Swift/BAT and RXTE/ASM Observations of the 35 day X-Ray Cycle of Hercules X-1
Bibliographic record
Abstract
Abstract Swift/BAT and RXTE/ASM observations have monitored the X-ray binary system Her X-1 for approximately 14.5 yr each, and both were monitoring Her X-1 for a period of ∼5.5 yr. Here we study the 35 day cycle using these observations. Using a cross-correlation method we find the times of peaks of the 35 day cycles for ∼150 cycles observed by Swift/BAT and ∼150 cycles observed by RXTE/ASM. These cycles include ∼60 observed with both instruments. The noise level of the RXTE/ASM measurements is larger than that of Swift/BAT, resulting in larger uncertainty in peak times. The distribution of 35 day cycle lengths can be fit with a Gaussian with mean 34.79 days and σ of 1.1 days. The distribution of orbital phases of 35 day cycle peaks is well fit by a uniform distribution, with 76% of the cycles, plus a Gaussian distribution peaked at orbital phase ∼0.5, with 24% of the cycles. We construct the long-term average 35 day lightcurve in the 15–50 keV band from Swift/BAT, and in the 2–12 keV band from RXTE/ASM. The high-energy band shows more variability in the short high state and the low-energy band shows more variability in the main high state. This is consistent with a precessing accretion disk model as the cause of the 35 day cycle.
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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 | 0.002 | 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) | 0.001 | 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".