Multifunctional Metasurface Design with a Generative Adversarial Network

TL;DR

This paper introduces a GAN-based method for rapid, on-demand design of multifunctional metasurfaces, overcoming traditional trial-and-error approaches and enabling diverse electromagnetic functionalities with a single iteration.

Contribution

The paper presents a novel GAN framework that efficiently generates metasurface designs for multiple functions, independent of design complexity and accommodating fabrication constraints.

Findings

Successfully designed bifocal metalens and polarization-multiplexed devices

Achieved rapid, single-iteration metasurface design process

Demonstrated versatility in multifunctional electromagnetic responses

Abstract

Metasurfaces have enabled precise electromagnetic wave manipulation with strong potential to obtain unprecedented functionalities and multifunctional behavior in flat optical devices. These advantages in precision and functionality come at the cost of tremendous difficulty in finding individual meta-atom structures based on specific requirements (commonly formulated in terms of electromagnetic responses), which makes the design of multifunctional metasurfaces a key challenge in this field. In this paper, we present a Generative Adversarial Networks (GAN) that can tackle this problem and generate meta-atom/metasurface designs to meet multifunctional design goals. Unlike conventional trial-and-error or iterative optimization design methods, this new methodology produces on-demand free-form structures involving only a single design iteration. More importantly, the network structure and the robust training process are independent of the complexity of design objectives, making this approach ideal for multifunctional device design. Additionally, the ability of the network to generate distinct classes of structures with similar electromagnetic responses but different physical features could provide added latitude to accommodate other considerations such as fabrication constraints and tolerances. We demonstrate the network's ability to produce a variety of multifunctional metasurface designs by presenting a bifocal metalens, a polarization-multiplexed beam deflector, a polarization-multiplexed metalens and a polarization-independent metalens.