Probing the Subparsec Dust of a Supermassive Black Hole with the Tidal Disruption Event AT 2020mot
Bibliographic record
Abstract
Abstract AT 2020mot is a typical UV/optical tidal disruption event (TDE) with no radio or X-ray signatures in a quiescent host. We find an i-band excess and rebrightening along the decline of the light curve which could be due to two consecutive dust echoes from the TDE. We model our observations following van Velzen et al. and find that the near-infrared light curve can be explained by concentric rings of thin dust within ∼0.1 pc of a ∼6 × 106 M ⊙ supermassive black hole (SMBH), among the smallest scales at which dust has been inferred near SMBHs. We find dust covering factors of order f c ≤ 2%, much lower than found for dusty tori of active galactic nuclei. These results highlight the potential of TDEs for uncovering the environments around black holes when including near-infrared observations in high-cadence transient studies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".