Nanophotonic devices based on optimization algorithms

Cuicui Lu, Hongyi Yuan, Nianen Zhang

科研成果: 书/报告/会议事项章节章节同行评审

1 引用 (Scopus)

摘要

Nanophotonic devices, which take photons as information carriers, are the essential components for photonic chips, and play a key role in optical computing, optical interconnection, and optical networks. However, most of the traditional methods that rely on human experience and physical inspiration for structural design and parameter optimization, usually require many resources, and the performance of the designed device is limited. Compared with the previous numerical methods, optimization algorithms can help us to find the best pattern, improve efficiency, and save time. The design of nanophotonic devices based on optimization algorithms can break the restrictions of traditional methods and predict new configurations, which is universal and efficient for different materials, different structures, different modes, and different wavelengths. In this chapter, we introduce the typical nanophotonic devices based on the optimization algorithms from physical concepts to their applications. Here, the algorithms used to design nanophotonic structures are divided into two main types, gradient-based and heuristic. Gradient-based algorithms used in the nanophotonic design include topology optimization, objective-first algorithm, and other gradient-based optimization algorithms. Heuristic algorithms can be regarded as gradient-independent algorithms, which generate new solutions with different strategies based on randomness but not gradients information. Heuristic algorithms can be further classified into two kinds, the individual-based and the population-based. The typical optimization algorithms will be illustrated in this chapter according to the related reports and our research experiences, which can bring inspiration for the efficient design of photonic devices.

源语言英语
主期刊名Intelligent Nanotechnology
主期刊副标题Merging Nanoscience and Artificial Intelligence
出版商Elsevier
71-111
页数41
ISBN(电子版)9780323857963
ISBN(印刷版)9780323901413
DOI
出版状态已出版 - 1 1月 2022

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