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arXiv · 2510.21930

Characterizing Low-Latency Sky Localization in Multi-Detector Gravitational-Wave Networks

Abstract

Low-latency analyses of gravitational-wave (GW) data from LIGO, Virgo, and KAGRA enable rapid detection of compact binary coalescences (CBC) and prompt sky localization, essential for electromagnetic follow-up in multi-messenger astronomy. We evaluate the performance and limitations of low-latency sky localization using BAYESTAR algorithm, and investigate the impact of low-significance Virgo triggers. We inject simulated CBC signals into Gaussian-stationary noise and into Virgo data from the second part of the third LIGO-Virgo observing run (O3b), then reconstruct skymaps across multiple detector network configurations. Localization accuracy is assessed using Percentile-Percentile plots, the Jaccard index, and the Kullback-Leibler divergence. Binary neutron star mergers are statistically consistent with ideal calibration, showing deviations below 3$\sigma$, particularly when Virgo is included in the network, whereas skymaps for neutron star--black hole and binary black hole mergers tend to be overconfident. Adding a third detector generally improves accuracy, but the searched area can degrade when Virgo's signal-to-noise ratio is low (SNR $\leq$ 5). For high-SNR events, relying on two detectors can mislocalize the source. Excluding Virgo can therefore cause the HL skymap to miss the true location when Virgo has strong antenna response, in such cases a three-detector configuration is required to recover the correct position and avoid misleading multi-messenger follow-up. We introduce diagnostics to flag problematic skymaps and apply them to O3 public alerts, recovering simulation-predicted trends and flagging a few anomalous morphologies. The results are relevant for improving rapid vetting of GW alerts and guiding observational strategies in multi-messenger astronomy.

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Amazigh Ouzriat, Viola Sordini, Francesco Di Renzo. 2025-10-24. Characterizing Low-Latency Sky Localization in Multi-Detector Gravitational-Wave Networks. https://arxiv.org/abs/2510.21930

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