The prospects of pulsar timing with new-generation radio telescopes and the Square Kilometre Array
Bibliographic record
Abstract
Pulsars are highly magnetized and rapidly rotating neutron stars. As they spin, the lighthouse-like beam of radio emission from their magnetic poles sweeps across the Earth with a regularity approaching that of the most precise clocks known. This precision combined with the extreme environments in which they are found, often in compact orbits with other neutron stars and white dwarfs, makes them excellent tools for studying gravity. Present and near-future pulsar surveys, especially those using the new generation of telescopes, will find more extreme binary systems and pulsars that are more precise 'clocks'. These telescopes will also greatly improve the precision to which we can measure the arrival times of the pulses. The Square Kilometre Array will revolutionize pulsar searches and timing precision. The increased number of sources will reveal rare sources, including possibly a pulsar-black hole binary, which can provide the most stringent tests of strong-field gravity. The improved timing precision will reveal new phenomena and also allow us to make a detection of gravitational waves in the nanohertz frequency regime. It is here where we expect to see the signature of the binary black holes that are formed as galaxies merge throughout cosmological history.This article is part of a discussion meeting issue 'The promises of gravitational-wave astronomy'.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".