Spacetime Tomography Using the Event Horizon Telescope
Bibliographic record
Abstract
Abstract We have now entered a new era of high-resolution imaging astronomy with the beginning of the Event Horizon Telescope (EHT). The EHT can resolve the dynamics of matter in the immediate vicinity around black holes at and below the horizon scale. One of the candidate black holes, Sagittarius A*, flares 1–4 times a day depending on the wavelength. A possible interpretation of these flares could be hotspots generated through magnetic-reconnection events in the accretion flow. In this paper, we construct a semi-analytical model for hotspots that includes the effects of shearing as a spot moves along the accretion flow. We then explore the ability of the EHT to recover these hotspots. Even including significant systematic uncertainties, such as thermal noise, diffractive scattering, and background emission due to an accretion disk, we were able to recover the hotspots and spacetime structure to sub-percent precision. Moreover, by observing multiple flaring events we show how the EHT could be used to tomographically map spacetime. This provides new avenues for testing relativistic fluid dynamics and general relativity near the event horizon of supermassive black holes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".