Methods and results of a search for gravitational waves associated with gamma-ray bursts using the GEO 600, LIGO, and Virgo detectors
Bibliographic record
Abstract
In this paper we report on a search for short-duration gravitational wave bursts in the frequency range 64 Hz–1792 Hz associated with gamma-ray bursts (GRBs), using data from GEO 600 and one of the LIGO or Virgo detectors. We introduce the method of a linear search grid to analyze GRB events with large sky localization uncertainties, for example the localizations provided by the Fermi Gamma-ray Burst Monitor (GBM). Coherent searches for gravitational waves (GWs) can be computationally intensive when the GRB sky position is not well localized, due to the corrections required for the difference in arrival time between detectors. Using a linear search grid we are able to reduce the computational cost of the analysis by a factor of O(10) for GBM events. Furthermore, we demonstrate that our analysis pipeline can improve upon the sky localization of GRBs detected by the GBM, if a high-frequency GW signal is observed in coincidence. We use the method of the linear grid in a search for GWs associated with 129 GRBs observed satellite-based gamma-ray experiments between 2006 and 2011. The GRBs in our sample had not been previously analyzed for GW counterparts. A fraction of our GRB events are analyzed using data from GEO 600 while the detector was using squeezed-light states to improve its sensitivity; this is the first search for GWs using data from a squeezed-light interferometric observatory. We find no evidence for GW signals, either with any individual GRB in this sample or with the population as a whole. For each GRB we place lower bounds on the distance to the progenitor, under an assumption of a fixed GW emission energy of 10−2M⊙c2, with a median exclusion distance of 0.8 Mpc for emission at 500 Hz and 0.3 Mpc at 1 kHz. The reduced computational cost associated with a linear search grid will enable rapid searches for GWs associated with Fermi GBM events once the advanced LIGO and Virgo detectors begin operation. © 2014 The American Physical Society
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".