NEUTRON STAR RADIUS MEASUREMENT WITH THE QUIESCENT LOW-MASS X-RAY BINARY U24 IN NGC 6397
Bibliographic record
Abstract
This paper reports the spectral and timing analyses of the quiescent low-mass X-ray binary (qLMXB) U24 observed during five archived Chandra /ACIS exposures of the nearby globular cluster NGC 6397, for a total of 350 ks. We find that the X-ray flux and the parameters of the hydrogen atmosphere spectral model are consistent with those previously published for this source. On short timescales, we find no evidence of aperiodic intensity variability, with 90% confidence upper limits during five observations ranging between <8.6% rms and <19% rms, in the 0.0001–0.1 Hz frequency range (0.5–8.0 keV); and no evidence of periodic variability, with maximum observed powers in this frequency range having a chance probability of occurrence from a Poisson-deviated light curve in excess of 10%. We also report the improved neutron star (NS) physical radius measurement, with statistical accuracy of the order of ∼10%: R NS = 8.9 +0.9 −0.6 km for M NS = 1.4 M ☉ . Alternatively, we provide the confidence regions in mass–radius space as well as the best-fit projected radius R ∞ = 11.9 +1.0 −0.8 km, as seen by an observer at infinity. The best-fit effective temperature, kT eff = 80 +4 −5 eV, is used to estimate the NS core temperature which falls in the range T core = (3.0–9.8) × 10 7 K , depending on the atmosphere model considered. This makes U24 the third most precisely measured NS radius among qLMXBs, after those in ω Cen and M13.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".