P452 Computational Physics

Course No: 
P206 (Quantum Mechanics I) & P301 (Statistical Mechanics)

(42 Lectures + 14 Tutorial)

  1. Introduction to theory of computation and Random numbers.
  2. Monte Carlo: Importance sampling, Markov chain, Metropolis algorithm, Ising Model and other applications.
  3. Molecular Dynamics: Integration methods (e.g Verlet and Leap frog algorithms), extended ensembles, molecular system.
  4. Variational methods for Schrodinger Equation, Hartree and Hartee-Fock methods. 

  5. Quantum Monte Carlo methods. 

  6. Special Topics Like: QMD, Ideal fluids, matrix inversions, Numerical solution of Poisson’s equation: Finite difference method. Particle-Mesh Methods, radiative transfer etc.

Reference Books: 
  1. Computational Physics by Joseph Marie Thijssen, Cambridge University Press
  2. An Introduction to Computational Physics by Tao Pang, Cambridge University press
  3. Computer Simulation of Liquid by M. P. Allen and D. J. Tildesley, Clarendon press
  4. A Guide to Monte Carlo Simulations in Statistical Physics by L. Landau and K. Binder
  5. Quantum Monte Carlo Methods by M. Suzuki (Editor) Springer-Verlag
  6. New Methods in Computational Quantum Mechanics by I. Prigogine and Stuart A. Rice
  7. Understanding Molecular Simulation by D. Frankel and B. Smit, Second edition, academic press.
  8. Computational Methods in Field Theory by H. Gausterer and C.B. Lang (Lecture notes in physics 409)
  9. Density Functional Theory of Atoms and Molecules by R. G. Parr and W. Yang
  10. F. Jensen, introduction to Computational Chemistry by F. Jensen
  11. Essentials of Computational Chemistry by C. J. Crammer
  12. Dynamical mean field theory by Jean-Marc Robin
  13. Quantum Monte Carlo Methods by James Gubernatis, Naoki Kawashima, Philipp Werner
  14. Computer Simulations using Particles - R. W. Hockney and J. W. Eastwood
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