <code>H1-EXCLUDE_ZEROLAG_FULL_DATA_1DET_ECCENTRIC_SEARCH.hdf</code>, <code>L1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1L1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1L1V1-EXCLUDE_ZEROLAG_FULL_DATA_3DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>V1-EXCLUDE_ZEROLAG_FULL_DATA_1DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>L1-EXCLUDE_ZEROLAG_FULL_DATA_1DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1-EXCLUDE_ZEROLAG_FULL_DATA_1DET_QUASICIRCULAR_SEARCH.hdf</code></p> </li> <li>Description of files: Clusters foreground triggers with related statistics from quasi-circular and eccentric searches can be found in files <code>H1L1V1-COMBINE_STATMAP_QUASICIRCULAR_SEARCH.hdf</code> and <code>H1L1V1-COMBINE_STATMAP_ECCENTRIC_SEARCH.hdf</code>, respectively. Clustered triggers in background constructions for various detector combinations for searches are provided in files <code>DETECTOR_COMBINATION-EXCLUDE_ZEROLAG_FULL_DATA_#DET_SEARCH-TYPE.hdf</code>, where <code>DETECTOR_COMBINATION</code> represents H1, L1, V1, H1L1, H1V1, L1V1, H1L1V1 with the corresponding number of detectors <code>#DET</code> in the file name string for respective searches <code>#DET_SEARCH-TYPE</code>. </li> <li>Plotting script, <code>fig5.py</code>: Relevant dataset for foreground triggers from each search is <code>foreground/ifar_exc</code> that stores statistical information of triggers in the exclusive background of the respective search. The statmap files for background triggers are primarily used in the figure's right panel. The background statmap files are used to build the search significance/FAR. The script reads <code>background_exc/stat</code> to obtain ranking statistics for background events. For single-detector events, the <code>trigger_fit</code> method of PyCBC using an exponentially decaying function is used to evaluate statistical significance, event rate whereas for events in multiple detectors' observing time, the <code>n_louder </code>method is used to get event rate/significance at a given ranking statistics. </li> </ul> <p>Figure 6:</p> <ul> <li>Data files: <code>H1L1V1_INJ_FIND_ECCENTRIC_INJECTIONS_ECCENTRIC_SEARCH.hdf</code>, <code>Eccentric_template_bank_GW200105_search.hdf</code>,<code> H1-ECCENTRIC_INJECTION_TRIGGERS_ECCENTRIC_SEARCH.hdf</code>, <code>L1-ECCENTRIC_INJECTION_TRIGGERS_ECCENTRIC_SEARCH.hdf</code>, <code>V1-ECCENTRIC_INJECTION_TRIGGERS_ECCENTRIC_SEARCH.hdf</code></li> <li>Description of files: <code>H1L1V1_INJ_FIND_ECCENTRIC_INJECTIONS_ECCENTRIC_SEARCH.hdf</code> contains details of recovered (parameters, ranking statistics) and missed eccentric injections in the eccentric search with the eccentric bank stored in <code>Eccentric_template_bank_GW200105_search.hdf</code>. The single-detector triggers due to injections are stored in <code>DETECTOR-ECCENTRIC_INJECTION_TRIGGERS_ECCENTRIC_SEARCH.hdf</code>, where <code>DETECTOR</code> represents H1, L1, or V1. PyCBC's <code>SingleDetTriggers</code> module is used to establish a mapping between triggers and corresponding template parameters. </li> <li>Plotting script, <code>fig6.py</code>: This script results in a corner plot of the offsets of the injections and corresponding template parameters. </li> </ul> <p>Figure 7:</p> <ul> <li>Data files: <p><code>L1_triggers_eccentric_search.hdf</code>, <code>Eccentric_template_bank_GW200105_search.hdf</code>, <code>H1L1V1-COMBINE_STATMAP_ECCENTRIC_SEARCH.hdf</code></p> </li> <li>Description of files: The file <code>L1_triggers_eccentric_search.hdf</code> contains unclustered L1 detector triggers with noise triggers vetoed out. All clustered triggers found in all detector combinations are provided in <code>H1L1V1-COMBINE_STATMAP_ECCENTRIC_SEARCH.hdf</code>, while <code>Eccentric_template_bank_GW200105_search.hdf</code> is the template bank used in the search.