POViT: Vision Transformer for Multi-Objective Design and Characterization of Photonic Crystal Nanocavities.

ABSTRACT: We study a new technique for solving the fundamental challenge in nanophotonic design: fast and accurate characterization of nanoscale photonic devices with minimal human intervention. Much like the fusion between Artificial Intelligence and Electronic Design Automation (EDA), many efforts have been made to apply deep neural networks (DNN) such as convolutional neural networks to prototype and characterize next-gen optoelectronic devices commonly found in Photonic Integrated Circuits. However, state-of-the-art DNN models are still far from being directly applicable in the real world: e.g., DNN-produced correlation coefficients between target and predicted physical quantities are about 80%, which is much lower than what it takes to generate reliable and reproducible nanophotonic designs. Re

SUBMITTER: Chen X 

PROVIDER: S-EPMC9784978 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature