Series:

Frontiers in Physics

5 total works

Cover of Photon-Hadron Interactions
In these classic lectures, Feynman analyses the theoretical questions related to electron and photon interactions at high energies. These lectures are based on a special topics course taught by Feynman at Caltech in 1971 and 1972. The material is dealt with on an advanced level and includes discussions of vector meson dominance and deep inelastic scattering. The possible consequences of the parton model are also analyzed.

Cover of Statistical Mechanics

Statistical Mechanics

by Richard P Feynman

Published 21 January 1972

This classic graduate lecture note volume on statistical mechanics focuses on Physics, rather than mathematics. It provides a concise introduction to basic concepts and a clear presentation of difficult topics, while challenging the student to reflect upon as yet unanswered questions.

Cover of Quantum Electrodynamics

Quantum Electrodynamics

by Richard P Feynman

Published 12 December 1962
This text material constitutes notes on the third of a three-semester course in quantum mechanics given at the California Institute of Technology in 1953, presenting the main results and calculational procedures of quantum electrodynamics.

Cover of Feynman Lectures On Computation
When, in 1984 86, Richard P. Feynman gave his famous course on computation at the California Institute of Technology, he asked Tony Hey to adapt his lecture notes into a book. Although led by Feynman, the course also featured, as occasional guest speakers, some of the most brilliant men in science at that time, including Marvin Minsky, Charles Bennett, and John Hopfield. Although the lectures are now thirteen years old, most of the material is timeless and presents a "Feynmanesque" overview of many standard and some not-so-standard topics in computer science such as reversible logic gates and quantum computers.

Cover of Feynman And Computation

Feynman And Computation

by Anthony Hey

Published 27 June 2002
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.