RAVEN (Rapid Association and Visualization Engine) is a software toolkit developed for fast and automated multi-messenger coincidence analysis between gravitational-wave (GW) candidates and high-energy astrophysical transients such as gamma-ray bursts (GRBs). Designed to support real-time operations, RAVEN evaluates the likelihood of associations between GW triggers (e.g., from LIGO/Virgo/KAGRA) and electromagnetic (EM) events from instruments like Fermi-GBM and Swift-BAT, helping to identify potential joint detections and prioritize follow-up observations.
Key Features
Real-Time Association Analysis
RAVEN compares the spatial and temporal coincidence between GW alerts and EM candidates to assess the probability of a genuine association. It considers localization overlaps, event times, and detection confidence to produce statistical significance estimates.
Sky Map Intersection Tools
Supports manipulation and comparison of sky localization maps in both flat and multi-order HEALPix formats. Users can compute intersection regions, credibility contours, and sky-overlap probabilities between GW and GRB maps.
Significance Estimation
Calculates false alarm probabilities (FAP) and p-values for candidate associations based on spatial and temporal coincidence, helping to quantify how likely a joint detection is to be astrophysical rather than due to chance.
Interoperability with Other Pipelines
Integrates with other tools such as NITRATES, GUANO, and Echo-Location, enabling streamlined workflows for detecting and evaluating GRB counterparts to GW events. RAVEN also supports ToO follow-up pipelines by providing prioritized targets with high statistical significance.
Multi-Messenger Visualization
Generates intuitive plots and overlays of sky localization maps from multiple observatories, aiding quick human interpretation and decision-making during follow-up campaigns.
Support for Broad Source Classes
While optimized for short GRBs and compact binary coalescences, RAVEN can also be applied to a broader range of EM and GW transients, including long GRBs, fast radio bursts (FRBs), and neutrinos.
Use Case
RAVEN is a core tool in the multi-messenger transient detection ecosystem. It is used to:
- Rapidly assess candidate associations between GW and EM signals.
- Generate statistically ranked lists of follow-up targets.
- Visualize and interpret joint localization maps from diverse observatories.
- Support scientific alerts and public communications in the event of significant multi-messenger detections.
- Provide upper-limit analysis in the case of non-detections by calculating probability-weighted flux limits.
By enabling rapid and robust statistical association of signals across observational channels, RAVEN enhances the scientific yield of multi-messenger astrophysics and strengthens the global infrastructure for detecting and responding to astrophysical transients.
Link: https://www.pnas.org/doi/suppl/10.1073/pnas.2316474121/suppl_file/pnas.2316474121.sapp.pdf