The sensitivity of harassment to orbit: mass loss from early-type dwarfs in galaxy clusters
Bibliographic record
Abstract
We conduct a comprehensive numerical study of the orbital dependence of harassment on early-type dwarfs consisting of 168 different orbits within a realistic, Virgo-like cluster, varying in eccentricity and pericentre distance. We find harassment is only effective at stripping stars or truncating their stellar discs for orbits that enter deep into the cluster core. Comparing to the orbital distribution in cosmological simulations, we find that the majority of the orbits (more than three quarters) result in no stellar mass loss. We also study the effects on the radial profiles of the globular cluster systems of early-type dwarfs. We find these are significantly altered only if harassment is very strong. This suggests that perhaps most early-type dwarfs in clusters such as Virgo have not suffered any tidal stripping of stars or globular clusters due to harassment, as these components are safely embedded deep within their dark matter halo. We demonstrate that this result is actually consistent with an earlier study of harassment of dwarf galaxies, despite the apparent contradiction. Those few dwarf models that do suffer stellar stripping are found out to the virial radius of the cluster at redshift = 0, which mixes them in with less strongly harassed galaxies. However when placed on phase-space diagrams, strongly harassed galaxies are found offset to lower velocities compared to weakly harassed galaxies. This remains true in a cosmological simulation, even when haloes have a wide range of masses and concentrations. Thus phase-space diagrams may be a useful tool for determining the relative likelihood that galaxies have been strongly or weakly harassed.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".