A new visual -- near-infrared diagnostic to estimate the metallicity of cluster and field dwarf stars
Annalisa Calamida (OAR-INAF), M. Monelli, A. P. Milone (IAC), G. Bono, (Univ. Tor Vergata), A. Pietrinferni (OACTe-INAF), E. P. Lagioia (Univ. Tor, Vergata)

TL;DR
This paper introduces a new visual and near-infrared color-based metallicity diagnostic for dwarf stars, calibrated with models and tested on field stars and globular clusters, achieving high accuracy.
Contribution
It presents a novel MIC relation for estimating stellar metallicity using visual-NIR colors, calibrated with alpha-enhanced models and validated on various stellar samples.
Findings
Photometric metallicity estimates agree within 0.1 dex of spectroscopic measurements.
The method accurately estimates metallicity for both field dwarfs and globular clusters.
The calibration provides reliable results across a wide metallicity range.
Abstract
We present a theoretical calibration of a new metallicity diagnostic based on the Stroemgren index m1 and on visual -- near-infrared (NIR) colors to estimate the global metal abundance of cluster and field dwarf stars. To perform the metallicity calibration we adopt alpha-enhanced evolutionary models transformed into the observational plane by using atmosphere models computed adopting the same chemical mixture. We apply the new visual - NIR Metallicity-Index-Color (MIC) relations to two different samples of field dwarfs and we find that the difference between photometric estimates and spectroscopic measurements is on average smaller than 0.1 dex, with a dispersion smaller than sigma = 0.3 dex. We apply the same MIC relations to a metal-poor (M 92) and a metal-rich (47 Tuc) globular cluster. We find a peak of -2.01+/-0.08 (sigma = 0.30 dex) and -0.47+/-0.01 (sigma = 0.42 dex),…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
