This material is part of several data products associated with GWTC-3, the third Gravitational-Wave Transient Catalog from the LIGO Scientific Collaboration, the Virgo Collaboration, and the KAGRA Collaboration. For more information, see the paper (dcc.ligo.org/LIGO-P2000318/public), the related material linked from this page, and the GWTC-3 data release documentation (www.gw-openscience.org/GWTC-3/). This release contains two data-quality products that are used by search analyses to help mitigate non-Gaussian noise in the detector data. Gating removes short-duration artifacts from the data by smoothly rolling the affected data to zero. The iDQ glitch likelihood uses machine learning to predict the probability that a non-Gaussian transient is present using information from auxiliary channels. Gating files used in analyses of O3 LIGO data As a pre-processing step, the PyCBC search pipeline uses an inverted-Tukey window to mitigate the effect of loud, non-Gaussian features in the data. This is further described in Usman et al. 2016. A subset of these times are the times listed in the txt files H1-O3_GATES_1238166018-31197600.txt L1-O3_GATES_1238166018-31197600.txt These times in these files were chosen based on auxiliary monitors of overflows in the digital-to-analog converters used to control the positions of the test masses. The gated times (i.e. the time period where the data is zeroed) are time segments where these monitors recorded an overflow were. The central time and suggested half-width of zero time were chosen to fully cover these time seconds. The final gating parameter, the suggested taper time was chosen to be 0.5 to balance the cost of impacting more data with the window function versus introducing additional artifacts into the data. The syntax of the files themselves is {central time} {suggested half-width of zero time} {suggested taper time} with each row containing the parameters of a single gate. The included notebook provides an example of how to read in and apply one of the suggested gates. Renormalized iDQ timeseries The renormalized iDQ timeseries data-quality product is used within the GstLAL search pipeline to generate results for GWTC-3. This data product was found to be statistically helpful in improving data quality within the GstLAL search pipeline. This is further described in Godwin et al. 2020. This file contains a time series for each LIGO detector related to the probability of a glitch in the strain data given the behavior in analyzed auxiliary channels monitoring the behavior of the detectors and their environment. H1L1-IDQ_TIMESERIES-1256655642-12905976.h5 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 et al. 2020, and the time dataset corresponds to the times associated with the renormalized iDQ log-likelihoods in the data dataset. How to download all files from this page If you would like to download all files on this page, we recommend zenodo_get: pip install zenodo_get zenodo-get RECORD_ID_OR_DOI where the record ID for the most recent version of this page is 5636795 and IDs for other versions can be found in the Versions section at the side of this page. For more general background on gravitational-wave data quality, try the materials from a GW Open Data Workshop or the guide to LIGO–Virgo data analysis.

LIGO Laboratory and Advanced LIGO are funded by the United States National Science Foundation (NSF) as well as the Science and Technology Facilities Council (STFC) of the United Kingdom, the Max-Planck-Society (MPS), and the State of Niedersachsen/Germany for support of the construction of Advanced LIGO and construction and operation of the GEO600 detector. Additional support for Advanced LIGO was provided by the Australian Research Council. Virgo is funded, through the European Gravitational Observatory (EGO), by the French Centre National de Recherche Scientifique (CNRS), the Italian Istituto Nazionale di Fisica Nucleare (INFN) and the Dutch Nikhef, with contributions by institutions from Belgium, Germany, Greece, Hungary, Ireland, Japan, Monaco, Poland, Portugal, Spain. The construction and operation of KAGRA are funded by Ministry of Education, Culture, Sports, Science and Technology (MEXT), and Japan Society for the Promotion of Science (JSPS), National Research Foundation (NRF) and Ministry of Science and ICT (MSIT) in Korea, Academia Sinica (AS) and the Ministry of Science and Technology (MoST) in Taiwan.

{"references": ["LIGO Scientific Collaboration and Virgo Collaboration and KAGRA Collaboration, GWTC-3, https://doi.org/10.7935/b024-1886"]}