Phase-Informed Discontinuous Galerkin Method for Extremely High-Frequency Wave Modeling

Two long-standing problems exist in the high-frequency electromagnetic scattering analysis: 1) full-wave methods suffer a geometric increase in computational costs, along with the rising frequencies and 2) ray tracing methods struggle to acquire sufficient phase information when dealing with complex targets. To address these two issues, we propose a phase-informed hybridizable discontinuous Galerkin (PI-HDG) method for extremely high-frequency modeling. Similar to the physics-informed machine learning algorithms, we integrate the prior knowledge of phase information into the basis-function construction in the PI-HDG algorithm, thus combining both strengths from the HDG method and geometric optics ansatz. Numerical experiments show that the PI-HDG algorithm can accurately compute high-frequency scattering characteristics of complex targets. Specifically, in a multiple scattering scenario, we achieve only 1/10 temporal consumption while 1/16 for the memory, when compared with the reference finite-element software.