Machine Learning for the Free Form Inverse Design in Nanophotonics PDF Download
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Author: Timo Gahlmann
Publisher:
ISBN: 9789179059347
Category : Machine learning
Languages : en
Pages : 0
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Book Description
Author: Timo Gahlmann
Publisher:
ISBN: 9789179059347
Category : Machine learning
Languages : en
Pages : 0
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Book Description
Author: Kan Yao
Publisher: Springer Nature
ISBN: 3031204735
Category : Science
Languages : en
Pages : 189
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Book Description
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.
Author: Peng Yu
Publisher: John Wiley & Sons
ISBN: 3527833048
Category : Technology & Engineering
Languages : en
Pages : 389
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Book Description
Integrated Nanophotonics Helps readers understand the important advances in nanophotonics materials development and their latest applications This book introduces the current state of and emerging trends in the development of integrated nanophotonics. Written by three well-qualified authors, it systematically reviews the knowledge of integrated nanophotonics from theory to the most recent technological developments. It also covers the applications of integrated nanophotonics in essential areas such as neuromorphic computing, biosensing, and optical communications. Lastly, it brings together the latest advancements in the key principles of photonic integrated circuits, plus the recent advances in tackling the barriers in photonic integrated circuits. Sample topics included in this comprehensive resource include: Platforms for integrated nanophotonics, including lithium niobate nanophotonics, indium phosphide nanophotonics, silicon nanophotonics, and nonlinear optics for integrated photonics The devices and technologies for integrated nanophotonics in on-chip light sources, optical packaging of photonic integrated circuits, optical interconnects, and light processing devices Applications on neuromorphic computing, biosensing, LIDAR, and computing for AI and artificial neural network and deep learning Materials scientists, physicists, and physical chemists can use this book to understand the totality of cutting-edge theory, research, and applications in the field of integrated nanophotonics.
Author: Federico Capasso
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110710684
Category : Technology & Engineering
Languages : en
Pages : 783
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Book Description
This book provides a cutting-edge research overview on the latest developments in the field of Optics and Photonics. All chapters are authored by the pioneers in their field and will cover the developments in Quantum Photonics, Optical properties of 2D Materials, Optical Sensors, Organic Opto-electronics, Nanophotonics, Metamaterials, Plasmonics, Quantum Cascade lasers, LEDs, Biophotonics and biomedical photonics and spectroscopy.
Author: Stefan Alexander Maier
Publisher: Springer Science & Business Media
ISBN: 0387378251
Category : Technology & Engineering
Languages : en
Pages : 234
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Book Description
Considered a major field of photonics, plasmonics offers the potential to confine and guide light below the diffraction limit and promises a new generation of highly miniaturized photonic devices. This book combines a comprehensive introduction with an extensive overview of the current state of the art. Coverage includes plasmon waveguides, cavities for field-enhancement, nonlinear processes and the emerging field of active plasmonics studying interactions of surface plasmons with active media.
Author: Paul R. Prucnal
Publisher: CRC Press
ISBN: 1498725244
Category : Science
Languages : en
Pages : 412
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Book Description
This book sets out to build bridges between the domains of photonic device physics and neural networks, providing a comprehensive overview of the emerging field of "neuromorphic photonics." It includes a thorough discussion of evolution of neuromorphic photonics from the advent of fiber-optic neurons to today’s state-of-the-art integrated laser neurons, which are a current focus of international research. Neuromorphic Photonics explores candidate interconnection architectures and devices for integrated neuromorphic networks, along with key functionality such as learning. It is written at a level accessible to graduate students, while also intending to serve as a comprehensive reference for experts in the field.
Author: Q. J. Zhang
Publisher: Artech House Publishers
ISBN:
Category : Computers
Languages : en
Pages : 396
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Book Description
Discover the new, unconventional alternatives for conquering RF and microwave design and modeling problems using neural networks -- information processing systems that can learn, generalize, and even allow model development when component formulas are missing -- with this book and software package. It shows you the ease of creating models with neural networks, and how quick model evaluation can be done, plus other opportunities presented by neural networks for conquering the toughest RF and microwave CAD problems.
Author: Sawyer D. Campbell
Publisher: John Wiley & Sons
ISBN: 1119853893
Category : Technology & Engineering
Languages : en
Pages : 596
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Book Description
Authoritative reference on the state of the art in the field with additional coverage of important foundational concepts Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning presents cutting-edge research advances in the rapidly growing areas in optical and RF electromagnetic device modeling, simulation, and inverse-design. The text provides a comprehensive treatment of the field on subjects ranging from fundamental theoretical principles and new technological developments to state-of-the-art device design, as well as examples encompassing a wide range of related sub-areas. The content of the book covers all-dielectric and metallodielectric optical metasurface deep learning-accelerated inverse-design, deep neural networks for inverse scattering, applications of deep learning for advanced antenna design, and other related topics. To aid in reader comprehension, each chapter contains 10-15 illustrations, including prototype photos, line graphs, and electric field plots. Contributed to by leading research groups in the field, sample topics covered in Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning include: Optical and photonic design, including generative machine learning for photonic design and inverse design of electromagnetic systems RF and antenna design, including artificial neural networks for parametric electromagnetic modeling and optimization and analysis of uniform and non-uniform antenna arrays Inverse scattering, target classification, and other applications, including deep learning for high contrast inverse scattering of electrically large structures Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning is a must-have resource on the topic for university faculty, graduate students, and engineers within the fields of electromagnetics, wireless communications, antenna/RF design, and photonics, as well as researchers at large defense contractors and government laboratories.
Author: Qiang Ren
Publisher: Springer Nature
ISBN: 9811662614
Category : Technology & Engineering
Languages : en
Pages : 137
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Book Description
This book investigates in detail the deep learning (DL) techniques in electromagnetic (EM) near-field scattering problems, assessing its potential to replace traditional numerical solvers in real-time forecast scenarios. Studies on EM scattering problems have attracted researchers in various fields, such as antenna design, geophysical exploration and remote sensing. Pursuing a holistic perspective, the book introduces the whole workflow in utilizing the DL framework to solve the scattering problems. To achieve precise approximation, medium-scale data sets are sufficient in training the proposed model. As a result, the fully trained framework can realize three orders of magnitude faster than the conventional FDFD solver. It is worth noting that the 2D and 3D scatterers in the scheme can be either lossless medium or metal, allowing the model to be more applicable. This book is intended for graduate students who are interested in deep learning with computational electromagnetics, professional practitioners working on EM scattering, or other corresponding researchers.
Author: Marco Wiering
Publisher: Springer Science & Business Media
ISBN: 3642276458
Category : Technology & Engineering
Languages : en
Pages : 653
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Book Description
Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade. The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together they truly represent a state-of-the-art of current reinforcement learning research. Marco Wiering works at the artificial intelligence department of the University of Groningen in the Netherlands. He has published extensively on various reinforcement learning topics. Martijn van Otterlo works in the cognitive artificial intelligence group at the Radboud University Nijmegen in The Netherlands. He has mainly focused on expressive knowledge representation in reinforcement learning settings.
