旋转
纳米光子学
启发式
计算机科学
反向
最大值和最小值
建筑
灵活性(工程)
软件
计算科学
计算机体系结构
计算机工程
理论计算机科学
物理
数学
程序设计语言
光学
几何学
数学分析
艺术
视觉艺术
操作系统
统计
凝聚态物理
作者
Logan Su,Dries Vercruysse,Jinhie Skarda,Neil V. Sapra,Jan Petykiewicz,Jelena Vučković
出处
期刊:Cornell University - arXiv
日期:2019-01-01
标识
DOI:10.48550/arxiv.1910.04829
摘要
A computational nanophotonic design library for gradient-based optimization called SPINS is presented. Borrowing the concept of computational graphs, SPINS is a design framework that emphasizes flexibility and reproducible results. The mathematical and architectural details to achieve these goals are presented, and practical considerations and heuristics for using inverse design are discussed, including the choice of initial condition and the landscape of local minima.
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