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Neuromorphic Photonics by Paul R. Prucnal,Bhavin J. Shastri Pdf
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.
Neuromorphic Photonic Devices and Applications by Min Gu,Elena Goi,Yangyundou Wang,Zhengfen Wan,Yibo Dong,Yuchao Zhang,Haoyi Yu Pdf
Neuromorphic Photonic Devices and Applications synthesizes the most critical advances in photonic neuromorphic models, photonic material platforms and accelerators for neuromorphic computing. The book discusses fields and applications that can leverage these new platforms. A brief review of the historical development of the field is followed by a discussion of the emerging 2D photonic materials platforms and recent work in implementing neuromorphic models and 3D neuromorphic systems. The application of artificial intelligence (AI), such as neuromorphic models to inverse design neuromorphic materials and devices and predict performance challenges is discussed throughout. Finally, a comprehensive overview of the applications of neuromorphic photonic technologies and the challenges, opportunities and future prospects is discussed, making the book suitable for researchers and practitioners in academia and R&D in the multidisciplinary field of photonics. Includes overview of primary scientific concepts for the research topic of neuromorphic photonics such as neurons as computational units, artificial intelligence, machine learning and neuromorphic models Reviews the latest advances in photonic materials, device platforms and enabling technology drivers of neuromorphic photonics Discusses potential applications in computing and optical communications
"As societys appetite for information continues to grow, so does our need to process this information with increasing speed and versatility. Conventional one-size-fits-all solutions offered by digital electronics can no longer satisfy this need, as Moores law, interconnection density, and the von Neumann architecture reach their limits. These limitations are already being felt in advanced applications such as cognitive radio, adaptive control, and scientific computing. With its superior speed and reconfigurability, analog photonics can provide some relief to these problems; however, complex applications of analog photonics have remained largely unexplored due to the absence of a robust photonic integration industry. Recently, the landscape for commercially-manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. Despite the advent of commercially-viable photonic integration platforms, significant challenges still remain before scalable analog photonic processors can be realized. A central challenge is the development of mathematical bridges linking photonic device physics to models of complex analog information processing. Among such models, those of neural networks are perhaps the most widely studied and used by engineering communities. 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 todays 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."--Provided by publisher.
Programmable Integrated Photonics by José Capmany,Daniel Pérez Pdf
This book provides the first comprehensive, up-to-date and self-contained introduction to the emergent field of Programmable Integrated Photonics (PIP). It covers both theoretical and practical aspects, ranging from basic technologies and the building of photonic component blocks, to design alternatives and principles of complex programmable photonic circuits, their limiting factors, techniques for characterization and performance monitoring/control, and their salient applications both in the classical as well as in the quantum information fields. The book concentrates and focuses mainly on the distinctive features of programmable photonics, as compared to more traditional ASPIC approaches. After some years during which the Application Specific Photonic Integrated Circuit (ASPIC) paradigm completely dominated the field of integrated optics, there has been an increasing interest in PIP. The rising interest in PIP is justified by the surge in a number of emerging applications that call for true flexibility and reconfigurability, as well as low-cost, compact, and low-power consuming devices. Programmable Integrated Photonics is a new paradigm that aims at designing common integrated optical hardware configurations, which by suitable programming, can implement a variety of functionalities. These in turn can be exploited as basic operations in many application fields. Programmability enables, by means of external control signals, both chip reconfiguration for multifunction operation, as well as chip stabilization against non-ideal operations due to fluctuations in environmental conditions and fabrication errors. Programming also allows for the activation of parts of the chip, which are not essential for the implementation of a given functionality, but can be of help in reducing noise levels through the diversion of undesired reflections.
