Inferring atomic data from solar observations
Modeling of observed spectral line profiles relies on the chosen parameterization of the physical parameters, approximations employed to solve the radiative transfer equation, and atomic data. The implicit assumption in all inversions is that atomic data are correct and known well enough to provide reliable physical parameters. Using poor atomic data significantly hinders our inversion results, especially in the case of multi-line inversions. In this talk, I will talk about a method for a self-consistent inference of atmospheric and atomic parameters from spatially resolved multi-line observations. I will highlight the robustness of the method by applying it to observations from the GREGOR/GRIS at 1.56 microns. Additionally, I will show some preliminary results from an inversion of a SunriseIII/SUSI observation of the quiet-sun at 409nm.
Dusan completed his PhD at the Max Planck Institute for Solar System Research in Goettingen as part of the SunriseIII team working with Smitha Narayanamurthy, Andreas Lagg, and Sami Solanki. During his PhD, he developed an inversion method for inferring the atomic parameters from multi-line observations. Currently, he is a postdoc at the University of Graz, working within Alexander Shapiro’s group on mitigating the stellar activity from exoplanets’ radial velocity curves. His main research interests are the (non-)LTE radiative transfer modelling of spectral lines, spectropolarimetric inversions, stellar atmospheres, and numerical optimization.