Spectral Methods in Computational Physics

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Course Description

Data analysis, spectra and correlations, sampling theorem, nonperiodic data, and windowing; spectral methods for numerical solution of partial differential equations; accuracy and computational cost; fast Fourier transform, Galerkin, collocation, and Tau methods; spectral and pseudospectral methods based on Fourier series and eigenfunctions of singular Sturm-Liouville problems; Chebyshev, Legendre, and Laguerre representations; convergence of eigenfunction expansions; discontinuities and Gibbs phenomenon; aliasing errors and control; efficient implementation of spectral methods; spectral methods for complicated domains; time differencing and numerical stability.

Cross Listed Courses

Grading Basis

ROP - Letter or Credit/No Credit

Min

3

Max

3

Course Repeatable for Degree Credit?

No

Course Component

Discussion

Enrollment Optional?

Yes

Course Component

Lecture

Enrollment Optional?

No

Does this course satisfy the University Language Requirement?

No

Programs

CME322 is a completion requirement for:
  • (from the following course set: )
  • (from the following course set: )