EVOLUTION OF ACCRETION DISKS IN TIDAL DISRUPTION EVENTS
Bibliographic record
Abstract
During a stellar tidal disruption event (TDE), an accretion disk forms as stellar debris returns to the disruption site and circularizes. Rather than being confined within the circularizing radius, the disk can spread to larger radii to conserve angular momentum. A spreading disk is a source of matter for re-accretion at rates that may exceed the later stellar fallback rate, although a disk wind can suppress its contribution to the central black hole accretion rate. A spreading disk is detectible through a break in the central accretion rate history or, at longer wavelengths, by its own emission. We model the evolution of TDE disk size and accretion rate by accounting for the time-dependent fallback rate, for the influence of wind losses in the early advective stage, and for the possibility of thermal instability for accretion rates intermediate between the advection-dominated and gas-pressure-dominated states. The model provides a dynamic basis for modeling TDE light curves. All or part of a young TDE disk will precess as a solid body because of the Lense–Thirring effect, and precession may manifest itself as a quasi-periodic modulation of the light curve. The precession period increases with time. Applying our results to the jetted TDE candidate Swift J1644+57, whose X-ray light curve shows numerous quasi-periodic dips, we argue that the data best fit a scenario in which a main-sequence star was fully disrupted by an intermediate mass black hole on an orbit significantly inclined from the black hole equator, with the apparent jet shutoff at t = 500 days corresponding to a disk transition from the advective state to the gas-pressure-dominated state.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".