Feynman And Computation

by Anthony Hey

Overview

Computational properties of use to biological organisms or to the construction of computers can emerge as collective properties of systems having a large number of simple equivalent components (or neurons). The physical meaning of content-addressable memory is described by an appropriate phase space flow of the state of a system. A model of such a system is given, based on aspects of neurobiology but readily adapted to integrated circuits. The collective properties of this model produce a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size. The algorithm for the time evolution of the state of the system is based on asynchronous parallel processing. Additional emergent collective properties include some capacity for generalization, familiarity recognition, categorization, error correction, and time sequence retention. The collective properties are only weakly sensitive to details of the modeling or the failure of individual devices.

Product Details

ISBN-13:	9780813340395
Publisher:	Taylor & Francis
Publication date:	06/27/2002
Series:	Frontiers in Physics
Edition description:	Revised ed.
Pages:	462
Product dimensions:	6.00(w) x 8.90(h) x 1.10(d)

About the Author

David Pines is research professor of physics at the University of Illinois at Urbana-Champaign. He has made pioneering contributions to an understanding of many-body problems in condensed matter and nuclear physics, and to theoretical astrophysics. Editor of Perseus' Frontiers in Physics series and former editor of American Physical Society's Reviews of Modern Physics, Dr. Pines is a member of the National Academy of Sciences, the American Philosophical Society, a foreign member of the USSR Academy of Sciences, a fellow of the American Academy of Arts and Sciences, and of the American Association for the Advancement of Science. Dr. Pines has received a number of awards, including the Eugene Feenberg Memorial Medal for Contributions to Many-Body Theory; the P.A.M. Dirac Silver Medal for the Advancement of Theoretical Physics; and the Friemann Prize in Condensed Matter Physics.

Table of Contents

Feynman and Computation — Feynman’s Course on Computation — Feynman and Computation — Neural Networks and Physical Systems with Emergent Collective Computational Abilities — Feynman as a Colleague — Collective Electrodynamics I — A Memory — Numerical Evidence that the Motion of Pluto is Chaotic — Reducing the Size — There’s Plenty of Room at the Bottom — Information is Inevitably Physical — Scaling of MOS Technology to Submicrometer Feature Sizes — Richard Feynman and Cellular Vacuum — Quantum Limits — Simulating Physics with Computers — Quantum Robots — Quantum Information Theory — Quantum Computation — Parallel Computation — Computing Machines in the Future — Internetics: Technologies, Applications and Academic Fields — Richard Feynman and the Connection Machine — Crystalline Computation — Fundamentals — Information, Physics, Quantum: The Search for Links — Feynman, Barton and the Reversible Schrödinger Difference Equation — Action, or the Fungibility of Computation — Algorithmic Randomness, Physical Entropy, Measurements, and the Demon of Choice

Editorial Reviews

This work was originally published in 1999 by Perseus Press. Three papers by Feynman and 19 contributions address the advanced topics covered in the course on computation he taught at CalTech. Many of the contributions are updated versions of guest lectures. The five sections consider the evolution of his lectures, limitations due to size, limitations due to quantum mechanics, parallel computation, and fundamentals, such as reversible dynamics, action integrals, and the threat to the second law of thermodynamics posed by Maxwell's Demon. Intended as a complementary volume to (1996). Annotation c. Book News, Inc., Portland, OR (booknews.com)