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Low-latency gravitational wave alert products and their performance at the time of the fourth LIGO-Virgo-KAGRA observing run

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arxiv 2308.04545 v4 pith:WUKT2EXC submitted 2023-08-08 astro-ph.HE

classification astro-ph.HE
keywords dataproductsperformancealertinfrastructurelow-latencysearchesduring
verification ladder T0 review T1 audit T2 compute T3 formal

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Multi-messenger searches for BNS and NSBH mergers are currently one of the most exciting areas of astronomy. The search for joint electromagnetic and neutrino counterparts to GWs has resumed with O4. To support this effort, public semi-automated data products are sent in near real-time and include localization and source properties to guide complementary observations. In preparation for O4, we have conducted a study using a simulated population of compact binaries and a MDC in the form of a real-time replay to optimize and profile the software infrastructure and scientific deliverables. End-to-end performance was tested, including data ingestion, running online search pipelines, performing annotations, and issuing alerts to the astrophysics community. We present an overview of the low-latency infrastructure and the performance of the data products that are now being released during O4 based on the MDC. We report the expected median latency for the preliminary alert of full bandwidth searches (29.5s) and show consistency and accuracy of released data products using the MDC. For the first time, we report the expected median latency for triggers from early warning searches (-3.1s), which are new in O4 and target neutron star mergers during inspiral phase. This paper provides a performance overview for LVK low-latency alert infrastructure and data products using the MDC and serves as a useful reference for the interpretation of O4 detections.

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Forward citations

Cited by 4 Pith papers

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

  1. Ab Initio Real-Time Gravitational-Wave Parameter Estimation

    gr-qc 2026-07 accept novelty 6.0 of 10

    Slice-within-Gibbs nested sampling on modern GPUs delivers well-calibrated BNS parameter estimation in ~12 minutes uncompressed and ~89 seconds with heterodyning, from cold priors.

  2. Detectability of Gravitational-wave counterparts of EP-FXTs observed during the O4b LIGO-Virgo-KAGRA Observing Run

    astro-ph.HE 2026-07 conditional novelty 6.0 of 10

    No gravitational-wave counterpart is statistically associated with any of 47 Einstein Probe fast X-ray transients in the O4b run; 90% exclusion distances of ~178 Mpc (BNS) and ~349 Mpc (NSBH) disfavor nearby compact-b...

  3. Searching for binary black hole mergers with deep learning in Advanced LIGO's third observing run

    gr-qc 2025-12 conditional novelty 5.0 of 10

    A hybrid matched-filter/deep-learning pipeline recovers 31 known O3 events and reports a new tentative high-mass candidate, with sensitivity comparable to existing searches only for chirp masses above 25 solar masses.

  4. Applications of machine learning in gravitational wave research with current interferometric detectors

    gr-qc 2024-12 unverdicted

    A community review of machine learning in current gravitational-wave detectors, mapping where ML already works in production (noise subtraction, glitch classification, low-latency classification) and where traditional...

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