Effects of transients in LIGO suspensions on searches for gravitational waves
Bibliographic record
Abstract
This paper presents an analysis of the transient behavior of the Advanced LIGO (Laser Interferometer Gravitational-wave Observatory) suspensions used to seismically isolate the optics. We have characterized the transients in the longitudinal motion of the quadruple suspensions during Advanced LIGO's first observing run. Propagation of transients between stages is consistent with modeled transfer functions, such that transient motion originating at the top of the suspension chain is significantly reduced in amplitude at the test mass. We find that there are transients seen by the longitudinal motion monitors of quadruple suspensions, but they are not significantly correlated with transient motion above the noise floor in the gravitational wave strain data, and therefore do not present a dominant source of background noise in the searches for transient gravitational wave signals. Using the suspension transfer functions, we compared the transients in a week of gravitational wave strain data with transients from a quadruple suspension. Of the strain transients between 10 and 60 Hz, 84% are loud enough that they would have appeared above the sensor noise in the top stage quadruple suspension monitors if they had originated at that stage at the same frequencies. We find no significant temporal correlation with the suspension transients in that stage, so we can rule out suspension motion originating at the top stage as the cause of those transients. However, only 3.2% of the gravitational wave strain transients are loud enough that they would have been seen by the second stage suspension sensors, and none of them are above the sensor noise levels of the penultimate stage. Therefore, we cannot eliminate the possibility of transient noise in the detectors originating in the intermediate stages of the suspension below the sensing noise.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".