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arXiv · astro-ph/0403410

Probing the RGB-phase transition: Near-IR photometry of six intermediate age LMC clusters

Abstract

This is the first of a series of papers devoted to a global study of the photometric properties of the red stellar sequences in a complete sample of the Large Magellanic Cloud clusters, by means of near infrared array photometry. Deep J,H,Ks photometry and accurate Color Magnitude Diagrams down to K=18.5, i.e. 1.5 mag below the red He-clump, for six intermediate age clusters (namely NGC1987, NGC2108, NGC2190, NGC2209, NGC2231, NGC2249) are presented. A quantitative estimate of the population ratios (by number and luminosity) between Red Giant Branch and He-clump stars for each target cluster is provided and discussed in the framework of probing the so-called Red Giant Branch phase transition (RGB Ph-T). By using the Elson & Fall s-parameter as an age indicator, the observed RGB population shows a sharp enhancement (both in number and luminosity) at s=36. Obviously, the corresponding absolute age strictly depends on the details of theoretical models adopted to calibrate the s-parameter. Curiously, the currently available calibrations of the s-parameter in term of age based on canonical (by Elson & Fall 1988) and overshooting (Girardi et al. 1995) models provide ages that well agree within 10%, suggesting that the full development of the Red Giant Branch occurs at t=700 Myr and be a relatively fast event (delta t=300 Myr). However, the RGB Ph-T epoch derived from the overshooting calibration of the s-parameter turns out to be significantly earlier than the epoch provided by the recent evolutionary tracks by Girardi et al. (2000). A new calibration of the s-parameter based on high quality Color Magnitude Diagrams and updated models is urged to address the origin of this discrepancy and finally establish the epoch of the RGB Ph-T.

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Francesco R. Ferraro, Livia Origlia, Vincenzo Testa, Claudia Maraston. 2004-03-17. Probing the RGB-phase transition: Near-IR photometry of six intermediate age LMC clusters. https://doi.org/10.1086/420837

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