PHYS 542

Numerical Methods in Physics
Numerical methods for data analysis and computation in physics

Spring Quarter, 2011
T-Th 7:00-8:50 pm
Tuesdays: A114 Physics Astronomy Building
Thursdays: online session (or in-person, go to B305 Physics Astronomy Building)

Instructor: R. J. Wilkes
Professor, Department of Physics
wilkes@u.washington.edu, B303 PAB, 543-4232

4 credits 
MS program and GNM students: register in Section A, using form sent by UW-PCE,
All other students register in Section B via MyUW


The following topics will be covered,  illustrated with case studies of applications in physics research. Grades will be based on a mid-term quiz, and a brief written report on a topic chosen by the student.

Numerical precision
Sorting, matrix inversion, histograms
Interpolation and smoothing: polynomial and spline, Chebyshev, miscellaneous
Integration: elementary, Gaussian quadrature, Monte Carlo and 2D integration
Statistics: distributions, significance tests, correlations
Minimization and fitting: linear and nonlinear least squares, max likelihood, minimax
Monte Carlo methods
Fourier methods: Fast Fourier Transforms,  convolution and correlations, spectra and filtering
Differential equations: Runge-Kutta method, shooting method, relaxation methods

Textbooks: 
Required: Numerical Recipes: The Art Of Scientific Computing, W. Press et al, Cambridge, 2007. Earlier editions 1992 or later are OK also (C, C++ or Fortran).
Recommended: 
Numerical Recipes Source Code CD, Cambridge, 2007;

Prerequisites: 
Graduate status, or get permission of instructor by email.
Familiar with elements of calculus, linear algebra and complex variables.
Familiarity with a high-level programming language (e.g., C++, basic, fortran) or programming environment (Matlab, Mathcad, Mathematica) is helpful, but not required.