Pulse Shapes from Rapidly Rotating Neutron Stars: Equatorial Photon Orbits
Bibliographic record
Abstract
We demonstrate that fitted values of the stellar radius obtained by fitting theoretical light curves to observations of millisecond-period X-ray pulsars can significantly depend on the method used to calculate the light curves. The worst-case errors in the fitted radius are evaluated by restricting ourselves to the case of light emitted and received in the equatorial plane of a rapidly rotating neutron star. First, using an approximate flux that is adapted to the one-dimensional nature of such an emission region, we show how pulse shapes can be constructed using an exact spacetime metric and fully accounting for time-delay effects. We compare this to a method that approximates the exterior spacetime of the star by the Schwarzschild metric, inserts special relativistic effects by hand, and neglects time-delay effects. By comparing these methods, we show that there are significant differences in these methods for some applications—for example, pulse timing and constraining the stellar radius. In the case of constraining the stellar radius, we show that fitting the approximate pulse shapes to the full calculation yields errors in the fitted radius of as much as approximately ±10%, depending on the rotation rate and size of the star as well as the details describing the emitting region. However, not all applications of pulse shape calculations suffer from significant errors; we also show that the calculation of the soft-hard phase lag for a 1 keV blackbody does not strongly depend on the method used for calculating the pulse shapes.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".