UID:
almafu_9961047240602883
Format:
1 online resource (188 pages)
Edition:
First edition.
ISBN:
9783031204739
Series Statement:
Springer Series in Optical Sciences Series ; Volume 241
Content:
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 this fast-developing, interdisciplinary field.
Note:
Chapter1. Fundamentals of nanophotonics -- Chapter2. Nanophotonic devices and platforms. - Chapter3. Fundamentals of machine learning -- Chapter4. DL-assisted inverse design in nanophotonics -- Chapter5. DL-enabled applications in nanophotonics -- Chapter6. Nanophotonic and optical platforms for DL.
Additional Edition:
Print version: Yao, Kan Nanophotonics and Machine Learning Cham : Springer International Publishing AG,c2023 ISBN 9783031204722
Language:
English
DOI:
10.1007/978-3-031-20473-9
