GRAVITATIONAL WAVES FROM INDIVIDUAL SUPERMASSIVE BLACK HOLE BINARIES IN CIRCULAR ORBITS: LIMITS FROM THE NORTH AMERICAN NANOHERTZ OBSERVATORY FOR GRAVITATIONAL WAVES
Bibliographic record
Abstract
We perform a search for continuous gravitational waves from individual supermassive black hole binaries using robust frequentist and Bayesian techniques. We augment standard pulsar timing models with the addition of time-variable dispersion measure and frequency variable pulse shape terms. We apply our techniques to the Five Year Data Release from the North American Nanohertz Observatory for Gravitational Waves. We find that there is no evidence for the presence of a detectable continuous gravitational wave; however, we can use these data to place the most constraining upper limits to date on the strength of such gravitational waves. Using the full 17 pulsar data set we place a 95% upper limit on the strain amplitude of h 0 ≲ 3.0 × 10 −14 at a frequency of 10 nHz. Furthermore, we place 95% sky-averaged lower limits on the luminosity distance to such gravitational wave sources, finding that d L ≳ 425 Mpc for sources at a frequency of 10 nHz and chirp mass 10 10 M ☉ . We find that for gravitational wave sources near our best timed pulsars in the sky, the sensitivity of the pulsar timing array is increased by a factor of ∼four over the sky-averaged sensitivity. Finally we place limits on the coalescence rate of the most massive supermassive black hole binaries.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".