Material Optimization in Transverse Electromagnetic Scattering Applications

TL;DR

This paper presents an efficient algorithm for discrete material optimization in electromagnetic applications, combining analytic and global optimization techniques, with proven convergence and demonstrated effectiveness through numerical examples.

Contribution

It introduces a novel optimization algorithm that handles nonlinear parametrizations of material tensors with global convergence guarantees.

Findings

Efficient optimization of cloaking layers for nano-particles.

Successful identification of multiple materials with distinct optical properties.

Algorithm achieves high-quality solutions with reduced computation time.

Abstract

A class of algorithms for the solution of discrete material optimization problems in electromagnetic applications is discussed. The idea behind the algorithm is similar to that of the sequential programming. However, in each major iteration a model is established on the basis of an appropriately parametrized material tensor. The resulting nonlinear parametrization is treated on the level of the sub-problem, for which, globally optimal solutions can be computed due to the block separability of the model. Although global optimization of non-convex design problems is generally prohibitive, a well chosen combination of analytic solutions along with standard global optimization techniques leads to a very efficient algorithm for most relevant material parametrizations. A global convergence result for the overall algorithm is established. The effectiveness of the approach in terms of both computation time and solution quality is demonstrated by numerical examples, including the optimal design of cloaking layers for a nano-particle and the identification of multiple materials with different optical properties in a matrix.