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arxiv: 2605.19153 · v1 · pith:KDJRNCVOnew · submitted 2026-05-18 · 🌀 gr-qc · astro-ph.HE· astro-ph.IM

GstLAL O4 Online Results Paper

Shomik Adhicary , Pratyusava Baral , Amanda Baylor , Becca Ewing , Yun-Jing Huang , Rachael Huxford , Prathamesh Joshi , James Kennington
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Ryan Magee Cody Messick Wanting Niu Cort Posnansky Surabhi Sachdev Shio Sakon Urja Shah Divya Singh Leo Tsukada Zach Yarbrough Noah Zhang Kipp Cannon Sarah Caudill Bryce Cousins Jolien D. E. Creighton Heather Fong Richard N. George Olivia Godwin Reiko Harada Soichiro Kuwahara Alvin K. Y. Li Duncan Meacher Soichiro Morisaki Debnandini Mukherjee Alexander Pace Anarya Ray Stefano Schmidt Ron Tapia Koh Ueno Aaron Viets Leslie Wade Madeline Wade Graham Woan Chad Hanna
This is my paper

Pith reviewed 2026-05-20 08:40 UTC · model grok-4.3

classification 🌀 gr-qc astro-ph.HEastro-ph.IM
keywords gravitational wavesreal-time analysisGstLALO4 observing runlow latencybinary mergersastrophysical classificationfalse alarm rate
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The pith

GstLAL produced initial gravitational-wave candidate uploads at a median latency of 15.8 seconds with 98% effective uptime during O4.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper evaluates the GstLAL real-time analysis pipeline during the fourth observing run of the LIGO-Virgo-KAGRA network. It reports that the pipeline delivered candidate uploads quickly while staying operational for nearly the entire period examined. The search contributed to hundreds of plausible events, supplied the first public information for most of them, and matched final catalog results on the majority of classifications. These outcomes show how a low-latency pipeline supports rapid follow-up observations of potential electromagnetic or neutrino signals from mergers.

Core claim

The GstLAL real-time analysis is designed to identify candidates with low latency, high detection efficiency, and sustained operational uptime over long observing periods. Across O4, it produced initial candidate uploads with a median latency of 15.8 s while maintaining an effective uptime of 98% during the first two parts of the observing run. During the run, the analysis contributed to 250 candidates classified as astrophysically plausible, provided the first upload for 222 of these, and was the sole contributor for 75. Among Gravitational-Wave Transient Catalog events with a false-alarm rate below one per year, 88% were identified as significant in low latency and promoted for expert vet팅

What carries the argument

The GstLAL real-time analysis pipeline, which ranks candidates using a statistic and background model to separate signals from noise and issues low-latency uploads.

Load-bearing premise

The pipeline's ranking statistic and background model correctly separate real gravitational-wave signals from detector noise.

What would settle it

Finding that more than 12 percent of events with false-alarm rates below one per year were not flagged as significant in low latency, or that classification agreement with the final catalog fell substantially below 93 percent, would undermine the reported performance.

Figures

Figures reproduced from arXiv: 2605.19153 by Aaron Viets, Alexander Pace, Alvin K. Y. Li, Amanda Baylor, Anarya Ray, Becca Ewing, Bryce Cousins, Chad Hanna, Cody Messick, Cort Posnansky, Debnandini Mukherjee, Divya Singh, Duncan Meacher, Graham Woan, Heather Fong, James Kennington, Jolien D. E. Creighton, Kipp Cannon, Koh Ueno, Leo Tsukada, Leslie Wade, Madeline Wade, Noah Zhang, Olivia Godwin, Prathamesh Joshi, Pratyusava Baral, Rachael Huxford, Reiko Harada, Richard N. George, Ron Tapia, Ryan Magee, Sarah Caudill, Shio Sakon, Shomik Adhicary, Soichiro Kuwahara, Soichiro Morisaki, Stefano Schmidt, Surabhi Sachdev, Urja Shah, Wanting Niu, Yun-Jing Huang, Zach Yarbrough.

