Syllabus

1. Interpolation (Lagrange method).
2. Numerical integration (Simpson & Trapezoidal method).
3. Differentiation (Runge-Kutta method).
4. Numerical solution to partial differential equations.
5. Solving Schrödinger equation for quantum harmonic oscillator.
6. Simulating chemical equilibrium of a gas using random numbers.
7. Introduction to classical Monte-Carlo (MC) simulation. MC simulation of 2D Ising model.
8. Phase-space analysis of non-linear physical systems.

The objective of this laboratory course is to equip the students with some fundamental computational techniques which are regularly used to solve some mathematical and physical problems numerically.

1. Learn to use computers to solve mathematical problems.
2. Develop the skills to solve physical problems with the help of computers.

Steven C. Chapra, Numerical Methods for Engineers, McGraw Hill Education India Private Limited

David P. Landau and Kurt Binder, A Guide to Monte Carlo Simulations in Statistical Physics, Cambridge University Press

Rubin H. Landau, Manuel J Páez, Cristian C. Bordeianu, Computational Physics: Problem Solving with Computers, Wiley VCH

Steven Koonin, Dawn Meredith, Computational Physics: Fortran Version, Westview Press