</li> <li>Plotting script, <code>fig7.py</code>: The plotting extracts the index of the trigger reported against GW200105 from the file with clustered trigger information. Within a time window of 1 second around that trigger, all triggers are read from <code>L1_triggers_eccentric_search.hdf</code>. By mapping those triggers to the search template bank, the figure relating ranking statistics and template parameters for the corresponding triggers is produced.</li> </ul> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20119453 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Data release: Detection of GW200105 with a targeted eccentric search Phukon, Khun Sang Schmidt, Patricia Morrás, Gonzalo Pratten, Geraint <p>Data behind the figures in Phukon et al., arxiv:2512.10803, and the scripts to generate them. </p> <p>Figure 1:</p> <ul> <li>Data files: <code>Eccentric_template_bank_GW200105_search.hdf</code>, <code>Quasicircular_template_bank_GW200105_search.hdf</code> </li> <li>Description of files: The file <code>Eccentric_template_bank_GW200105_search.hdf</code> contains the parameters of the template bank used in the eccentric search. The waveforms of templates are modeled by the TaylorF2Ecc approximant. The datasets with keys <code>mass1</code>, <code>mass2</code>, <code>spin1z</code>, <code>spin2z,</code> and <code>eccentricity</code> provide parameter values for the masses, spins of the components of non-precessing templates, and eccentricity, respectively. Existing datasets in the quasicircular template bank in <code>Quasicircular_template_bank_GW200105_search.hdf</code> hold the same meaning as in the eccentric bank.</li> <li>Plotting script, <code>fig1.py</code>: Figure 1 is made using the eccentric template bank, best-fit eccentric template parameters with GW200105 provided in Table II of Phukon et al., arxiv:2512.10803, and the median values of posteriors for GW200105 from Morras et al., arxiv:2503.15393.</li> </ul> <p>Figures 2 and 3: </p> <ul> <li>Data files: <p><code>H1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_ECCENTRIC_SEARCH.hdf</code>, <code>L1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1V1-EXCLUDE_ZEROLAG_FULL_DATA_3DET_ECCENTRIC_SEARCH.hdf</code>, <code>H1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1L1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>L1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1L1V1-EXCLUDE_ZEROLAG_FULL_DATA_3DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1_triggers_with_background_eccentric_search.hdf</code> (not provided here), <code>L1_triggers_with_background_eccentric_search.hdf</code> (not provided here), <code>V1_triggers_with_background_eccentric_search.hdf</code> (not provided here), <code>H1_triggers_with_background_quasicircular_search.hdf</code> (not provided here), <code>L1_triggers_with_background_quasicircular_search.hdf</code> (not provided here), <code>V1_triggers_with_background_quasicircular_search.hdf</code> (not provided here),<span class="Apple-converted-space"> </span><code>H1L1V1_INJ_FIND_ECCENTRIC_INJECTIONS_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1V1_INJ_FIND_ECCENTRIC_INJECTIONS_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1L1V1_INJ_FIND_QUASICIRCULAR_INJECTIONS_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1V1_INJ_FIND_QUASICIRCULAR_INJECTIONS_QUASICIRCULAR_SEARCH.hdf</code></p> </li> <li>Description of files: In files <code>DETECTOR_COMBINATION-EXCLUDE_ZEROLAG_FULL_DATA_#DET_SEARCH-TYPE.hdf</code>, clustered triggers used in