Observational constraints on the optical and near-infrared emission from the neutron star-black hole binary merger S190814bv
Bibliographic record
Abstract
On 2019 August 14, the LIGO and Virgo interferometers detected a high-significance event labelled S190814bv. Preliminary analysis of the GW data suggests that the event was likely due to the merger of a compact binary system formed by a BH and a NS. ElectromagNetic counterparts of GRAvitational wave sources at the VEry Large Telescope (ENGRAVE) collaboration members carried out an intensive multi-epoch, multi-instrument observational campaign to identify the possible optical/near infrared counterpart of the event. In addition, the ATLAS, GOTO, GRAWITA-VST, Pan-STARRS and VINROUGE projects also carried out a search on this event. Our observations allow us to place limits on the presence of any counterpart and discuss the implications for the kilonova (KN) possibly generated by this NS-BH merger, and for the strategy of future searches. Altogether, our observations allow us to exclude a KN with large ejecta mass $M\gtrsim 0.1\,\mathrm{M_\odot}$ to a high ($>90\%$) confidence, and we can exclude much smaller masses in a subsample of our observations. This disfavours the tidal disruption of the neutron star during the merger. Despite the sensitive instruments involved in the campaign, given the distance of S190814bv we could not reach sufficiently deep limits to constrain a KN comparable in luminosity to AT 2017gfo on a large fraction of the localisation probability. This suggests that future (likely common) events at a few hundreds Mpc will be detected only by large facilities with both high sensitivity and large field of view. Galaxy-targeted observations can reach the needed depth over a relevant portion of the localisation probability with a smaller investment of resources, but the number of galaxies to be targeted in order to get a fairly complete coverage is large, even in the case of a localisation as good as that of this event.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".