Cellular Automata Technology

Theory of Computation -- Computation by Abstracts Devices.

The thirty four contributions in this book cover many aspects of contemporary studies on cellular automata and include reviews, research reports, and guides to recent literature and available software. Cellular automata, dynamic systems in which space and time are discrete, are yielding interesting applications in both the physical and natural sciences. The thirty four contributions in this book cover many aspects of contemporary studies on cellular automata and include reviews, research reports, and guides to recent literature and available software. Chapters cover mathematical analysis, the structure of the space of cellular automata, learning rules with specified properties: cellular automata in biology, physics, chemistry, and computation theory; and generalizations of cellular automata in neural nets, Boolean nets, and coupled map lattices.Current work on cellular automata may be viewed as revolving around two central and closely related problems: the forward problem and the inverse problem. The forward problem concerns the description of properties of given cellular automata. Properties considered include reversibility, invariants, criticality, fractal dimension, and computational power. The role of cellular automata in computation theory is seen as a particularly exciting venue for exploring parallel computers as theoretical and practical tools in mathematical physics. The inverse problem, an area of study gaining prominence particularly in the natural sciences, involves designing rules that possess specified properties or perform specified task. A long-term goal is to develop a set of techniques that can find a rule or set of rules that can reproduce quantitative observations of a physical system. Studies of the inverse problem take up the organization and structure of the set of automata, in particular the parameterization of the space of cellular automata. Optimization and learning techniques, like the genetic algorithm and adaptive stochastic cellular automata are applied to find cellular automaton rules that model such physical phenomena as crystal growth or perform such adaptive-learning tasks as balancing an inverted pole.Howard Gutowitz is Collaborateur in the Service de Physique du Solide et Résonance Magnetique, Commissariat a I'Energie Atomique, Saclay, France.

Cellular automata make up a class of completely discrete dynamical systems, which have became a core subject in the sciences of complexity due to their conceptual simplicity, easiness of implementation for computer simulation, and their ability to exhibit a wide variety of amazingly complex behavior. The feature of simplicity behind complexity of cellular automata has attracted the researchers' attention from a wide range of divergent fields of study of science, which extend from the exact disciplines of mathematical physics up to the social ones, and beyond. Numerous complex systems containing many discrete elements with local interactions have been and are being conveniently modelled as cellular automata. In this book, the versatility of cellular automata as models for a wide diversity of complex systems is underlined through the study of a number of outstanding problems using these innovative techniques for modelling and simulation.

The Quantum Cellular Automaton (QCA) concept represents an attempt to break away from the traditional three-terminal device paradigm that has dominated digital computation. Since its early formulation in 1993 at Notre Dame University, the QCA idea has received significant attention and several physical implementations have been proposed. This book provides a comprehensive discussion of the simulation approaches and the experimental work that have been undertaken on the fabrication of devices capable of demonstrating the fundamentals of QCA action. Complementary views of future perspectives for QCA technology are presented, highlighting a process of realistic simulation and of targeted experiments that can be assumed as a model for the evaluation of future device proposals. Contents: The Concept of Quantum-Dot Cellular Automata (C S Lent); QCA Simulation with the Occupation-Number Hamiltonian (M Macucci & M Governale); Realistic Time-Independent Models of a QCA Cell (J Martorell et al.); Time-Independent Simulation of QCA Circuits (L Bonci et al.); Simulation of the Time-Dependent Behavior of QCA Circuits with the Occupation-Number Hamiltonian (I Yakimenko & K-F Berggren); Time-Dependent Analysis of QCA Circuits with the Monte Carlo Method (L Bonci et al.); Implementation of QCA Cells with SOI Technology (F E Prins et al.); Implementation of QCA Cells in GaAs Technology (Y Jin et al.); Non-Invasive Charge Detectors (G Iannaccone et al.); Metal Dot QCA (G L Snider et al.); Molecular QCA (C S Lent); Magnetic Quantum-Dot Cellular Automata (MQCA) (A Imre et al.). Readership: Physicists, electronic engineers and academics.

This book explores Probabilistic Cellular Automata (PCA) from the perspectives of statistical mechanics, probability theory, computational biology and computer science. PCA are extensions of the well-known Cellular Automata models of complex systems, characterized by random updating rules. Thanks to their probabilistic component, PCA offer flexible computing tools for complex numerical constructions, and realistic simulation tools for phenomena driven by interactions among a large number of neighboring structures. PCA are currently being used in various fields, ranging from pure probability to the social sciences and including a wealth of scientific and technological applications. This situation has produced a highly diversified pool of theoreticians, developers and practitioners whose interaction is highly desirable but can be hampered by differences in jargon and focus. This book – just as the workshop on which it is based – is an attempt to overcome these difference and foster interest among newcomers and interaction between practitioners from different fields. It is not intended as a treatise, but rather as a gentle introduction to the role and relevance of PCA technology, illustrated with a number of applications in probability, statistical mechanics, computer science, the natural sciences and dynamical systems. As such, it will be of interest to students and non-specialists looking to enter the field and to explore its challenges and open issues.

This book gathers selected research papers presented at the Second Asian Symposium on Cellular Automata Technology (ASCAT 2023), organized by academicians from Kolkata at Indian Institute of Engineering Science and Technology, Shibpur, West Bengal, India, and by researchers of Cellular Automata India, a research group which was created during the pandemic, during March 2–4, 2023. The book presents one of the most emergent areas in natural computing, cellular automaton (CA). CA is a paradigm of uniform fine-grained parallel computation which has been explored to understand complex systems by developing its model at the microscopic level. The book discusses many real-life problems in the domain of pattern recognition and classification, clustering, electronic circuit design, bioinformatics, material and mining engineering, modelling of physical and social systems, etc., by using CA.

This book gathers selected research papers presented at the First Asian Symposium on Cellular Automata Technology (ASCAT 2022), organized online by academicians from Kolkata, India, during March 3–5, 2022. The book presents one of the most emergent areas in natural computing, cellular automaton (CA). CA is a paradigm of uniform fine-grained parallel computation which has been explored to understand complex systems by developing its model at the microscopic level. The book discusses many real-life problems in the domain of very large-scale integration (VLSI) design and test, pattern recognition and classification, cryptography, pseudo-random pattern generation, image processing, sensor networks, material science, etc., by using CA.