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

TL;DR

This study evaluates the performance of low-latency sky localization for gravitational-wave sources using BAYESTAR across detector networks, with a focus on the Virgo detector’s impact under Gaussian and real O3b noise. By injecting CBC signals into simulations and real Virgo data, and applying PP plots, Jaccard overlap, and KL divergence diagnostics, the authors quantify calibration, localization accuracy, and information gain when expanding from two- to three-detector networks. They find that binary neutron star localizations are generally well-calibrated, while BBH and NSBH posteriors tend to be overconfident, and that adding a third detector substantially improves localization, especially when Virgo has a strong antenna response, though low Virgo SNR can degrade results. The work also introduces practical skymap diagnostics and validates them on O3 public alerts, offering actionable guidance for rapid vetting and follow-up strategies in multi-messenger astronomy, while outlining future needs for calibration and integration with full parameter estimation.

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$σ$, 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.

Figures (17)

• Figure 1: Median amplitude spectral densities for LIGO Hanford, LIGO Livingston, and Virgo during the second part of the third observing run (O3b).
• Figure 2: PP plots assessing statistical calibration of sky localization across CBC categories, comparing results between Gaussian-stationary noise in Virgo (left column) and real Virgo strain data (right column). The diagonal line represents ideal calibration. The diagonal line represents ideal calibratio and shaded bands represent 1-, 2-, and 3-sigma confidence intervals.
• Figure 3: Impact of adding a third detector to a 2-detector baseline on the 90% contour sky area ratio. Each curve corresponds to a specific 2-detector configuration augmented by the third interferometer (H1, L1, or V1). Results include all CBC injections, shaded areas represent 1$\sigma$ error bands.
• Figure 4: SNR ($\rho_{IFO}$) versus SNR fraction ($f_{IFO}$) for each interferometer (H1, L1, V1), color-coded by the searched area ratio. Positive values (yellow) indicate improved localization when adding the third detector; negative values (blue) indicate a degradation.
• Figure 5: Distributions of the renormalized Jaccard index $J'_{90}$ comparing HLV to HL, HV, and LV skymaps, for all CBC sources. Each panel shows multiple distributions conditioned on increasing SNR thresholds in the third detector.