TORCWA: GPU-accelerated Fourier modal method and gradient-based optimization for metasurface design

TORCWA is an electromagnetic wave simulation and optimization tool utilizing rigorous coupled-wave analysis. One of the advantages of TORCWA is that it provides GPU-accelerated simulation. It shows a greatly accelerated simulation speed compared to when the same simulation is performed on a CPU-based. Although it has accelerated speed, the simulation results are almost identical to the commercialized electromagnetic wave simulations. The second advantage is that it provides GPU-accelerated gradient calculation for the simulation results with reverse-mode automatic differentiation of PyTorch version 1.10.1. In particular, the instability of gradient calculation of eigendecomposition is also improved. With this property, TORCWA can be utilized for the optimization of various nanophotonic devices. Here, we first introduce the formulation used in TORCWA, compare it with other commercial simulations, and show the computational performance in multiple environments. Then, the gradient calculation and optimization examples are shown. Thanks to accelerated computational performance and gradient calculation, TORCWA is a worthy program for designing and optimizing various nanophotonic devices.TORCWA是一款采用严格耦合波分析（rigorous coupled-wave analysis）的电磁波模拟与优化工具。该工具的优势之一在于支持GPU加速模拟，相较于基于CPU的同类模拟，其模拟速度可实现大幅提升。尽管模拟速度显著提升，但其计算结果与商业化电磁波模拟软件的输出几乎完全一致。其二，该工具依托PyTorch 1.10.1版本的反向自动微分机制，可为模拟结果提供GPU加速的梯度计算，尤为关键的是，其还改善了本征分解的梯度计算不稳定性问题。依托这一特性，TORCWA可用于各类纳米光子器件的优化设计。本文首先介绍TORCWA所采用的建模公式，将其与其他商业化模拟工具进行对比，并在多种运行环境下展示其计算性能；随后将展示梯度计算与优化的相关示例。凭借出色的计算性能与梯度计算能力，TORCWA是一款适用于各类纳米光子器件设计与优化的优质工具。

搜集汇总

背景与挑战

背景概述

该数据集是TORCWA工具，一个用于超表面设计的电磁波仿真和优化程序。其关键特点包括利用GPU加速实现快速仿真，以及基于PyTorch的自动微分提供高效的梯度计算，从而支持纳米光子器件的优化设计。