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.
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.
Key Features:
- Unique both in its content connecting three advanced topics, and in requiring no advanced prerequisites beyond linear algebra and differential equations
- Offers a smooth but rigorous introduction to quantum computing concepts ideal for first forays into the field
- Modular and structured in lectures, enabling readers to pick up where they left off easily
