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Title:
Waves and wavelets: An automated detection technique for solar oscillations
Authors:
De Moortel, I.; McAteer, R. T. J.
Affiliation:
AA(School of Mathematics and Statistics, University of St Andrews), AB(National Research Council Research Associate, NASA Goddard Space Flight Center, Solar Physics Branch, Code 682)
Publication:
Solar Physics, Volume 223, Issue 1-2, pp. 1-11 (SoPh Homepage)
Publication Date:
09/2004
Origin:
SPRINGER
DOI:
10.1007/s11207-004-0806-7
Bibliographic Code:
2004SoPh..223....1D

Abstract

This paper investigates the possibility of automating the detection of propagating intensity perturbations in coronal loops using wavelet analysis. Two different sets of TRACE 171 Å images are studied using the automated wavelet routine presented by McAteer et al. (2004). Both localised, short-lived periodicities and sustained, periodic, oscillations are picked up by the routine, with the results dependent to a large extent on the signal-to-noise ratio of the dataset. At present, the automation is only partial; the relevance of the detected periodicity and the identification of the coronal structure supporting it still have to be determined by the user, as does the judging of the accuracy of the results. Care has to be taken when interpreting the results of the wavelet analysis, and a good knowledge of all possible factors that might influence or distort the results is a necessity. Despite these limitations, wavelet analysis can play an important role in automatically identifying a variety of phenomena and in the analysis of the ever-growing (observational or simulated) datasets.
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