This course is a continuation of Computational Physics course (509). It introduces andvanced concepts and algorithms in Computational Condensed Matter Physics and brings students to the active research in Computational Condensed Matter area.

Lectures will be given in "hands on" style only, and students should bring their own laptops to follow the lectures. Latops should run python (including numpy, scipy, weave, matplotlib) and should have C++ and fortran compiler installed.

This course requires familiarity with some basics of programming languages such as Python (and a little of C++). It is designed for the student who wishes to broaden his/her knowledge of applications of computation and develop techniques in Computational Physics.

Class Time: ARC building (108), 3:20-4:40pm on Monday and Wednesday

Instructor:

Kristjan Haule Office: Serin E267 email: haule@physics.rutgers.edu Phone: 445 5500, ext: 3881 Office hours: Monday 4 pm

If you are not yet familiar with Python, or you just want to refresh your memory, check out some of these links:

1. Learn Python in 10 minutes
2. How to Think Like a Computer Scientist
3. Python for beginners
4. Dive Into Python
5. Code Like a Pythonista: Idiomatic Python
6. Python documentation
7. Python regular expressions
8. Weave (to speed up the Python code)

1. Set up the environment on your computer to be able to code in Python or C++. The instructions from 509 can help.

1. Perturbation theory at low orders
2. Random numbers and multidimensional integration
3. Monte Carlo methods and Simulated Annealing
4. Quantum Monte Carlo methods
5. Continuous Time Quantum Monte Carlo method
6. Parallel programming with MPI
7. Exact diagonalization
8. Density functional theory
9. Dynamical Mean Field Theory for model Hamiltonians
10. Local Density Approximation + Dynamical Mean Field Theory (LDA+DMFT)

1. Molecular dynamics simulation

Students with Disabilities