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Fast evaluation of multi-detector consistency for real-time gravitational wave searches

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arxiv 1901.02227 v2 pith:GJVX5LYN submitted 2019-01-08 gr-qc astro-ph.IM

classification gr-qcastro-ph.IM
keywords gravitationalwavereal-timeidentificationsecondsignalefficientligo
verification ladder T0 review T1 audit T2 compute T3 formal
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Gravitational waves searches for compact binary mergers with LIGO and Virgo are presently a two stage process. First, a gravitational wave signal is identified. Then, an exhaustive search over possible signal parameters is performed. It is critical that the identification stage is efficient in order to maximize the number of gravitational wave sources that are identified. Initial identification of gravitational wave signals with LIGO and Virgo happens in real-time which requires that less than one second of computational time must be used for each one second of gravitational wave data collected. In contrast, subsequent parameter estimation may require hundreds of hours of computational time to analyze the same one second of gravitational wave data. The real-time identification requirement necessitates efficient and often approximate methods for signal analysis. We describe one piece of real-time gravitational-wave identification: an efficient method for ascertaining a signal's consistency between multiple gravitational wave detectors suitable for real-time gravitational wave searches for compact binary mergers. This technique was used in analyses of Advanced LIGO's second observing run and Advanced Virgo's first observing run.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. PINCH: Pipeline-Informed Noise Characterization in LIGO's Third Observing Run

    gr-qc 2025-05 conditional novelty 6.0 of 10

    PINCH uses support vector machines trained on clean GstLAL triggers to identify glitch-induced triggers, revealing class-specific patterns in how transient noise contaminates LIGO's third observing run.

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