Stellar spectroscopic classification has been successfully automated by a number of groups. Automated classification and parameterization work best when applied to a homogeneous data set, and thus these techniques primarily have been developed for and applied to large surveys. While most ongoing large spectroscopic surveys target extragalactic objects, many stellar spectra have been and will be obtained. We briefly summarize past work on automated classification and parameterization, with emphasis on the work done in our group. Accurate automated classification in the spectral type domain and parameterization in the temperature domain have been relatively easy. Automated parameterization in the metallicity domain, formally outside the MK system, has also been effective. Due to the subtle effects on the spectrum, automated classification in the luminosity domain has been somewhat more difficult, but still successful. In order to extend the use of automated techniques beyond a few surveys, we present our current efforts at building a web-based automated stellar spectroscopic classification and parameterization machine. Our proposed machinery would provide users with MK classifications as well as the astrophysical parameters of effective temperature, surface gravity, mean abundance, abundance anomalies, and microturbulence.
The Garrison Festschrift
L. Davis Press
The Garrison Festchrift Conference
Number of Pages
Scholarly Commons Citation
von Hippel, T., Prieto, C. A., & Sneden, C. (2002). Automated Stellar Spectral Classification and Parameterization for the Masses. The Garrison Festschrift, (). Retrieved from https://commons.erau.edu/publication/1171
Appeared in The Garrison Festchrift conference proceedings (2003).
Dr. von Hippel was not affiliated with Embry-Riddle Aeronautical University at the time this paper was published.