Inverse Design of Multi-input Multi-output 2D Metastructured Devices

TL;DR

This paper introduces a computationally efficient inverse design method for complex 2D metastructured devices using a circuit network solver and gradient-based optimization, enabling practical design of large-scale MIMO metastructures.

Contribution

It presents a novel 2-D circuit network solver with reduced order models combined with an adjoint-based gradient optimization for designing large-scale MIMO metastructures.

Findings

Successfully designed a planar beamformer validated with full-wave simulations.

Developed an efficient inverse design process for electrically-large metastructures.

Validated the method with practical examples like an analog signal processor.

Abstract

In this work, an optimization-based inverse design method is provided for multi-input multi-output (MIMO) metastructured devices. Typically, optimization-based methods use a full-wave solver in conjunction with an optimization routine to design devices. Due to the computational cost this approach is not practical for designing electrically-large aperiodic metastructured devices. To address this issue, a 2-D circuit network solver using reduced order models of the metastructure's unit cells is introduced. The circuit network solver is used in conjunction with a gradient-based optimization routine that uses the adjoint variable method to solve large-scale optimization problems like those posed by metastructured devices. To validate the inverse design method, a planar beamformer and an analog signal processor for aperture field reconstruction are designed and validated with full-wave simulations.