Figure 1
Figure 1. Figure 1: FIG. 1. Overview of the monitoring and alerting infrastruc [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2. Distribution of the percentage of data dropped by [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3. Distribution of upload latencies for GstLAL on [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4. Cumulative number of detections and candidates [PITH_FULL_IMAGE:figures/full_fig_p008_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5. Comparison of the online and offline FARs for all [PITH_FULL_IMAGE:figures/full_fig_p009_5.png] view at source ↗
read the original abstract

Gravitational-wave observations of merging binary neutron stars and black holes are now routinely made by detectors in the Advanced LIGO-Virgo-KAGRA network. Neutron star binary systems may also produce detectable electromagnetic and particle emission over times scales ranging from seconds to years. Real-time gravitational-wave searches play a central role in enabling time-critical electromagnetic and/or neutrino follow-up observations. During the fourth observing run (O4) of the Advanced LIGO-Virgo-KAGRA network, multiple real-time searches operated continuously to identify candidate gravitational-wave events and publicly disseminate information about these discoveries. Here, the performance and results of the GstLAL real-time analysis are reported. The analysis is designed to identify candidates with low latency, high detection efficiency, and sustained operational uptime over long observing periods. Across O4, it produced initial candidate uploads with a median latency of 15.8 s while maintaining an effective uptime of 98% during the first two parts of the observing run. During the run, the analysis contributed to 250 candidates classified as astrophysically plausible, provided the first upload for 222 of these, and was the sole contributor for 75. Among Gravitational-Wave Transient Catalog events with a false-alarm rate below one per year, 88% were identified as significant in low latency and promoted for expert vetting and public dissemination. The low-latency astrophysical classifications agreed with the final catalog classifications for 93% of the events considered.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 2 minor

Summary. The manuscript reports operational performance metrics for the GstLAL real-time gravitational-wave search pipeline during the O4 run of the LIGO-Virgo-KAGRA network. Key results include a median latency of 15.8 s for initial candidate uploads, 98% effective uptime in the first two parts of the run, contributions to 250 astrophysically plausible candidates (first upload for 222, sole contributor for 75), identification of 88% of GWTC events with FAR below 1/yr as significant in low latency, and 93% agreement between low-latency astrophysical classifications and final catalog classifications.

Significance. If the reported counts and timings hold, this work supplies a concrete benchmark for the reliability of an established low-latency pipeline over a multi-month observing run. The quantitative documentation of latency, uptime, and classification agreement is useful for planning multi-messenger follow-up campaigns and for comparing real-time search performance across pipelines.

major comments (1)
  1. [Results / classification agreement paragraph] The 93% classification agreement and 88% identification rate are presented without an explicit statement of the event sample size, selection cuts, or statistical uncertainties. If these percentages are load-bearing for the claim of reliable low-latency performance, the manuscript should specify the denominator (number of events considered) and any error estimation in the relevant results section.
minor comments (2)
  1. [Abstract and § on uptime] The abstract and main text use 'effective uptime' without a precise definition or formula; a short parenthetical or footnote clarifying how downtime intervals are excluded would improve reproducibility.
  2. [Latency results] Table or figure showing the distribution of upload latencies would strengthen the median 15.8 s claim; if such a figure exists, ensure axis labels and caption explicitly state the time window used.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their positive assessment of the manuscript and recommendation for minor revision. We address the single major comment below.

read point-by-point responses

  1. Referee: [Results / classification agreement paragraph] The 93% classification agreement and 88% identification rate are presented without an explicit statement of the event sample size, selection cuts, or statistical uncertainties. If these percentages are load-bearing for the claim of reliable low-latency performance, the manuscript should specify the denominator (number of events considered) and any error estimation in the relevant results section.

    Authors: We agree that the manuscript would benefit from greater explicitness on these points to support the claims of reliable low-latency performance. In the revised version, we have updated the relevant results section to state the exact number of events in the denominator for both percentages, clarify the selection cuts (GWTC events with FAR below 1/yr for the identification rate; events with available low-latency and catalog classifications for the agreement rate), and include statistical uncertainties on the percentages. revision: yes

Circularity Check

0 steps flagged

No significant circularity; factual operational metrics

full rationale

The paper reports empirical performance metrics from running the established GstLAL pipeline on O4 data, including direct counts of candidate uploads, latency timings, uptime percentages, and classification agreement rates with the final catalog. These are observational results logged from the run rather than any derivation chain, fitted parameters, or predictions. No equations or self-referential steps appear; references to prior GstLAL work provide context for the pipeline but are not load-bearing for the reported numbers, which stand independently as factual records.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

This is an observational performance report with no mathematical model, free parameters, or new postulated entities. All numbers are empirical tallies of pipeline outputs during the run.

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discussion (0)

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