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Determination of Broadening Functions using the Singular Value Decomposition (SVD) Technique

Published online by Cambridge University Press:  12 April 2016

Slavek Rucinski*
Affiliation:
Canada-France-Hawaii Telescope Co., Kamuela, HI 96743, USA

Abstract

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The cross-correlation function (CCF) has become the standard tool for extraction of radial-velocity and broadening information from high resolution spectra. It permits integration of information which is common to many spectral lines into one function which is easy to calculate, visualize and interpret. However, the CCF is not the best tool for many applications where it should be replaced by the proper broadening function (BF). Typical applications requiring use of BFs rather than CCFs involve finding locations of star spots, studies of projected shapes of highly distorted stars such as contact binaries (as no assumptions can be made about BF symmetry or even continuity) and [Fe/H] metallicity determinations (good baselines and avoidance of negative lobes are essential). It is stressed that the CCFs are not broadening functions. This note concentrates on the advantages of determining BFs through the process of linear inversion, preferably accomplished using the singular value decomposition (SVD). Some basic examples of numerical operations are given in the IDL programming language.

Type
Part 2. Fundamental Concepts and Techniques
Copyright
Copyright © Astronomical Society of the Pacific 1999

References

Anderson, L., Stanford, D. & Leininger, D. 1983, ApJ, 270, 200 Google Scholar
Craig, I.J.D. & Brown, J.C. 1986, Inverse Problems in Astronomy, (Bristol and Boston: Adam Hilger Ltd)Google Scholar
Golub, G.H. & Van Loan, C.F. 1989, Matrix Computations, 2nd ed. (Baltimore: Johns Hopkins Univ. Press)Google Scholar
Press, W.H., Teukolsky, S.A., Vetterling, W.T. & Flannery, B.P. 1986, Numerical Recipes, Cambridge University Press (all editions)Google Scholar
Rix, H.-W. & White, S.D.M. 1992, MNRAS, 254, 384 Google Scholar
Rucinski, S.M. 1992, AJ, 104, 1968 Google Scholar
Rucinski, S.M., Lu, W.-X. & Shi, J. 1993, AJ, 106, 1174;Google Scholar
Tonry, J. & Davis, M. 1979, AJ, 84, 1511 CrossRefGoogle Scholar
Zucker, S. & Mazeh, T. 1994, ApJ, 420, 806 Google Scholar