Pan-STARRS Follow-up of the Gravitational-wave Event S250818k and the Light Curve of SN2025ulz
Bibliographic record
Abstract
Abstract Kilonovae are the scientifically rich—but observationally elusive—optical transient phenomena associated with compact binary mergers. Only a handful of events have been discovered to date, all through multiwavelength (gamma-ray) and multimessenger (gravitational-wave) signals. Given their scarcity, it is important to maximise the discovery possibility of new kilonova events. To this end, we present our follow-up observations of the gravitational-wave signal S250818k—a plausible binary neutron star merger at a distance of 237 ± 62 Mpc. Pan-STARRS tiled 286 and 318 deg 2 (32% and 34% of the 90% sky localisation region) within 3 and 7 days of the GW signal, respectively. ATLAS covered 65% of the sky map within 3 days, but with lower sensitivity. These observations uncovered 47 new transients; however, none were deemed to be linked to S250818k. We undertook an expansive follow-up campaign of AT2025ulz, the purported counterpart to S250818k. The griz -band light curve, combined with our redshift measurement ( z = 0.0849 ± 0.0003), all indicate that SN2025ulz is a type IIb supernova and thus not the counterpart to S250818k. We rule out the presence of an AT2017gfo-like kilonova within ≈27% of the distance posterior sampled by our Pan-STARRS pointings (≈9.1% across the total 90% 3D sky localisation). We demonstrate that early observations are optimal for probing the distance posterior of the 3D gravitational-wave sky map, and that SN2025ulz was a plausible kilonova candidate for ≲5 days, before ultimately being ruled out.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".