Swift Follow-up Observations of Gravitational-wave and High-energy Neutrino Coincident Signals
Bibliographic record
Abstract
Electromagnetic observations of gravitational-wave and high-energy neutrino events are crucial in understanding the physics of their astrophysical sources. X-ray counterparts are especially useful in studying the physics of the jet, the energy of the outflow, and the particle acceleration mechanisms in the system. Ultraviolet and optical observations can help us constrain the mass and velocity of the outflow and provide hints on the viewing angle. We present the Neil Gehrels Swift Observatory prompt searches for X-ray and UV/optical counterparts to the joint gravitational-wave and high-energy neutrino coincident events that happened during the third observing run of LIGO/Virgo. Swift observed the overlap between gravitational-wave and neutrino error regions for three of the considerable (p-value < 1%) joint gravitational-wave and high-energy neutrino coincident alerts, which were generated by the IceCube Neutrino Observatory in real time after triggering by the LIGO/Virgo gravitational-wave public alerts. The searches did not associate any X-ray or UV/optical counterparts with any of the joint gravitational-wave and high-energy neutrino coincident events; however, the follow-up of these alerts significantly improved the tiling techniques covering regions between the gravitational-wave sky maps and the neutrino's error regions, making the real-time system ready for future potential discoveries. We discuss the details of each follow-up procedure, the results of each search, and the plans for future searches.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".