Available on-demand - *S.EL09.06.04
Exploiting Phase Change Materials and Multi-Objective Optimization for Reconfigurable Multi-Functional Meta-Optics
Sawyer Campbell1,Yuhao Wu1,Eric Whiting1,Lei Kang1,Pingjuan Werner1,Douglas Werner1
The Pennsylvania State University1
Show Abstract
Phase change materials (PCMs) are an extremely attractive material platform for the realization of multi-functional and reconfigurable meta-optics. For example, PCMs can be exploited to synthesize metasurfaces and metamaterials to enable a variety of tunable devices such as beam-steerers, optical shutters, spectral filters, and adaptive focal length lenses [1]–[5]. However, the expanded degrees of design freedom that PCMs offer can make direct device design intractable for all but the most experienced engineers. This challenge is best overcome through the use of advanced inverse-design tools and state-of-the-art optimization algorithms. To this end, a number of successful meta-device inverse-design approaches have been demonstrated in the literature including those based on topology optimization, deep learning, and global optimization [6]. While each method has its pros and cons, one method stands out as an ideal candidate for reconfigurable meta-optic design: multi-objective optimization. In contrast to ubiquitous single-objective optimization algorithms, which require users to combine multiple goals into a single cost function usually via a weighted sum, true multi-objective optimization (MOO) algorithms allow designers to minimize multiple competing objectives simultaneously without the need for a priori information on how best to weight a single cost function [7], [8]. Thus, MOO algorithms are perfectly suited for reconfigurable meta-optic design as each independent functionality can be assigned a unique cost function and optimized. Moreover, MOO algorithms provide the user with a collection of designs called the Pareto set that can be analyzed to determine the inherent tradeoffs between competing design objectives. In our presentation, we will introduce an efficient multi-objective optimization enabled design framework for the generation of multi-functional unit cells based on phase change materials. Additionally, several reconfigurable meta-optic design examples will be presented, and future research directions discussed.
References
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