Computational Physics

Mooc course

Title: Computational Science and Engineering using Python

NPTEL course link: https://nptel.ac.in/courses/115104095/

Youtube link: here

See the tutorials here


Course Contents

First Part

  1. About computers: hardware and software

  2. How to be a good programmer?

  3. Algorithmic thinking and Aesthetics.

  4. Python Programming Language

Second Part: Numerical analysis

Interpolation, Integration, Differentiation, ODE solver, PDE solver, matrix computations, Monte-Carlo method, Equation solver.

Detailed schedule for 2020 Sept-Nov course

Week 1 Sept 1-6: About computers, Python: Variables and Array (1,2,3)

Week 2 Sept 7-13: Python: Control structures, Programming style (4,5)

Week 3 Sept 14-20: Plotting, Error Analysis & Nondimenensionalization, Data input/output, (6,7,8)

Week 4: Sept 21-27: Interpolation (9,10)

Week 5 Sept 28-Oct 4: Numerical integration (11,12,13)

Week 6 Oct 5-Oct 11: Differentiation (14), ODE solvers (15,16)

Midsem exam Oct 12-18

Week 7 Oct 19-25: ODE solvers (15,16) continued

Week 8 Oct 26-Nov 1: Fourier transforms, PDE solvers_-diffusion spectral (17, 18)

Week 9 Nov 2-8: PDE solvers: FD (diffusion, wave eqn) (19A, 19B, 20A)

Week 10: Nov9-15: PDE solvers: FD (diffusion, wave eqn) (19A, 19B, 20A), Schrodinger equation (23)

Week 11: Nov16-22: Nonlinear equations (24), Boundary value problem (25),Linear Algebra (26)

Week 12: Nov 23-29: Summary (27)

Dec 3-12: Exam

Textbooks & References

  1. Mark Newmann: Computational Physics with Python, 2nd Ed. (to be placed in TB section). http://www-personal.umich.edu/~mejn/cp/index.html

  2. J. M. Stewart: Python for Scientists, Cambridge U. Press (2014)

  3. M. Lutz, Learning Python 5th Edition, O'Reilly Media (2013)

  4. J. H. Ferziger, Numerical Methods for Engineering Applications, John Wiley & Sons (in TB section).