An Introduction to Information Processing provides an informal introduction to the computer field. This book introduces computer hardware, which is the actual computing equipment. Organized into three parts encompassing 12 chapters, this book begins with an overview of the evolution of personal computing and includes detailed case studies on two of the most essential personal computers for the 1980s, namely, the IBM Personal Computer and Apple's Macintosh. This text then traces the evolution of modern computing systems from the earliest mechanical calculating devices to microchips. Other chapters consider the components and operation of typical data communications systems. This book discusses as well the various types of communications networks and communications via space satellites. The final chapter deals with software or computer programs, the sets of instructions that programmers write to inform the computer how to solve particular problems. This book is a valuable resource for computer specialists, mathematicians, and computer programmers.

Human Information Processing: An Introduction to Psychology, Second Edition, was written to reflect recent developments, as well as anticipate new directions, in this flourishing field. The ideas of human information processing are relevant to all human activities, most especially those of human interactions. The book discusses all the traditional areas and then goes beyond: consciousness, states of awareness, multiple levels of processing (and of awareness), interpersonal communication, emotion, and stress. The book begins with an introduction to some of the more interesting phenomena of perception and poses some of the puzzles faced by those who would attempt to unravel the structures. Separate chapters cover the systems of most interest for human communication: the visual system and the auditory system; the structure of the nervous system; and the systems of memory: sensory information storage, short-term memory, and long-term memory. Subsequent chapters deal with the different aspects of memory, including show how memory is used in thought, in language, and in decision making. Also examined are the neurological basis of memory and the representation of knowledge within memory.

First published in 1979. Basic research, at its essence, is exploration of the unknown. When it is successful, isolated pieces of reality are deciphered and described. Most of the history of an empirical discipline consists of probes into this darkness-some bold, others careful and systematic. Most of these efforts are initially incorrect. At best, they are distant approximations to a reality that may not be correctly specified for centuries. How, then, can we describe the fragmented knowledge that characterizes a scientific discipline for most of its history? A dynamic field of science is held together by its paradigm. The author’s think it is essential to adequate scientific education to teach paradigms, and believe that there is an effective method. The method emphasizes the integral nature, rather than the objective correctness, of a given set of consensual commitments. They believe that paradigmatic content can be effectively combined with the technical research literature commonly presented in scientific texts. This book represents the culmination of those beliefs.

Quantum information processing offers fundamental improvements over classical information processing, such as computing power, secure communication, and high-precision measurements. However, the best way to create practical devices is not yet known. This textbook describes the techniques that are likely to be used in implementing optical quantum information processors. After developing the fundamental concepts in quantum optics and quantum information theory, the book shows how optical systems can be used to build quantum computers according to the most recent ideas. It discusses implementations based on single photons and linear optics, optically controlled atoms and solid-state systems, atomic ensembles, and optical continuous variables. This book is ideal for graduate students beginning research in optical quantum information processing. It presents the most important techniques of the field using worked examples and over 120 exercises.

Recent advances in the area of lifted inference, which exploits the structure inherent in relational probabilistic models. Statistical relational AI (StaRAI) studies the integration of reasoning under uncertainty with reasoning about individuals and relations. The representations used are often called relational probabilistic models. Lifted inference is about how to exploit the structure inherent in relational probabilistic models, either in the way they are expressed or by extracting structure from observations. This book covers recent significant advances in the area of lifted inference, providing a unifying introduction to this very active field. After providing necessary background on probabilistic graphical models, relational probabilistic models, and learning inside these models, the book turns to lifted inference, first covering exact inference and then approximate inference. In addition, the book considers the theory of liftability and acting in relational domains, which allows the connection of learning and reasoning in relational domains.

This new edition of a well-received textbook provides a concise introduction to both the theoretical and experimental aspects of quantum information at the graduate level. While the previous edition focused on theory, the book now incorporates discussions of experimental platforms. Several chapters on experimental implementations of quantum information protocols have been added: implementations using neutral atoms, trapped ions, optics, and solidstate systems are each presented in its own chapter. Previous chapters on entanglement, quantum measurements, quantum dynamics, quantum cryptography, and quantum algorithms have been thoroughly updated, and new additions include chapters on the stabilizer formalism and the Gottesman-Knill theorem as well as aspects of classical and quantum information theory. To facilitate learning, each chapter starts with a clear motivation to the topic and closes with exercises and a recommended reading list. Quantum Information Processing: Theory and Implementation will be essential to graduate students studying quantum information as well as and researchers in other areas of physics who wish to gain knowledge in the field.

Introduction to the Theory of Quantum Information Processing provides the material for a one-semester graduate level course on quantum information theory and quantum computing for students who have had a one-year graduate course in quantum mechanics. Many standard subjects are treated, such as density matrices, entanglement, quantum maps, quantum cryptography, and quantum codes. Also included are discussions of quantum machines and quantum walks. In addition, the book provides detailed treatments of several underlying fundamental principles of quantum theory, such as quantum measurements, the no-cloning and no-signaling theorems, and their consequences. Problems of various levels of difficulty supplement the text, with the most challenging problems bringing the reader to the forefront of active research. This book provides a compact introduction to the fascinating and rapidly evolving interdisciplinary field of quantum information theory, and it prepares the reader for doing active research in this area.