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We present frb-voe , a publicly available software package that enables radio observatories to broadcast fast radio burst (FRB) alerts to subscribers through low-latency virtual observatory events (VOEvents). We describe a use case of frb-voe by the Canadian Hydrogen Intensity Mapping Experiment Fast Radio Burst (CHIME/FRB) Collaboration, which has broadcast thousands of FRB alerts to subscribers worldwide. Using this service, observers have daily opportunities to conduct rapid multiwavelength follow-up observations of new FRB sources. Alerts are distributed as machine-readable reports and as emails containing FRB metadata, and are available to the public within approximately 13 s of detection. A sortable database and a downloadable JSON file containing FRB metadata from all broadcast alerts can be found on CHIME/FRB’s public webpage. The frb-voe service also provides users with the ability to retrieve FRB names from the Transient Name Server through the frb-voe client user interface. The frb-voe service can act as a foundation on which any observatory that detects FRBs can build its own VOEvent broadcasting service to contribute to the coordinated multiwavelength follow-up of astrophysical transients.

GWSkyNet-Multi is a machine learning model developed for the classification of candidate gravitational-wave events detected by the LIGO and Virgo observatories. The model uses limited information released in the low-latency Open Public Alerts to produce prediction scores indicating whether an event is a merger of two black holes (BHs), a merger involving a neutron star (NS), or a non-astrophysical glitch. This facilitates time-sensitive decisions about whether to perform electromagnetic follow-up of candidate events during LIGO-Virgo-KAGRA (LVK) observing runs. However, it is not well understood how the model is leveraging the limited information available to make its predictions. As a deep learning neural network, the inner workings of the model can be difficult to interpret, impacting our trust in its validity and robustness. We tackle this issue by systematically perturbing the model and its inputs to explain what underlying features and correlations it has learned for distinguishing the sources. We show that the localization area of the 2D sky maps and the computed coherence versus incoherence Bayes factors are used as strong predictors for distinguishing between real events and glitches. The estimated distance to the source is further used to discriminate between binary BH mergers and mergers involving NSs. We leverage these findings to show that events misclassified by GWSkyNet-Multi in LVK’s third observing run have distinct sky areas, coherence factors, and distance values that influence the predictions and explain these misclassifications. The results help identify the model’s limitations and inform potential avenues for further optimization.

We present an extensive contemporaneous X-ray and radio campaign performed on the repeating fast radio burst (FRB) source FRB 20220912A for 8 weeks immediately following the source’s detection by CHIME/FRB. This includes X-ray data from XMM-Newton, NICER, and Swift, and radio detections of FRB 20220912A from CHIME/Pulsar and Effelsberg. We detect no significant X-ray emission at the time of 30 radio bursts with upper limits on a 0.5–10.0 keV X-ray fluence of (1.5–14.5) × 10 ^−10 erg cm ^−2 (99.7% credible interval, unabsorbed) on a timescale of 100 ms. Translated into a fluence ratio η _x/r = F _X-ray / F _radio , this corresponds to η _x/r < 7 × 10 ^6 . For persistent emission from the location of FRB 20220912A, we derive a 99.7% 0.5–10.0 keV isotropic flux limit of 8.8 × 10 ^−15 erg cm ^−2 s ^−1 (unabsorbed) or an isotropic luminosity limit of 1.4 × 10 ^41 erg s ^−1 at a distance of 362.4 Mpc. We derive a hierarchical extension to the standard Bayesian treatment of low-count and background-contaminated X-ray data, which allows the robust combination of multiple observations. This methodology allows us to place the best (lowest) 99.7% credible interval upper limit on an FRB η _x/r to date, η _x/r < 2 × 10 ^6 , assuming that all 30 detected radio bursts are associated with X-ray bursts with the same fluence ratio. If we instead adopt an X-ray spectrum similar to the X-ray burst observed contemporaneously with FRB-like emission from the Galactic magnetar SGR 1935+2154 detected on 2020 April 28, we derive a 99.7% credible interval upper limit on η _x/r of 8 × 10 ^5 , which is only 3 times the observed value of η _x/r for SGR 1935+2154.