书目名称 | Nanophotonics and Machine Learning | 副标题 | Concepts, Fundamenta | 编辑 | Kan Yao,Yuebing Zheng | 视频video | | 概述 | Provides the first book-level coverage of intelligent nanophotonics.Presents the fundamental concepts of both photonics and machine learning in an accessible way.Summarizes applications to nanophotoni | 丛书名称 | Springer Series in Optical Sciences | 图书封面 |  | 描述 | .This book, the first of its kind, bridges the gap between the increasingly interlinked fields of nanophotonics and artificial intelligence (AI). While artificial intelligence techniques, machine learning in particular, have revolutionized many different areas of scientific research, nanophotonics holds a special position as it simultaneously benefits from AI-assisted device design whilst providing novel computing platforms for AI. This book is aimed at both researchers in nanophotonics who want to utilize AI techniques and researchers in the computing community in search of new photonics-based hardware. The book guides the reader through the general concepts and specific topics of relevance from both nanophotonics and AI, including optical antennas, metamaterials, metasurfaces, and other photonic devices on the one hand, and different machine learning paradigms and deep learning algorithms on the other. It goes on to comprehensively survey inverse techniques for device design, AI-enabled applications in nanophotonics, and nanophotonic platforms for AI. This book will be essential reading for graduate students, academic researchers, and industry professionals from either side of th | 出版日期 | Book 2023 | 关键词 | Intelligent nanophotonics; Machine learning for inverse design; Photonic neural network; All-optical ma | 版次 | 1 | doi | https://doi.org/10.1007/978-3-031-20473-9 | isbn_softcover | 978-3-031-20475-3 | isbn_ebook | 978-3-031-20473-9Series ISSN 0342-4111 Series E-ISSN 1556-1534 | issn_series | 0342-4111 | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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