Speaker
Description
Spectral (periodogram) analysis has proved effective for identifying oscillatory behavior in Hα solar filament observations. In this preliminary study, we apply recent periodogram‐based frameworks—those of Luna et al. (2022) and Castelló et al. (2025)—to extreme-ultraviolet (EUV) image sequences from the Solar Orbiter mission. Adopting a Bayesian inference approach with a red-noise background model, we will evaluate whether periodic signals can be robustly detected across the full field of view. Our primary goal is to determine the feasibility of these techniques for automatic oscillation detection and spatial characterization in EUV time sequences, thereby eliminating the need for manually placed analysis slits. The outcomes will inform the development of a systematic, data-driven pipeline for mapping solar oscillations in high-resolution EUV datasets.