Silicon Photonics IV by David J. Lockwood,Lorenzo Pavesi Pdf
This fourth book in the series Silicon Photonics gathers together reviews of recent advances in the field of silicon photonics that go beyond already established and applied concepts in this technology. The field of research and development in silicon photonics has moved beyond improvements of integrated circuits fabricated with complementary metal–oxide–semiconductor (CMOS) technology to applications in engineering, physics, chemistry, materials science, biology, and medicine. The chapters provided in this book by experts in their fields thus cover not only new research into the highly desired goal of light production in Group IV materials, but also new measurement regimes and novel technologies, particularly in information processing and telecommunication. The book is suited for graduate students, established scientists, and research engineers who want to update their knowledge in these new topics.
Silicon Photonics for High-Performance Computing and Beyond by Mahdi Nikdast,Sudeep Pasricha,Gabriela Nicolescu,Ashkan Seyedi,Di Liang Pdf
Silicon photonics is beginning to play an important role in driving innovations in communication and computation for an increasing number of applications, from health care and biomedical sensors to autonomous driving, datacenter networking, and security. In recent years, there has been a significant amount of effort in industry and academia to innovate, design, develop, analyze, optimize, and fabricate systems employing silicon photonics, shaping the future of not only Datacom and telecom technology but also high-performance computing and emerging computing paradigms, such as optical computing and artificial intelligence. Different from existing books in this area, Silicon Photonics for High-Performance Computing and Beyond presents a comprehensive overview of the current state-of-the-art technology and research achievements in applying silicon photonics for communication and computation. It focuses on various design, development, and integration challenges, reviews the latest advances spanning materials, devices, circuits, systems, and applications. Technical topics discussed in the book include: • Requirements and the latest advances in high-performance computing systems • Device- and system-level challenges and latest improvements to deploy silicon photonics in computing systems • Novel design solutions and design automation techniques for silicon photonic integrated circuits • Novel materials, devices, and photonic integrated circuits on silicon • Emerging computing technologies and applications based on silicon photonics Silicon Photonics for High-Performance Computing and Beyond presents a compilation of 19 outstanding contributions from academic and industry pioneers in the field. The selected contributions present insightful discussions and innovative approaches to understand current and future bottlenecks in high-performance computing systems and traditional computing platforms, and the promise of silicon photonics to address those challenges. It is ideal for researchers and engineers working in the photonics, electrical, and computer engineering industries as well as academic researchers and graduate students (M.S. and Ph.D.) in computer science and engineering, electronic and electrical engineering, applied physics, photonics, and optics.
Daniel Brunner,Miguel C. Soriano,Guy Van der Sande
Author : Daniel Brunner,Miguel C. Soriano,Guy Van der Sande Publisher : Walter de Gruyter GmbH & Co KG Page : 391 pages File Size : 46,6 Mb Release : 2019-07-08 Category : Science ISBN : 9783110582116
Photonic Reservoir Computing by Daniel Brunner,Miguel C. Soriano,Guy Van der Sande Pdf
Photonics has long been considered an attractive substrate for next generation implementations of machine-learning concepts. Reservoir Computing tremendously facilitated the realization of recurrent neural networks in analogue hardware. This concept exploits the properties of complex nonlinear dynamical systems, giving rise to photonic reservoirs implemented by semiconductor lasers, telecommunication modulators and integrated photonic chips.
Phase Change Materials-Based Photonic Computing by Harish Bhaskaran,Wolfram Pernice Pdf
Phase Change Materials-Based Photonic Computing provides a clear introduction to the field, introducing concepts of photonics, computing, phase change materials and future outlooks. Phase change materials are well known and studied in many contexts, and photonics is a longstanding field, with photonic neuromorphic computing recently gathering interest. However, the two fields are disparate and few people understand the key concepts needed to integrate the two. This book will be the first to do so in this promising field. It is suitable for researchers and practitioners in academia and industry working in the disciplines of materials science and engineering, electrical engineering and computing. Introduces the advanced fundamental concepts of photonics computing and phase change materials, including brief video lectures to accompany each chapter Reviews the remaining challenges to translation, opportunities and future outlooks Addresses definitions, historical context, foundational concepts and the latest advances of phase change materials-based photonics computing
This book represents a unique collection of the latest developments in the rapidly developing world of optoelectronics. The contributing authors to this book are a group of internationally distinguished researchers. This book consists of a collection of chapters divided into two sections, with the first section covering new applications and the second section covering materials and crystal structures topics to support future generations of optoelectronic devices and open the door for future, more demanding applications. This collection of chapters will be of considerable interest to scientists, engineers, physicists, and technologists working in research and development in the fields of optoelectronics and photonics, as well as to young researchers who are at the beginning of their career.
