Deep-Learning-Based Inverse-Designed Millimeter-Wave Passives and Power Amplifie

Abstract

This work describes deep-learning-enabled inverse design of multi-port electromagnetic (EM) structures co-designed with circuits that can enable the synthesis of novel high-frequency on-chip passives and circuits with designer scattering parameters in a rapid and automated fashion. The design of EM structures for high-frequency circuits typically starts from a pre-selected topology of unit functional elements that are subsequently optimized for the desired scattering parameters through time- con