Extracting information from the data flood of new solar telescopes. Brainstorming
A. Asensio Ramos (IAC)

TL;DR
This paper discusses the challenges and proposes potential methods for efficiently extracting magnetic and thermodynamic information from the large volumes of spectropolarimetric data generated by upcoming large solar telescopes.
Contribution
It introduces several innovative approaches aimed at speeding up the inference process for solar plasma properties from spectropolarimetric observations.
Findings
Proposed methods could significantly reduce data analysis time.
New approaches may improve the accuracy of magnetic field measurements.
Frameworks suggested are adaptable to future large datasets.
Abstract
Extracting magnetic and thermodynamic information from spectropolarimetric observations is a difficult and time consuming task. The amount of science-ready data that will be generated by the new family of large solar telescopes is so large that we will be forced to modify the present approach to inference. In this contribution, I propose several possible ways that might be useful for extracting the thermodynamic and magnetic properties of solar plasmas from such observations quickly.
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Taxonomy
TopicsGaussian Processes and Bayesian Inference · Solar and Space Plasma Dynamics · Scientific Research and Discoveries
