Using Long-term Millisecond Pulsar Timing to Obtain Physical Characteristics of the Bulge Globular Cluster Terzan 5
Bibliographic record
Abstract
Abstract Over the past decade, the discovery of three unique stellar populations and a large number of confirmed pulsars within the globular cluster Terzan 5 has raised questions over its classification. Using the long-term radio pulsar timing of ms pulsars in the cluster core, we provide new measurements of key physical properties of the system. As Terzan 5 is located within the galactic bulge, stellar crowding and reddening make optical and near-infrared observations difficult. Pulsar accelerations, however, allow us to study the intrinsic characteristics of the cluster independent of reddening and stellar crowding and probe the mass density profile without needing to quantify the mass-to-light ratio. Relating the spin and orbital periods of each pulsar to the acceleration predicted by a King model, we find a core density of × 106 pc−3, a core radius of pc, a pulsar density profile of , and a total mass of ( pc) ≃ 3.0 × 105 , assuming a cluster distance of 5.9 kpc. Using this information, we argue against Terzan 5 being a disrupted dwarf galaxy and discuss the possibility of it being a fragment of the Milky Way’s proto-bulge. We also discuss whether low-mass pulsars were formed via electron-capture supernovae or exist in a core full of heavy white dwarfs and hard binaries. Finally, we provide an upper limit for the mass of a possible black hole at the core of the cluster of .
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".