USING MILLIMETER VLBI TO CONSTRAIN RIAF MODELS OF SAGITTARIUS A*
Bibliographic record
Abstract
The recent detection of Sagittarius A* at λ = 1.3 mm on a baseline from Hawaii to Arizona demonstrates that millimeter wavelength very long baseline interferometry (VLBI) can now spatially resolve emission from the innermost accretion flow of the Galactic center region. Here, we investigate the ability of future millimeter VLBI arrays to constrain the spin and inclination of the putative black hole and the orientation of the accretion disk major axis within the context of radiatively inefficient accretion flow (RIAF) models. We examine the range of baseline visibility and closure amplitudes predicted by RIAF models to identify critical telescopes for determining the spin, inclination, and disk orientation of the Sgr A* black hole and accretion disk system. We find that baseline lengths near 3 Gλ have the greatest power to distinguish amongst RIAF model parameters, and that it will be important to include new telescopes that will form north–south baselines with a range of lengths. If an RIAF model describes the emission from Sgr A*, it is likely that the orientation of the accretion disk can be determined with the addition of a Chilean telescope to the array. Some likely disk orientations predict detectable fluxes on baselines between the continental United States and even a single 10–12 m dish in Chile. The extra information provided from closure amplitudes by a four-antenna array enhances the ability of VLBI to discriminate amongst model parameters.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".