Multiple and changing cycles of active stars I. Methods of analysis and application to the solar cycles

TL;DR

This paper introduces and applies advanced time-frequency analysis methods, especially wavelets and other distributions, to study the complex, multi-scale magnetic activity cycles of the Sun and active stars, overcoming limitations of traditional periodicity methods.

Contribution

It demonstrates the effectiveness of time-frequency distributions in analyzing stellar activity data and reveals complex, evolving solar cycles using these techniques.

Findings

Time-frequency methods effectively analyze stellar activity variations.

Noise has minimal impact on long-term cycle detection.

Solar activity exhibits complex, multi-scale evolution.

Abstract

Long-term observational data have information on the magnetic cycles of active stars and that of the Sun. The changes in the activity of our central star have basic effects on Earth, like variations in the global climate. Therefore understanding the nature of these variations is extremely important. The observed variations related to magnetic activity cannot be treated as stationary periodic variations, therefore methods like Fourier transform or different versions of periodogramms give only partial information on the nature of the light variability. We demonstrate that time-frequency distributions provide useful tools for analyzing the observations of active stars. With test data we demonstrate that the observational noise has practically no effect on the determination in the the long-term changes of time-series observations of active stars. The rotational signal may modify the determined cycles, therefore it is advisable to remove it from the data. Wavelets are less powerful in recovering complex long-term changes than other distributions which are discussed. Applying our technique to the sunspot data we find a complicated, multi-scale evolution in the solar activity.