Mg II h&k fine structure prominence modelling and the consequences for observations

¹ University of Wrocław, Centre of Scientific Excellence – Solar and Stellar Activity, Kopernika 11, 51-622 Wrocław, Poland
e-mail: aaron.peat@uwr.edu.pl
² SUPA School of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ, UK
³ Université Paris-Saclay, CNRS, Institut d’Astrophysique Spatiale, 91405 Orsay, France

Received: 20 June 2023
Accepted: 22 September 2023

Abstract

Aims. Using 2D Mg II h&k solar prominence modelling, our aim is to understand the formation of complex line profiles and how these are seen by the Interface Region Imaging Spectrograph (IRIS). Additionally, we see how the properties of these simulated observations are interpreted through the use of traditional 1D prominence modelling.

Methods. We used a cylindrical non-local thermodynamic equilibrium (NLTE) 2D complete redistribution (CRD) code to generate a set of cylindrical prominence strands, which we stacked behind each other to produce complex line profiles. Then, with the use of the point spread functions (PSFs) of IRIS, we were able to predict how IRIS would observe these line profiles. We then used the 1D NLTE code PROM in combination with the Cross Root Mean Square method (xRMS) to find the properties recovered by traditional 1D prominence modelling.

Results. Velocities of magnitude lower than 10 km s⁻¹ are sufficient to produce asymmetries in the Mg II h&k lines. However, convolution of these with the PSFs of IRIS obscures this detail and returns standard looking single peaks. By increasing the velocities by a factor of three, we recover asymmetric profiles even after this convolution. The properties recovered by xRMS appear adequate at first, but the line profiles chosen to fit these profiles do not satisfactorily represent the line profiles. This is likely due to the large line width of the simulated profiles.

Conclusions. Asymmetries can be introduced by multithread models with independent Doppler velocities. The large line width created by these models makes it difficult for traditional 1D forward modelling to find good matches. This may also demonstrate degeneracies in the solution recovered by single-species 1D modelling.