Rapid data quality investigations of gravitational-wave events with the Data Quality Report Builder toolkit
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arXiv
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2026
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| author | Davis, Derek Yarbrough, Zach Areeda, Joseph Macas, Ronaldas Arnaud, Nicolas Helmling-Cornell, Adrian Doliva, Paolina Godwin, Olivia Yuzurihara, Hirotaka Mannix, Benjamin Alvarez-Lopez, Sofia Trevor, Max Huxford, Rachael Nguyen, Philippe Berger, Beverly Chatterjee, Chayan Di Renzo, Francesco Palomba, Christiano Sordini, Viola Pesios, Dimitrios Walker, Marissa Ahuja, Airene Chan, Man Leong Ding, Julian Frey, Raymond Herbst, Franz Lecoeuche, Yannick Liyanage, Annudesh McIver, Jess Ng, Raymond Perry, Sophie Rawcliffe, Caitlin Schofield, Robert |
| author_facet | Davis, Derek Yarbrough, Zach Areeda, Joseph Macas, Ronaldas Arnaud, Nicolas Helmling-Cornell, Adrian Doliva, Paolina Godwin, Olivia Yuzurihara, Hirotaka Mannix, Benjamin Alvarez-Lopez, Sofia Trevor, Max Huxford, Rachael Nguyen, Philippe Berger, Beverly Chatterjee, Chayan Di Renzo, Francesco Palomba, Christiano Sordini, Viola Pesios, Dimitrios Walker, Marissa Ahuja, Airene Chan, Man Leong Ding, Julian Frey, Raymond Herbst, Franz Lecoeuche, Yannick Liyanage, Annudesh McIver, Jess Ng, Raymond Perry, Sophie Rawcliffe, Caitlin Schofield, Robert |
| contents | We present the Data Quality Report Builder toolkit, DQRbuild, a suite of data quality tools that have been developed to vet gravitational-wave events in preparation for the fourth LIGO-Virgo-KAGRA observing run. We explain the main functionality and the many scientific tests that we support. To validate the performance of the tools included in the toolkit, we run a series of tests on all significant candidates shared as public alerts in the third observing run to compare against what was manually reported using human intervention. We find that these automated tools can now identify 96% of the problems identified by humans during this previous observing run, with a 24% false alarm rate. We conclude with a commentary on the prospects and potential challenges for fully automating the process of vetting the data quality for gravitational-wave events identified in future observing runs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_16183 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Rapid data quality investigations of gravitational-wave events with the Data Quality Report Builder toolkit Davis, Derek Yarbrough, Zach Areeda, Joseph Macas, Ronaldas Arnaud, Nicolas Helmling-Cornell, Adrian Doliva, Paolina Godwin, Olivia Yuzurihara, Hirotaka Mannix, Benjamin Alvarez-Lopez, Sofia Trevor, Max Huxford, Rachael Nguyen, Philippe Berger, Beverly Chatterjee, Chayan Di Renzo, Francesco Palomba, Christiano Sordini, Viola Pesios, Dimitrios Walker, Marissa Ahuja, Airene Chan, Man Leong Ding, Julian Frey, Raymond Herbst, Franz Lecoeuche, Yannick Liyanage, Annudesh McIver, Jess Ng, Raymond Perry, Sophie Rawcliffe, Caitlin Schofield, Robert Instrumentation and Methods for Astrophysics General Relativity and Quantum Cosmology We present the Data Quality Report Builder toolkit, DQRbuild, a suite of data quality tools that have been developed to vet gravitational-wave events in preparation for the fourth LIGO-Virgo-KAGRA observing run. We explain the main functionality and the many scientific tests that we support. To validate the performance of the tools included in the toolkit, we run a series of tests on all significant candidates shared as public alerts in the third observing run to compare against what was manually reported using human intervention. We find that these automated tools can now identify 96% of the problems identified by humans during this previous observing run, with a 24% false alarm rate. We conclude with a commentary on the prospects and potential challenges for fully automating the process of vetting the data quality for gravitational-wave events identified in future observing runs. |
| title | Rapid data quality investigations of gravitational-wave events with the Data Quality Report Builder toolkit |
| topic | Instrumentation and Methods for Astrophysics General Relativity and Quantum Cosmology |
| url | https://arxiv.org/abs/2605.16183 |