background constructions for various detector combinations for searches are provided. Here <code>DETECTOR_COMBINATION</code> represents H1, L1, V1, H1L1, H1V1, L1V1, H1L1V1 with the corresponding number of detectors <code>#DET</code> in the file name string for respective searches <code>#DET_SEARCH-TYPE</code>. The files that contain summary statistics of eccentric and quasi-circular injection recovery in both searches are given by <code>H1L1V1_INJ_FIND_INJECTIONS-TYPE_SEARCH-TYPE.hdf</code>, where <code>INJECTIONS-TYPE</code> specifies either <code>ECCENTRIC_INJECTIONS</code> and <code>QUASICIRCULAR_INJECTIONS</code>, and <code>SEARCH-TYPE</code> is for <code>ECCENTRIC_SEARCH</code> and <code>QUASICIRCULAR_SEARCH.</code> The single detector trigger files with noise triggers, i.e. <code>DETECTOR_triggers_with_background_SEARCH-TYPE.hdf</code> are not provided in this repository as those exceed the size quota. In the filename string, <code>DETECTOR</code> and <code>SEARCH-TYPE</code> are dummies for H1, L1, V1, and eccentric_search, quasicircular search, respectively. </li> <li>Plotting scripts, <code>fig2.py</code> and <code>fig3.py</code>: The script fig2.py mainly compares chi-square and SNR values of noise triggers and eccentric injection triggers in both eccentric and quasi-circular searches. While fig3.py compares chi-square and SNR values of noise triggers and quasicircular injection triggers in both searches. </li> </ul> <p> Figure 4: </p> <ul> <li>Data files: <code>H1L1V1_INJ_FIND_ECCENTRIC_INJECTIONS_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1V1_INJ_FIND_ECCENTRIC_INJECTIONS_QUASICIRCULAR_SEARCH.hdf</code> </li> <li>Description of files: Each HDF file contains the parameters of the eccentric injections used in both searches, statistics associated with recovered injections, and information on missed injections. From each file, the relevant data group about found injections is <code>found_after_vetoes,</code> and about missed injections is <code>missed/after_vetoes</code>. All injection parameters used in this study are stored in the group <code>injections</code> .</li> <li>Plotting script, <code>fig4.py</code> : The sensitive volumes are computed using the pylal-based method with 200 bins at different IFAR thresholds. </li> </ul> <p>Figure 5: </p> <ul> <li>Data files: <p><code>H1L1V1-COMBINE_STATMAP_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1V1-COMBINE_STATMAP_QUASICIRCULAR_SEARCH.hdf</code>, <code>L1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_ECCENTRIC_SEARCH.hdf</code>, <code>H1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_ECCENTRIC_SEARCH.hdf</code>, <code>H1L1V1-EXCLUDE_ZEROLAG_FULL_DATA_3DET_ECCENTRIC_SEARCH.hdf</code>, <code>V1-EXCLUDE_ZEROLAG_FULL_DATA_1DET_ECCENTRIC_SEARCH.hdf</code>, <code>L1-EXCLUDE_ZEROLAG_FULL_DATA_1DET_ECCENTRIC_SEARCH.hdf</code>, <code>H1-EXCLUDE_ZEROLAG_FULL_DATA_1DET_ECCENTRIC_SEARCH.hdf</code>, <code>L1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1V1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1L1-EXCLUDE_ZEROLAG_FULL_DATA_2DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1L1V1-EXCLUDE_ZEROLAG_FULL_DATA_3DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>V1-EXCLUDE_ZEROLAG_FULL_DATA_1DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>L1-EXCLUDE_ZEROLAG_FULL_DATA_1DET_QUASICIRCULAR_SEARCH.hdf</code>, <code>H1-EXCLUDE_ZEROLAG_FULL_DATA_1DET_QUASICIRCULAR_SEARCH.hdf</code></p> </li> <li>Description of files: Clusters foreground triggers with related statistics from quasi-circular and eccentric searches can be found in files <code>H1L1V1-COMBINE_STATMAP_QUASICIRCULAR_SEARCH.hdf</code> and <code>H1L1V1-COMBINE_STATMAP_ECCENTRIC_SEARCH.hdf</code>, respectively. Clustered triggers in background constructions for various detector combinations for searches are provided in files <code>DETECTOR_COMBINATION-EXCLUDE_ZEROLAG_FULL_DATA_#DET_SEARCH-TYPE.hdf</code>, where <code>DETECTOR_COMBINATION</code> represents H1, L1, V1, H1L1, H1V1, L1V1, H1L1V1 with the corresponding number of detectors <code>#DET</code> in the file name string for respective searches <code>#DET_SEARCH-TYPE</code>. </li> <li>Plotting script, <code>fig5.py</code>: Relevant dataset for foreground triggers from each search is <code>foreground/ifar_exc</code> that stores statistical information of triggers in the exclusive background of the respective search. The statmap files for background triggers are primarily used in the figure's right panel. The background statmap files are used to build the search significance/FAR. The script reads <code>background_exc/stat</code> to obtain ranking statistics for background events. For single-detector events, the <code>trigger_fit</code> method of PyCBC using an exponentially decaying function is used to evaluate statistical significance, event rate whereas for events in multiple detectors' observing time, the <code>n_louder </code>method is used to get event rate/significance at a given ranking statistics. </li> </ul> <p>Figure 6:</p> <ul> <li>Data files: <code>H1L1V1_INJ_FIND_ECCENTRIC_INJECTIONS_ECCENTRIC_SEARCH.hdf</code>, <code>Eccentric_template_bank_GW200105_search.hdf</code>,<code> H1-ECCENTRIC_INJECTION_TRIGGERS_ECCENTRIC_SEARCH.hdf</code>, <code>L1-ECCENTRIC_INJECTION_TRIGGERS_ECCENTRIC_SEARCH.hdf</code>, <code>V1-ECCENTRIC_INJECTION_TRIGGERS_ECCENTRIC_SEARCH.hdf</code></li> <li>Description of files: <code>H1L1V1_INJ_FIND_ECCENTRIC_INJECTIONS_ECCENTRIC_SEARCH.hdf</code> contains details of recovered (parameters, ranking statistics) and missed eccentric injections in the eccentric search with the eccentric bank stored in <code>Eccentric_template_bank_GW200105_search.hdf</code>. The single-detector triggers due to injections are stored in <code>DETECTOR-ECCENTRIC_INJECTION_TRIGGERS_ECCENTRIC_SEARCH.hdf</code>, where <code>DETECTOR</code> represents H1, L1, or V1. PyCBC's <code>SingleDetTriggers</code> module is used to establish a mapping between triggers and corresponding template parameters. </li> <li>Plotting script, <code>fig6.py</code>: This script results in a corner plot of the offsets of the injections and corresponding template parameters. </li> </ul> <p>Figure 7:</p> <ul> <li>Data files: <p><code>L1_triggers_eccentric_search.hdf</code>, <code>Eccentric_template_bank_GW200105_search.hdf</code>, <code>H1L1V1-COMBINE_STATMAP_ECCENTRIC_SEARCH.hdf</code></p> </li> <li>Description of files: The file <code>L1_triggers_eccentric_search.hdf</code> contains unclustered L1 detector triggers with noise triggers vetoed out. All clustered triggers found in all detector combinations are provided in <code>H1L1V1-COMBINE_STATMAP_ECCENTRIC_SEARCH.hdf</code>, while <code>Eccentric_template_bank_GW200105_search.hdf</code> is the template bank used in the search.</li> <li>Plotting script, <code>fig7.py</code>: The plotting extracts the index of the trigger reported against GW200105 from the file with clustered trigger information. Within a time window of 1 second around that trigger, all triggers are read from <code>L1_triggers_eccentric_search.hdf</code>. By mapping those triggers to the search template bank, the figure relating ranking statistics and template parameters for the corresponding triggers is produced.</li> </ul> |
| title | Data release: Detection of GW200105 with a targeted eccentric search |
| url | https://doi.org/10.5281/zenodo.20119453 |