The effect of dwarf galaxies on the tidal tails of globular clusters
Bibliographic record
Abstract
ABSTRACT The tidal tails of globular clusters have been shown to be sensitive to the external tidal field. We investigate how Galactic globular clusters with observed tails are affected by satellite dwarf galaxies by simulating tails in galaxy models with and without dwarf galaxies. The simulations indicate that tidal tails can be subdivided into three categories based on how they are affected by dwarf galaxies: (1) dwarf galaxies perturb the progenitor cluster’s orbit (NGC 4590, Pal 1, Pal 5), (2) dwarf galaxies perturb the progenitor cluster’s orbit and individual tail stars (NGC 362, NGC 1851, NGC 4147, NGC 5466, NGC 7492, Pal 14, Pal 15), and (3) dwarf galaxies negligibly affect tidal tails (NGC 288, NGC 5139, NGC 5904, Eridanus). Perturbations to a cluster’s orbit occur when dwarf galaxies pass within its orbit, altering the size and shape of the orbital and tail path. Direct interactions between one or more dwarf galaxies and tail stars lead to kinks and spurs, however we find that features are more difficult to observe in projection. We further find that the tails of Pal 5 are shorter in the galaxy model with dwarf galaxies as it is closer to apocentre, which results in the tails being compressed. Additional simulations reveal that differences between tidal tails in the two galaxy models are primarily due to the Large Magellanic Cloud. Understanding how dwarf galaxies affect tidal tails allows for tails to be used to map the distribution of matter in dwarf galaxies and the Milky Way.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".