Computational Physics

Week 1: Rapid overview of Fortran programming LanguageWeek 2: Random Number generation and testing, Generation of random numbers with given distributionWeek 3: Numerical Integration: (a) Deterministic: Trapezoidal method & (b) Multi-dimensional Integration
using stochastic methods.Week 4: Lattice Monte Carlo simulations using Ising model to understand phase transitions: Metropolis
algorithm, understanding kinetic barriers, finite size effects, role of thermal fluctuationsWeek 5: Metropolis algorithm, understanding kinetic barriers, finite size effects, role of thermal fluctuations;
Principle of detailed balance, calculating thermodynamic averagesWeek 6: Determining transition temperature using Binders cumulant
Week 7: Solving differential equationsWeek 8: Linear, non-linear and coupled differential equations
Week 9: Solving differential equations Schrodinger eqn. in Quantum Mechanics with Numerov’s algorithm
and variational principle.
Week 10:Classical Molecular Dynamics simulations using Lennard-Jones’ potential
Week 11:Classical Molecular Dynamics simulations using Lennard-Jones’ potential
Week 12:Classical Molecular Dynamics simulations using Lennard-Jones’ potential