SOMMA · Solar Magnetic Mapping: UV Spectropolarimetric Diagnostics from Photosphere to Transition Region

Understanding the magnetic field stratification throughout the solar atmosphere is imperative for characterizing the origin of solar activity and the physical processes that drive space weather. However, due to the impossibility of performing direct measurements, diagnosing the solar magnetic field remains a complex challenge, requiring continuous advancements in both observational techniques and theoretical modeling.The polarization of spectral lines formed in the solar atmosphere carries the imprint of the magnetic field via the Zeeman and Hanle effects. By analyzing their signatures on spectropolarimetric signals, it is possible to infer information about the magnetic field across different layers of the solar atmosphere.Recently, the CLASP2 and CLASP2.1 suborbital missions have demonstrated the diagnostic potential of ultraviolet spectropolarimetry for probing chromospheric magnetism. Their unprecedented observations enabled the most detailed mapping to date of the magnetic field stratification in active regions, while also validating the use of the Hanle effect to detect weak magnetic fields in quiet-Sun areas.The spectral window observed by the CLASP experiments includes the strong Mg II h & k resonance lines, whose cores encode information on the upper solar chromosphere, and several other weaker spectral lines. The polarization signals of these weaker lines carry complementary information on the magnetism of lower atmospheric regions, offering a unique opportunity to study magnetic coupling from the photosphere to the transition region. Regrettably, theoretical modeling of these lines has received little attention, limiting the exploitation of this spectral window’s diagnostic potential. This project aims to overcome this by improving our understanding of the formation of intensity and polarization signals in these lines. This will refine current diagnostic techniques and enable more accurate inferences of magnetic field from existing and future data.