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arXiv · 2112.07399

Metaplectic geometrical optics for ray-based modeling of caustics: Theory and algorithms

Abstract

The optimization of radiofrequency-wave (RF) systems for fusion experiments is often performed using ray-tracing codes, which rely on the geometrical-optics (GO) approximation. However, GO fails at caustics such as cutoffs and focal points, erroneously predicting the wave intensity to be infinite. This is a critical shortcoming of GO, since the caustic wave intensity is often the quantity of interest, e.g. RF heating. Full-wave modeling can be used instead, but the computational cost limits the speed at which such optimizations can be performed. We have developed a less expensive alternative called metaplectic geometrical optics (MGO). Instead of evolving waves in the usual $\textbf{x}$ (coordinate) or $\text{k}$ (spectral) representation, MGO uses a mixed $\textbf{X} \equiv \textsf{A}\textbf{x} + \textsf{B}\textbf{k}$ representation. By continuously adjusting the matrix coefficients $\textsf{A}$ and $\textsf{B}$ along the rays, one can ensure that GO remains valid in the $\textbf{X}$ coordinates without caustic singularities. The caustic-free result is then mapped back onto the original $\textbf{x}$ space using metaplectic transforms. Here, we overview the MGO theory and review algorithms that will aid the development of an MGO-based ray-tracing code. We show how using orthosymplectic transformations leads to considerable simplifications compared to previously published MGO formulas. We also prove explicitly that MGO exactly reproduces standard GO when evaluated far from caustics (an important property which until now has only been inferred from numerical simulations), and we relate MGO to other semiclassical caustic-removal schemes published in the literature. This discussion is then augmented by an explicit comparison of the computed spectrum for a wave bounded between two cutoffs.

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BibTeXRIS

N. A. Lopez, I. Y. Dodin. 2022-05-10. Metaplectic geometrical optics for ray-based modeling of caustics: Theory and algorithms. https://doi.org/10.1063/5.0082241

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