SERC School on Comp Stat Phys

A tentative outline of the courses is given here. Detailed course contain will be uploaded later.

Graph Enumeration Techniques:

Combinatorics, Asymptotic analysis, Application to Ising model, polymers, random walks, self-avoiding walks, biased walks, etc.

Instructors: D. Dhar and S. Kumar.

Monte Carlo Techniques:

Random number generation and Quality testing, Simple sampling of probability distribution, Importance sampling and Metropolis method, Finite size effects and boundary conditions, Error analysis, Applications in critical phenomena, phase transitions etc.; Applications to dynamic phenomena, Monte Carlo renormalization group technique and its applications, Quantum Monte Carlo and applications.

Instructors: S. Ramasesha, P. Ray and S. B. Santra.

Molecular Dynamics:

Physical Principles and different ensembles, Potentials in MD simulations, Examples of applications, Molecular dynamics algorithms, Integrators (Symplectic integrators), Thermostats, Long-range interaction algorithms, Parallelization strategies, Major software for MD simulations, Applications in liquids having long time correlations, Applications to biological systems.

Instructors: S. L. Chaplot and P. K. Maiti.

Mesoscale and Hydrodynamic Methods:

Brownian Dynamics, Dissipative Particle Dynamics (DPD), Langevin Dynamics, Lattice Boltzmann, Navier-Stokes simulation of turbulence, Applications to self-assembly of biomolecules, turbulence etc.

Instructors: R. Adhikari and S. Puri.

Optimization and Quantum Annealing:

Cost function minimization methods: simplex, conjugate gradients, genetic algorithms, annealing, quantum annealing, Applications with examples.

Instructors: B. K. Chakrabarti and S. K. Sarkar.

All courses will have tutorials and practise sessions on computers.