VLSI and Hardware Implementations using Modern Machine Learning Methods by Sandeep Saini,Kusum Lata,G.R. Sinha Pdf
Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques. Features: Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.
Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning by Sawyer D. Campbell,Douglas H. Werner Pdf
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.
This book delves into optics and photonic materials, describing the development of an intelligent all-optical system capable of replicating the functional building blocks of the biological brain. Starting with an analysis of biological neuronal dynamics and traversing the state of the art of neuromorphic systems developed to date, the book arrives at a description of neural networks realized through spatial soliton technology. After a brief introduction to the biology of neural networks (Chapter 1), the book delves into the description of the neuromorphic problem emphasizing the peculiarities of optical hardware developed to date. (Chapter 2). Chapter 3 is dedicated to the description of psychomemories , which represent the modeling of human learning according to the theories of modern neuro-psychology. This chapter provides the prerequisites for understanding how solitonic neural networks (SNNs) are able to learn and how they approach biological models. Chapter 4 focuses on the experimentation of solitonic optic neurons in thin layers of lithium niobate. Optical techniques for supervised and unsupervised learning are discussed. The entire chapter is accompanied by theoretical, simulative and experimental results. This chapter explains how an X-junction neuron is able to establish synapses, modify them, or erase them. The erasure of solitonic structures represents an important innovation in the field of nonlinear optics. Finally, Chapter 5 reports on the implementation of a network of neurons capable of processing information and storing it exactly as a human episodic memory does. The chapter ends with a number of insights into the lines of research that are currently being pursued on the basis of the results obtained. The book is meant for graduate students and researchers in the fields of optics, photonic applications, and biology. However, the main beneficiaries of this book are senior researchers in the field of nonlinear optics and artificial intelligence. To fully understand the results, it is important to have a basic knowledge of optical physics and neuron biology.
Nanophotonic Information Physics by Makoto Naruse Pdf
This book provides a new direction in the field of nano-optics and nanophotonics from information and computing-related sciences and technology. Entitled by "Information Physics and Computing in NanosScale Photonics and Materials”, IPCN in short, the book aims to bring together recent progresses in the intersection of nano-scale photonics, information, and enabling technologies. The topic will include (1) an overview of information physics in nanophotonics, (2) DNA self-assembled nanophotonic systems, (3) Functional molecular sensing, (4) Smart fold computing, an architecture for nanophotonics, (5) semiconductor nanowire and its photonic applications, (6) single photoelectron manipulation in imaging sensors, (6) hierarchical nanophotonic systems, (8) photonic neuromorphic computing, and (9) SAT solver and decision making based on nanophotonics.
Resonant Tunneling Diode Photonics by Charlie Ironside,Bruno Romeira,José Figueiredo Pdf
This book brings together two broad themes that have generated a great deal of interest and excitement in the scientific and technical community in the last 100 years or so: quantum tunnelling and nonlinear dynamical systems. It applies these themes to nanostructured solid state heterostructures operating at room temperature to gain insight into novel photonic devices, systems and applications.
Semiconductor Laser Diode by Dnyaneshwar Shaligram Patil Pdf
This book represents a unique collection of the latest developments in the rapidly developing world of semiconductor laser diode technology and applications. An international group of distinguished contributors have covered particular aspects and the book includes optimization of semiconductor laser diode parameters for fascinating applications. This collection of chapters will be of considerable interest to engineers, scientists, technologists and physicists working in research and development in the field of semiconductor laser diode, as well as to young researchers who are at the beginning of their career.
