The effects of dwarf galaxies on the orbital evolution of galactic globular clusters
Bibliographic record
Abstract
ABSTRACT We investigate the effect that dwarf galaxies have on the orbits, tidal histories, and assumed formation environment of Milky Way globular clusters. We determine the orbits of the Milky Way’s 150 globular clusters in a gravitational potential both with and without dwarf galaxies. We find that the presence of a small number of satellite galaxies can affect the orbits of many of the globular clusters. Over 12 Gyr, we find that the semimajor axis and orbital eccentricity of individual clusters fluctuate with dispersions of the order of $\sim 10{{\ \rm per\ cent}}$ and $\sim 4{{\ \rm per\ cent}}$, respectively. Outer clusters are more strongly affected by dwarf galaxies than inner clusters, with their semimajor axis and orbital eccentricities fluctuating by more than $\sim 15{{\ \rm per\ cent}}$ and $\sim 5{{\ \rm per\ cent}}$, respectively. Using detailed N-body simulations of select clusters, we find that altering their orbital histories can lead to different mass-loss rates and structural evolution. Furthermore, we caution against using kinematics alone to identify whether a Galactic cluster formed in situ or was accreted during a past merger event as these values are no longer conserved. The presence of dwarf galaxies causes the orbital energies and actions of individual clusters to evolve over time, spanning a wider range than that coming from random uncertainties in a cluster’s proper motions and radial velocity.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".