Measuring black hole spin through gravitational lensing of pulsars
Bibliographic record
Abstract
Abstract We propose a new procedure for measuring the spin of a black hole with an unprecedented accuracy based on the gravitational lensing of millisecond pulsars. We derive the basic equations for lensing by a rotating black hole. We show that the frame dragging effect increases the deflection angle of a light ray co-rotating with the black hole. For the primary (secondary) images the angular positions are larger (smaller) for a rotating black hole by an amount on the order of tens of microarcseconds. The differential time delay of images for the case in which the lens is a rotating black hole is smaller than that in the case of non-rotating lens of the same mass, and it can be larger than a few milliseconds. We show that this quantity offers the possibility of reducing the error of spin measurement to less than one percent if we could measure the differential time delay with accuracy of microseconds. We also study relativistic images that are produced by light rays that rotate around the black hole before reaching the observer. The angular positions of relativistic images on the same side as the primary (secondary) image are a few microarcseconds larger (smaller) if the black hole is rotating. Furthermore, the differential time delay between relativistic images is about twelve orders of magnitude larger in the case of rotating lens.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".