A multi-scale spectral pipeline using deep learning filament detection automatically identifies 91 oscillatory events in two weeks of 2014 GONG data, recovering known events and finding new ones with periods 20-126 min.
Physics of Solar Prominences: II - Magnetic Structure and Dynamics
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Observations and models of solar prominences are reviewed. We focus on non-eruptive prominences, and describe recent progress in four areas of prominence research: (1) magnetic structure deduced from observations and models, (2) the dynamics of prominence plasmas (formation and flows), (3) Magneto-hydrodynamic (MHD) waves in prominences and (4) the formation and large-scale patterns of the filament channels in which prominences are located. Finally, several outstanding issues in prominence research are discussed, along with observations and models required to resolve them.
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Automatic detection of solar filament oscillations I: Multi-scale spectral pipeline
A multi-scale spectral pipeline using deep learning filament detection automatically identifies 91 oscillatory events in two weeks of 2014 GONG data, recovering known events and finding new ones with periods 20-126 min.