About:
This
is a course about modern computational methods for the simulation of
manybody systems in condensed matter physics, including systems from
classical statistical physics and quantum manybody problems. Besides the
theoretical understanding of these algorithms and the physics of manybody
systems an important part of the course is to gain practical experience in
computational physics by implementing algorithms (programming) and
performing simulations.
Recommended for people who:
would like to dive into the fascinating field
of computational physics
would like to learn about stateoftheart
methods relevant in many areas in Science (also in nonacademic areas)
intend to do a computationally oriented project
in future (e.g. Master or PhDthesis)
would like to strengthen their understanding
in manybody physics
enjoy programming and would like to get more
practice in programming (we use Python in the exercises)
Topics:
Monte Carlo
methods for classical spin systems (Metropolis algorithm, cluster
algorithms and flathistogram methods)
Numerical
study of first and second order phase transitions in magnetic systems
Numerical
methods for the quantum onebody problem
Quantum
manybody problems (electronic structure problem) and effective lattice
models (e.g. spin chains and Hubbard model)
HartreeFock and Density Functional Theory
Exact diagonalization of quantum lattice models
Quantum
Monte Carlo and the negative sign problem
The density
matrix renormalization group and tensor network methods
Programming
language:
As
programming language we will use Python
We will do
a short introduction/warmup in the first week
This course (6EC) takes place in block 5 (semester 2), see course
catalogue or datanose.
