Measuring the Ellipticity of M87* Images
Bibliographic record
Abstract
Abstract The Event Horizon Telescope (EHT) images of the supermassive black hole at the center of the galaxy M87 provided the first image of the accretion environment on horizon scales. General relativity (GR) predicts that the image of the shadow should be nearly circular given the inclination angle of the black hole M87*. A robust detection of ellipticity in image reconstructions of M87* could signal new gravitational physics on horizon scales. Here we analyze whether the imaging parameters used in EHT analyses are sensitive to ring ellipticity, and measure the constraints on the ellipticity of M87*. We find that the top set is unable to recover ellipticity. Even for simple geometric models, the true ellipticity is biased low, preferring circular rings. Therefore, to place a constraint on the ellipticity of M87*, we measure the ellipticity of 550 synthetic data sets produced from GRMHD simulations. We find that images with intrinsic axis ratios of 2:1 are consistent with the ellipticity seen from EHT image reconstructions.
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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 | 0.001 | 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".