On the variation of Fourier parameters for Galactic and LMC Cepheids at optical, near-infrared and mid-infrared wavelengths
Bibliographic record
Abstract
We present a light-curve analysis of fundamental-mode Galactic and Large Magellanic Cloud (LMC) Cepheids based on the Fourier decomposition technique. We have compiled light-curve data for Galactic and LMC Cepheids in optical (VI), near-infrared (JHKs) and mid-infrared (3.6 and 4.5 μm) bands from the literature and determined the variation of their Fourier parameters as a function of period and wavelength. We observed a decrease in Fourier amplitude parameters and an increase in Fourier phase parameters with increasing wavelengths at a given period. We also found a decrease in the skewness and acuteness parameters as a function of wavelength at a fixed period. We applied a binning method to analyse the progression of the mean Fourier parameters with period and wavelength. We found that for periods longer than about 20 d, the values of the Fourier amplitude parameters increase sharply for shorter wavelengths as compared to wavelengths longer than the J band. We observed the variation of the Hertzsprung progression with wavelength. The central period of the Hertzsprung progression was found to increase with wavelength in the case of the Fourier amplitude parameters and decrease with increasing wavelength in the case of phase parameters. We also observed a small variation of the central period of the progression between the Galaxy and LMC, presumably related to metallicity effects. These results will provide useful constraints for stellar pulsation codes that incorporate stellar atmosphere models to produce Cepheid light curves in various bands.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| 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".