A systematic analysis of star cluster disruption by tidal shocks – I. Controlled N-body simulations and a new theoretical model
Bibliographic record
Abstract
Understanding the evolution of stellar clusters in an evolving tidal field is critical for studying the disruption of stellar clusters in a cosmological context. We systematically characterize the response of stellar clusters to tidal shocks using controlled N-body simulations of clusters with various properties that are subjected to different types of shocks. We find that the strength of the shock and the density of the cluster within the half-mass radius are the dominant properties that drive the amount of mass lost by the cluster, with the shape of the cluster profile being of minor influence. When the shock is applied as two separate sub-shocks, the amount of mass-loss during the second sub-shock is sensitive to the gap time between them. Clusters that experience successive sub-shocks separated by less than their crossing time attain the same masses and sizes at the end of the simulation. However, clusters subjected to sub-shocks separated by more than a crossing time experience different evolutionary histories. The amount of mass lost in the N-body models and its scaling with shock and cluster properties differ from that predicted by classical tidal disruption theory. We demonstrate that the discrepancy is alleviated by including a dependence on the escape time-scale of unbound stars, analogously to mass-loss driven by two-body relaxation. With our new theoretical model for shock-driven mass-loss, the predicted relative amounts of mass-loss agree with the results of the N-body simulations to ∼0.3 dex across the full suite of simulations.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".