Applications of Autocorrelation Analysis to the Study of Variable Stars

Details Applications of Autocorrelation Analysis to the Study of Variable Stars Applications of Autocorrelation Analysis to the Study of Variable Stars

May 2001

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2001aas...198.4707p&link_type=abstract

American Astronomical Society, 198th AAS Meeting, #47.07; Bulletin of the American Astronomical Society, Vol. 33, p.849

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Scientific paper

Autocorrelation analysis is a simple method for looking for cyclic behavior in variable star data. We have found it to be a useful adjunct to light curves and Fourier analysis, especially for stars which are only semi-regular. Its aliasing properties are different from those of Fourier analysis, and it does not require the star to be strictly periodic. The method was described by Burki et al. (A&A 65, 363 (1978)) and implemented independently by Percy & Sen (IAU IBVS #3670 (1991)). Because it is conceptually simple, it is quite suitable for student research. We describe two general applications: (i) period analysis of yellow and red semi-regular variables, and luminous blue variables such as P Cyg; in these stars, the seasonal gaps in the data are often similar to the periods of the stars; and (ii) period analysis of short-period variables of A and B type using Hipparcos epoch photometry, which has many measurements over several hours, then gaps of several weeks. We show specific examples of each kind. We also discuss the limitations of the method. Thanks to NSERC Canada, the AAVSO visual and photoelectric programs, and a score of student collaborators for supporting this research.

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