Modelling Gyrosynchrotron Emission from Energetic Electrons in the Solar Corona

The Sun is a prominent source of radio emission due to its proximity and solar activity. The most violent solar eruptive events, solar flares and coronal mass ejections (CMEs), can accelerate electrons, producing radio emissions often observed as bursts classified into different types. In particular, type IV radio bursts, which are routinely observed by the Parker Solar Probe (PSP), are associated with CMEs and electrons trapped within strong coronal magnetic fields. The distinct spectral and temporal features exhibited by these bursts enable inferences about the dynamics of CMEs and properties of the energetic particles. While spacecraft such as PSP provide valuable in-situ data supporting analysis of remotely obtained radio spectra, physics-based numerical models play a crucial role in enhancing our understanding of the mechanisms driving radio emissions.

In this talk, we present a novel coupling of three numerical models to simulate gyrosynchrotron (GS) emission from energetic electrons deep in the solar corona. Using the data-driven magnetohydrodynamic (MHD) coronal model COCONUT, we solve the 3D ideal MHD equations to derive coronal background configurations from 1 to 21.5 solar radii, including a CME modelled as a Titov–Démoulin flux rope. Subsequently, we utilise the particle transport code PARADISE to propagate energetic electrons as test particles through the MHD snapshots by solving the focused transport equation stochastically, obtaining spatio-temporal electron intensities. Finally, we use the solar wind parameters from COCONUT and the electron energy and pitch angle distributions from PARADISE as input to the Ultimate Fast GS Code (Kuznetsov and Fleishman, 2021), which computes emission and absorption coefficients that can be integrated along a line of sight to obtain radio spectra directly comparable to spacecraft measurements. This coupled approach illustrates how varying electron injection spectra and CME properties affect the observed radio spectra, offering insights into the energetic particles and CMEs. Furthermore, we highlight the potential of our model in future studies incorporating observational data.