Synthetic stellar photometry – I. General considerations and new transformations for broad-band systems
Bibliographic record
Abstract
After a pedagogical introduction to the main concepts of synthetic photometry, colours and bolometric corrections in the Johnson-Cousins, 2MASS, and HST-ACS/WFC3 photometric systems are generated from MARCS synthetic fluxes for various [Fe/H] and [alpha/Fe] combinations, and virtually any value of reddening E(B-V) < 0.7. The successes and failures of model fluxes in reproducing the observed magnitudes are highlighted. Overall, extant synthetic fluxes predict quite realistic broad-band colours and bolometric corrections, especially at optical and longer wavelengths: further improvements of the predictions for the blue and ultraviolet spectral regions await the use of hydrodynamic models where the microturbulent velocity is not treated as a free parameter. We show how the morphology of the colour-magnitude diagram (CMD) changes for different values of [Fe/H] and [alpha/Fe]; in particular, how suitable colour combinations can easily discriminate between red giant branch and lower main sequence populations with different [alpha/Fe], due to the concomitant loops and swings in the CMD. We also provide computer programs to produce tables of synthetic bolometric corrections as well as routines to interpolate in them. These colour-Teff-metallicity relations may be used to convert isochrones for different chemical compositions to various bandpasses assuming observed reddening values, thus bypassing the standard assumption of a constant colour excess for stars of different spectral type. We also show how such an assumption can lead to significant systematic errors. The MARCS transformations presented in this study promise to provide important constraints on our understanding of the multiple stellar populations found in globular clusters (e.g., the colours of lower main sequence stars are predicted to depend strongly on [alpha/Fe]) and of those located towards/in the Galactic bulge.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".