Star−Disk Collisions: Implications for Quasi-periodic Eruptions and Other Transients near Supermassive Black Holes
Bibliographic record
Abstract
Abstract We use Athena++ to study the hydrodynamics of repeated star−accretion disk collisions close to supermassive black holes, and we discuss their implications for the origin of quasi-periodic eruptions (QPEs) and other repeating nuclear transients. We quantify the impact of the collisions on the stellar structure, the amount of stripped stellar debris, and the orbital properties of the debris. We provide simple fitting functions for the stellar mass loss per collision; the mass loss is much larger after repeated collisions, due to the dilute stellar atmosphere shock-heated in earlier collisions. The lifetime of the QPE-emitting phase set by stellar mass loss in star−disk collision models for QPEs is thus at most ∼1000 yr; it is shortest for eRO-QPE2, of order a few decades. The mass of the stripped stellar debris per collision and its orbital properties imply that currently observed QPEs are not powered by direct star−disk collisions but rather by collisions between the stellar debris liberated in previous collisions and the accretion disk (“circularization shocks”). We discuss how the hydrodynamics of this interaction can explain the diverse timing properties of QPEs, including the regular timing of GSN 069 and eRO-QPE2 and the large flare-to-flare timing variations observed in eRO-QPE1. QPEs with recurrence times of many days, if observed, may have more regular timing.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".