Searches after Gravitational Waves Using ARizona Observatories (SAGUARO): Observations and Analysis from Advanced LIGO/Virgo's Third Observing Run
Bibliographic record
Abstract
Abstract With the conclusion of the third observing run for Advanced LIGO/Virgo (O3), we present a detailed analysis of both triggered and serendipitous observations of 17 gravitational-wave (GW) events (7 triggered and 10 purely serendipitous) from the Searches After Gravitational-waves Using ARizona Observatories (SAGUARO) program. We searched a total of 4935 deg 2 down to a median 5 σ transient detection depth of 21.1 AB mag using the Mt. Lemmon 1.5 m telescope, the discovery engine for SAGUARO. In addition to triggered events within 24 hr, our transient search encompassed a time interval following GW events of <120 hr, providing observations on ∼1/2 of the events accessible to the Mt. Lemmon 1.5 m telescope. We covered 2.1%–86% of the LVC total probability ( P total ) for individual events, with a median P total ≈ 8% within <120 hr. Following improvements to our pipeline and the addition of serendipitous observations, we find a total of seven new optical candidates across five GW events, which we are unable to rule out after searching for additional information and comparing to kilonova models. Using both publicly available and our own late-time data, we investigated a total of 252 optical candidates for these 17 events, finding that only 65% were followed up in some capacity by the community. Of the total 252 candidates, we are able to rule out an additional 12 previously reported counterpart candidates. In light of these results, we discuss lessons learned from the SAGUARO GW counterpart search. We discuss how community coordination of observations and candidate follow-up, as well as the role of archival data, are crucial to improving the efficiency of follow-up efforts and preventing unnecessary duplication of effort with limited electromagnetic resources.
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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 | 0.000 | 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) | 0.001 | 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".