The Second Annual Spitzer Science Center Conference: Infrared Diagnostics of Galaxy Evoluti

Catherine L. Buchanan, Rochester Institute of Technology
Joel H. Kastner, Rochester Institute of Technology
William J. Forrest, University of Rochester
Bruce J. Hrivnak, Valparaiso University
Raghvendra Sahai, NASA Jet Propulsion Laboratory
Michael Egan, Air Force Research Laboratory
Adam Frank, University of Rochester
Cecilia Barnbaum, Valdosta University

This is the pre-print of a paper published by the Astronomical Society of the Pacific. The final, published version is available here:

© 2008 Astronomical Society of the Pacific

Presented at the Second Annual Spitzer Science Center Conference: Infrared Diagnostics of Galaxy Evolution

This work is based on observations made with the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA. Support for this work was provided by NASA through awards issued by JPL/Caltech. The IRS was a collaborative venture between Cornell University and Ball Aerospace Corporation funded by NASA through the Jet Propulsion Laboratory and Ames Research Center.

Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.


We have produced an atlas of Spitzer Infrared Spectrograph (IRS) spectra of mass-losing, evolved stars in the Large Magellanic Cloud. These stars were selected to have high mass-loss rates and so contribute significantly to the return of processed materials to the ISM. Our high-quality spectra enable the determination of the chemistry of the circumstellar envelope from the mid-IR spectral features and continuum. We have classified the spectral types of the stars and show that the spectral types separate clearly in infrared color-color diagrams constructed from 2MASS data and synthetic IRAC/MIPS fluxes derived from our IRS spectra. We present diagnostics to identify and classify evolved stars in nearby galaxies with high confidence levels using Spitzer and 2MASS photometry. Comparison of the spectral classes determined using IRS data with the IR types assigned based on NIR colors also revealed a significant number of misclassifications and enabled us to refine the NIR color criteria resulting in more accurate NIR color classifications of dust-enshrouded objects.