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The stellar populations of deeply embedded young clusters: Near-infrared spectral classification

  • Michael R. Meyer
  • Suzan Edwards
  • Kenneth Hinkle
  • Michael F. Skrutskie
  • Stephen E. Strom
Part III: Young Stellar Objects and Their Environment
Part of the Lecture Notes in Physics book series (LNP, volume 465)

Abstract

Deeply embedded clusters of young stars offer a unique opportunity to study stellar evolution at the very earliest phases. We describe a program aimed at understanding the formation of young stellar objects (YSOs) through the use of near-infrared spectroscopy. Over the past 18 months, we have carried out an extensive survey of fundamental MK spectral standard stars in the near-infrared spanning luminosity classes I–II, III, and IV–V from spectral types O5 through M5 at a resolving power of R=3500. We summarize the results of this survey and present a two-dimensional classification scheme derived from H-band spectra. We have also observed a set of well-studied optically-visible young stars in the Taurus molecular cloud at high spectral resolution in the H-band in order to quantify the effects of accretion activity on near-infrared classification spectroscopy of young stellar objects. Our sample covers a range of spectral types and disk accretion rates including classical and weak-lined T Tauri stars. Results suggest that spectral types derived from infrared spectra agree with their optically derived counterparts to within a few subclasses for late-type stars. Further, weak-lined T Tauri star spectra closely resemble dwarf star spectra although they appear to have somewhat lower surface gravities. We also use these data to calculate the level of infrared excess emission in some classical T Tauri stars. Such measurements of the infrared “veiling” will provide crucial constraints on models of the distribution of warm circumstellar material surrounding some YSOs.

Keywords

Spectral Type Stellar Population Initial Mass Function Tauri Star Young Stellar Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag 1996

Authors and Affiliations

  • Michael R. Meyer
    • 1
  • Suzan Edwards
    • 2
  • Kenneth Hinkle
    • 3
  • Michael F. Skrutskie
    • 1
  • Stephen E. Strom
    • 1
  1. 1.Department of Physics and AstronomyUniversity of MassachusettsAmherst
  2. 2.Astronomy DepartmentSmith CollegeNorthampton
  3. 3.National Optical Astronomy ObservatoriesTucson

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