Search for gravitational waves associated with 39 gamma-ray bursts using data from the second, third, and fourth LIGO runs
Bibliographic record
Abstract
We present the results of a search for short-duration gravitational-wave bursts associated with 39 gamma-ray bursts (GRBs) detected by gamma-ray satellite experiments during LIGO's S2, S3, and S4 science runs. The search involves calculating the crosscorrelation between two interferometer data streams surrounding the GRB trigger time. We search for associated gravitational radiation from single GRBs, and also apply statistical tests to search for a gravitational-wave signature associated with the whole sample. For the sample examined, we find no evidence for the association of gravitational radiation with GRBs, either on a single-GRB basis or on a statistical basis. Simulating gravitational-wave bursts with sine-Gaussian waveforms, we set upper limits on the root-sum-square of the gravitational-wave strain amplitude of such waveforms at the times of the GRB triggers. We also demonstrate how a sample of several GRBs can be used collectively to set constraints on population models. The small number of GRBs and the significant change in sensitivity of the detectors over the three runs, however, limits the usefulness of a population study for the S2, S3, and S4 runs. Finally, we discuss prospects for the search sensitivity for the ongoing S5 run, and beyond for the next generation of detectors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| 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".