Parametric dependence of microwave beam broadening by plasma density turbulence

High-power microwave beams used for heating and current drive in magnetically confined fusion plasmas can be broadened significantly by plasma turbulence, negatively impacting the efficiency of the machine. The dependence of this beam broadening on plasma and beam parameters is not yet fully understood, particularly where the dependence on one parameter is not separable from the dependence on the other parameters, meaning the dependence must be expressed via functions of linear combinations of parameters, rather than functions of single parameters. The aim of this work is to develop an empirical model for how the broadening depends on plasma and beam parameters, allowing for the easy estimation of beam broadening by turbulence without the need for computationally expensive full-wave simulations. In this paper, a microwave beam is simulated propagating through a turbulent layer of plasma using the 2D full-wave cold plasma code EMIT-2D. The dependence of beam broadening on background plasma density, fluctuation amplitude, turbulence correlation lengths in the radial and poloidal direction, thickness of the turbulence layer, and microwave beam waist are considered. The parameter scans are conducted in pairwise combinations of the parameters in order to determine the separability of the dependencies. We find that the dependence on the radial and poloidal correlation lengths are not separable from each other, and neither are the dependences on the fluctuation level and the background density, but all other dependencies are separable. Ignoring this inseparability in the correlation lengths will usually result in an over-prediction of the broadening in tokamak plasmas. An empirical formula for the beam broadening based on the turbulence and beam parameters is found for fusion-relevant scenarios, making prediction of the effect possible in microseconds, instead of the hours required for full-wave simulation. This could then be of use for integrated modelling of heating and current drive systems.