Millisecond Pulsars in Dense Star Clusters: Evolution, Scaling Relations, and the Galactic-center Gamma-Ray Excess
Bibliographic record
Abstract
Abstract The number of millisecond pulsars (MSPs) observed in Milky Way globular clusters has increased explosively in recent years, but the underlying population is still uncertain due to observational biases. We use state-of-the-art N-body simulations to study the evolution of MSP populations in dense star clusters. These cluster models span a wide range in initial conditions, including different initial masses, metallicities, and virial radii, which nearly cover the full range of properties exhibited by the population of globular clusters in the Milky Way. We demonstrate how different initial cluster properties affect the number of MSPs, for which we provide scaling relations as a function of cluster age and mass. As an application, we use our formulae to estimate the number of MSPs delivered to the Galactic center from inspiralling globular clusters to probe the origin of the Galactic-center gamma-ray excess detected by Fermi. We predict about 400 MSPs in the Galactic center from disrupted globular clusters, which can potentially explain most of the observed gamma-ray excess.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".