Note to readers: The online lectures which serves as a companion to the book can be found in the following YouTube link.
This book is the third volume in the New Era Electronics lecture notes series, a compilation of volumes defining the important concepts tied to the electronics transition happening in the 21st century.
The material is adapted from a unique course that connects three diverse fields — statistical mechanics, neural networks and quantum computing — using the unifying concept of a state-space with 2N dimensions defined by N binary bits. First, the seminal concepts of statistical mechanics, developed to describe natural interacting systems, are described. Then, these concepts are connected to engineered interacting systems like Boltzmann Machines (BM), which are cleverly designed to solve problems in machine learning. Finally, we connect to engineered quantum systems, stressing the key role of quantum interference in distinguishing them from classical systems like BM.
Assuming only a basic background in differential equations and linear algebra, this book is accessible to broader audiences across its described topics, including students in physics, engineering and computing, as well as professionals working actively in the technical fields looking for a primer to unconventional computing.
Sample Chapter(s)
Chapter 1: Prologue
Contents:
- Prologue
- Statistical Mechanics
- Boltzmann Machines
- Transition Matrix
- Quantum Boltzmann Law
- Quantum Transition Matrix
Readership: Advanced undergraduate and graduate students, researchers and practitioners in the fields of machine learning, quantum computing and statistical physics.
"A wonderful journey from classical to quantum, elegantly bridged by p-bits! By introducing a layer of probability to classical bits, Datta provides a foundational entry point for understanding the intricacies of the quantum world. This volume by a giant in the field is a must-read, even if your focus isn't quantum, because p-bits themselves might revolutionize domain-specific classical computing."
Subhasish Mitra
William E Ayer Professor, Departments of Electrical Engineering and Computer Science, Stanford University
"Prof. Supriyo Datta is a pioneer in the recent resurgence of probabilistic computing, most notably in his approach of using intrinsically random physical devices to realize p-bit computers — with applications to invertible logic, combinatorial optimization, and machine learning. This book, based on his lectures, gives his unique take on the physics background needed to understand this growing field, as well as its connections with quantum computing."
Peter McMahon
Assistant Professor, Applied and Engineering Physics, Cornell University
"A new book by Supriyo Datta is always an opportunity to see one of the most creative minds in electronics in action. This new book does not disappoint. It connects the timely topics of machine learning and quantum computing to the principles of statistical mechanics, which have been known for more than 100 years. In less than 300 pages, readers will gain a comparative understanding of two of the most promising new approaches to computing."
Mark Lundstrom
Don and Carol Scifres Distinguished Professor of Electrical and Computer Engineering, Purdue University
"The prologue warns the reader that this book covers a spectrum of topics usually taught over many university courses — that is precisely what makes this book unique, timely, and exceptionally useful. It is written in a colloquial but precise style, making for engaging reading. It includes short quizzes, exercises, and summaries at the end of each chapter — an invaluable help for instruction."
Joao Hespanha
Distinguished Professor, University of California Santa Barbara
Supriyo Datta received his PhD from University of Illinois at Urbana-Champaign in 1979 working on surface acoustic wave devices, and has been with Purdue University since 1981. The non-equilibrium Green function (NEGF) method approach pioneered by his group for the description of quantum transport has been widely adopted in the field of nanoelectronics. He is also known for innovative theoretical proposals that have inspired new fields of research including negative capacitance devices, spintronics and p-bits. He is an elected member of both the US National Academy of Engineering (NAE) and the National Academy of Sciences (NAS).
Note to readers: The online lectures which serves as a companion to the book can be found in the following YouTube link.
Sample Chapter(s)
Chapter 1: Prologue
