The course will illustrate how computation is used in some areas of
physics and related disciplines, including statistical physics, quantum
physics and chemistry, biophysics and nonlinear dynamics. The mathematical
techniques surveyed will include ordinary differential equations, solution
of linear systems of equations, the Monte Carlo method, the Fast-Fourier
Transform, and finite-difference solution of partial differential
equations. Applications to topics in classical mechanics (molecular
dynamics, classical chaos), quantum mechanics (molecular electronic
structure, time-dependent wavepacket propagation, path integrals for
quantum statistical mechanics), statistical physics (Ising models) and
biophysics (ion transport through protein channels, protein folding) will
be presented. as neural network theory will be considered. Some
introduction to supercomputer architectures and parallel computing will be
provided.
