Stochastic optimization of low-loss optical negative-index metamaterial

Alexander V. Kildishev, Birck Nanotechnology Center, Purdue University
Uday K. Chettiar, Purdue University
Zhengtong Liu, Purdue University
V. M. Shalaev, Birck Nanotechnology Center and School of Electrical and Computer Engineering, Purdue University
Do-Hoon Kwon, Department of Electrical Engineering, Pennsylvania State University
Zikri Bayraktar, Department of Electrical Engineering, Pennsylvania State University
Douglas H. Werner, Department of Electrical Engineering, Pennsylvania State University

Abstract

Optical metamaterial consisting of metal-dielectric composites creates a complicated system that is not amenable to analytical solutions. This presents a challenge in optimizing these intricate systems. We present the application of three nature-inspired stochastic optimization techniques in conjunction with fast numerical electromagnetic solvers to yield a metamaterial that satisfies a required design criterion. In particular, three stochastic optimization tools (genetic algorithm, particle swarm optimization, and simulated annealing) are used for designing a low-loss optical negative index metamaterial. A negative refractive index around -0.8+0.2i is obtained at a wavelength of 770 nm. The particle swarm optimization algorithm is found to be the most efficient in this case.