The aim of this project is to carry out research on the complex dynamics of plasma and magnetic field structures in different layers of the solar atmosphere, with emphasis on their connectivity and energy balance. The project relies on the creation of theoretical models, advanced numerical simulations, the analysis of state-of-the-art observations, and the development and application of advanced diagnostic techniques. The key problems to be considered are:
The observational analysis of sunspot chromospheric oscillations.
A comprehensive study of the magnetic connectivity from photosphere to corona.
The observational detection of partial ionization effects in the Sun.
Solar prominence and filament studies with machine learning and radiative transfer modeling.
The modelling of the chromosphere and corona of cool stars.
Unravelling coronal bright points from numerical simulations and observations.
Evidence-based diagnostics of coronal waves and instabilities.
The extension of our in-house codes MANCHA3D/MAGEC to GPUs.
Update of Hazel2 Inversion Code.
The achievement of our goals will enable us to clarify the nature of the sudden brightenings in the core of chromospheric lines, to characterize them and determine their propagating/standing nature, and to quantify the wave energy budget in sunspots. It will shed light on the generation, transformation, and dissipation of energy by several physical mechanisms based on wave transformations, vortex motions, and shocks, across different layers of the atmosphere and taking into account partial ionization of the plasma. It will lead to the observational detection of multi-fluid effects, predicted and quantified by our models but yet to be discovered, by measuring the velocities of different species in different ionization states simultaneously. Using K- means clustering and radiative transfer modeling, it will address the complexity of filaments and prominences, uncovering their structure through spectropolarimetric observations and investigating their interaction with the underlying photosphere and chromosphere. Our systematic analysis of coronal bright points will clarify how these small-scale heating events contribute to the heating of the corona and how they are associated with small- scale chromospheric eruptions. The use of Bayesian model comparison techniques, will advance coronal seismology from parameter inference to evidence-based diagnostics. The scientific achievements will be complemented with the development of existing and new software tools for the simulation of physical processes and the diagnostics of magnetized plasmas.
