Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-30T00:59:29.603Z Has data issue: false hasContentIssue false

Automated p-mode identification using Bayes' theorem

Published online by Cambridge University Press:  03 August 2017

Timothy M. Brown*
Affiliation:
High Altitude Observatory/National Center for Atmospheric Research* P.O. Box 3000 Boulder, CO 80303 U.S.A.

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The task of interpreting p-mode spectra is complicated by the presence of a very large number of oscillation modes, each of which may appear (because of aliasing) in the power spectra corresponding to several values of l and m. Identifying peaks in a power spectrum with particular modes in an interactive fashion thus quickly becomes impractical. Here I describe an automated method for doing this identification. The method is based on an application of Bayes' theorem, which provides a simple way to use prior knowledge about the oscillation spectrum. The method takes as input the observed power spectra, and a model of the amplitudes and frequencies one expects to see.

Type
Chapter 8: Techniques for Observing Solar Oscillations
Copyright
Copyright © Reidel 1988 

References

Cox, R.T. 1961, The Algebra of Probable Inference, The Johns Hopkins Press, Baltimore.CrossRefGoogle Scholar
Duvall, T.L. 1982, Nature, 300, 242.CrossRefGoogle Scholar