Implementation of an $\mathcal{F}$-statistic all-sky search for continuous gravitational waves in Virgo VSR1 data
Bibliographic record
Abstract
We present an implementation of the $\\mathcal{F}$-statistic to carry out the\nfirst search in data from the Virgo laser interferometric gravitational wave\ndetector for periodic gravitational waves from a priori unknown, isolated\nrotating neutron stars. We searched a frequency $f_0$ range from 100 Hz to 1\nkHz and the frequency dependent spindown $f_1$ range from $-1.6\\,(f_0/100\\,{\\rm\nHz}) \\times 10^{-9}\\,$ Hz/s to zero. A large part of this frequency - spindown\nspace was unexplored by any of the all-sky searches published so far. Our\nmethod consisted of a coherent search over two-day periods using the\n$\\mathcal{F}$-statistic, followed by a search for coincidences among the\ncandidates from the two-day segments. We have introduced a number of novel\ntechniques and algorithms that allow the use of the Fast Fourier Transform\n(FFT) algorithm in the coherent part of the search resulting in a fifty-fold\nspeed-up in computation of the $\\mathcal{F}$-statistic with respect to the\nalgorithm used in the other pipelines. No significant gravitational wave signal\nwas found. The sensitivity of the search was estimated by injecting signals\ninto the data. In the most sensitive parts of the detector band more than 90%\nof signals would have been detected with dimensionless gravitational-wave\namplitude greater than $5 \\times 10^{-24}$.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".