Age gradients in the stellar populations of massive star forming regions based on a new stellar chronometer

Konstantin V. Getman, Eric D. Feigelson, Michael A. Kuhn, Patrick S. Broos, Leisa K. Townsley, Tim Naylor, Matthew S. Povich, Kevin L. Luhman, Gordon P. Garmire

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Abstract

A major impediment to understanding star formation in massive star-forming regions (MSFRs) is the absence of a reliable stellar chronometer to unravel their complex star formation histories. We present a new estimation of stellar ages using a new method that employs near-infrared (NIR) and X-ray photometry, Age JX. Stellar masses are derived from X-ray luminosities using the LX -M relation from the Taurus cloud. J-band luminosities are compared to mass-dependent pre-main-sequence (PMS) evolutionary models to estimate ages. Age JX is sensitive to a wide range of evolutionary stages, from disk-bearing stars embedded in a cloud to widely dispersed older PMS stars. The Massive Young Star-Forming Complex Study in Infrared and X-ray (MYStIX) project characterizes 20 OB-dominated MSFRs using X-ray, mid-infrared, and NIR catalogs. The Age JX method has been applied to 5525 out of 31,784 MYStIX Probable Complex Members. We provide a homogeneous set of median ages for over 100 subclusters in 15 MSFRs; median subcluster ages range between 0.5 Myr and 5 Myr. The important science result is the discovery of age gradients across MYStIX regions. The wide MSFR age distribution appears as spatially segregated structures with different ages. The Age JX ages are youngest in obscured locations in molecular clouds, intermediate in revealed stellar clusters, and oldest in distributed populations. The NIR color index J-H, a surrogate measure of extinction, can serve as an approximate age predictor for young embedded clusters.

Original languageEnglish (US)
Article number108
JournalAstrophysical Journal
Volume787
Issue number2
DOIs
StatePublished - Jun 1 2014

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science

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