A Chandra look at the X-ray faint millisecond pulsars in the globular cluster NGC 6752
Bibliographic record
Abstract
We combine new and archival Chandra observations of the globular cluster NGC 6752 to create a deeper X-ray source list, and study the faint radio millisecond pulsars (MSPs) of this cluster. We detect four of the five MSPs in NGC 6752, and present evidence for emission from the fifth. The X-rays from these MSPs are consistent with thermal emission from the neutron star surfaces, with significantly higher fitted blackbody temperatures than other globular cluster MSPs (though we cannot rule out contamination by non-thermal emission or other X-ray sources). NGC 6752 E is one of the lowest-LX MSPs known, with LX(0.3–8 keV) = |$1.0^{+0.9}_{-0.5}\times 10^{30}$| erg s−1. We check for optical counterparts of the three isolated MSPs in the core using new Hubble Space Telescope Advanced Camera for Surveys images, finding no plausible counterparts, which is consistent with their lack of binary companions. We compile measurements of LX and spin-down power for radio MSPs from the literature, including errors where feasible. We find no evidence that isolated MSPs have lower LX than MSPs in binary systems, omitting binary MSPs showing emission from intrabinary wind shocks. We find weak evidence for an inverse correlation between the estimated temperature of the MSP X-rays and the known MSP spin period, consistent with the predicted shrinking of the MSP polar cap size with increasing spin period.
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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 | 0.002 | 0.001 |
| 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) | 0.003 | 0.001 |
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".