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A guide to LIGO–Virgo detector noise and extraction of transient gravitational-wave signals

2020· article· en· 347 citations· W2972304929 on OpenAlex· 10.1088/1361-6382/ab685e

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A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Opus teacher head0.029
GPT teacher head0.336
Teacher spread
0.306 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

Abstract The LIGO Scientific Collaboration and the Virgo Collaboration have cataloged eleven confidently detected gravitational-wave events during the first two observing runs of the advanced detector era. All eleven events were consistent with being from well-modeled mergers between compact stellar-mass objects: black holes or neutron stars. The data around the time of each of these events have been made publicly available through the gravitational-wave open science center. The entirety of the gravitational-wave strain data from the first and second observing runs have also now been made publicly available. There is considerable interest among the broad scientific community in understanding the data and methods used in the analyses. In this paper, we provide an overview of the detector noise properties and the data analysis techniques used to detect gravitational-wave signals and infer the source properties. We describe some of the checks that are performed to validate the analyses and results from the observations of gravitational-wave events. We also address concerns that have been raised about various properties of LIGO–Virgo detector noise and the correctness of our analyses as applied to the resulting data.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

The record

Venue
Classical and Quantum Gravity
Topic
Pulsars and Gravitational Waves Research
Field
Physics and Astronomy
Canadian institutions
Funders
Division of Human Resource DevelopmentDivision of PhysicsScience and Technology Facilities CouncilICTP South American Institute for Fundamental ResearchIstituto Nazionale di Fisica NucleareLeverhulme TrustScottish Funding CouncilRussian Science FoundationInstitut des Origines de LyonMinistero dello Sviluppo EconomicoMinistry of Education, IndiaNational Research Foundation of KoreaHungarian Scientific Research FundGeneralitat ValencianaCouncil of Scientific and Industrial Research, IndiaCentre National de la Recherche ScientifiqueIndustry CanadaNational Natural Science Foundation of ChinaEuropean CommissionNemzeti Kutatási Fejlesztési és Innovációs HivatalAbdus Salam International Centre for Theoretical PhysicsGovern de les Illes BalearsNederlandse Organisatie voor Wetenschappelijk OnderzoekAgence Nationale de la RechercheNational Research FoundationRussian Foundation for Basic ResearchEuropean Regional Development FundScottish Universities Physics AllianceConseil Régional, Île-de-FranceNational Research, Development and Innovation OfficeAgencia Estatal de InvestigaciónSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungScience and Engineering Research BoardNational Science Foundation
Keywords
CorrectnessDetectorLIGONoise (video)Noisy dataBackground noiseTransient (computer programming)
Has abstract in OpenAlex
yes