The Search for Gravitational Waves
Bibliographic record
Abstract
There has been a significant advance in the sensitivity of broadband searches for gravitational waves, using an international network of kilometer-scale laser interferometers.This network has recently concluded a 22-month search for gravitational waves, covering a frequency range from 50 Hz to several kHz.Sensitivity to strains in space of the order of 10 -21 brings a variety of potential signals into range, from distortions of spinning neutron stars in our galaxy to the mergers of neutron stars and black holes in the Virgo cluster of galaxies.Technology development for a second generation of interferometers has matured and construction of Advanced LIGO interferometers began in 2008.This second generation of detectors, operating at the quantum limit, should provide a thousand-fold increase in the volume of space accessible to earthbound gravitational-wave detectors.Although the first detection of gravitational waves may be achieved by firstgeneration detectors before installation of Advanced LIGO begins in 2011, second-generation detectors will enable the routine detection of sources needed for gravitational-wave astronomy.This article describes the first and second generation detectors, gives some insight into what we have learned from observations and outlines future directions in this field.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.011 |
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".