The likelihood of undiscovered globular clusters in the outskirts of the Milky Way
Bibliographic record
Abstract
ABSTRACT The currently known Galactic globular cluster population extends out to a maximum galactocentric distance of ∼145 kpc, with the peculiarity that the outermost clusters predominantly have an inward velocity. Orbit averaging finds that this configuration occurs by chance about $6{{\ \rm per\ cent}}$ of the time, suggesting that several globular clusters with positive radial velocities remain undiscovered. We evaluate the expected number of undiscovered clusters at large distances under the assumption that the cluster population has a smooth radial distribution and is in equilibrium within the Milky Way’s virial radius. By comparing the present day kinematic properties of outer clusters to random orbital configurations of the Galactic globular cluster system through orbit averaging, we estimate a likelihood of $73{{\ \rm per\ cent}}$ of there being at least one undiscovered globular cluster within the Milky Way. This estimate assumes the current population is complete out to 50 kpc, and increases to $91{{\ \rm per\ cent}}$ if the population is complete out to 150 kpc. The likelihood of there being two undiscovered clusters is between $60$ and $70{{\ \rm per\ cent}}$, with the likelihood of there being three undiscovered clusters being on the order of $50{{\ \rm per\ cent}}$. The most likely scenario is that the undiscovered clusters are moving outwards, which results in the outer cluster population being consistent with an equilibrium state. Searches for distant and possibly quite low concentration and very low metallicity globular clusters will be enabled with upcoming deep imaging surveys.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".