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About:
This
is a course about modern computational methods for the simulation of
many-body systems in condensed matter physics, including systems from
classical statistical physics and quantum many-body problems. Besides the
theoretical understanding of these algorithms and the physics of many-body
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 state-of-the-art
methods relevant in many areas in Science (also in non-academic areas)
intend to do a computationally oriented project
in future (e.g. Master- or PhD-thesis)
would like to strengthen their understanding
in many-body 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 flat-histogram methods)
Numerical
study of first and second order phase transitions in magnetic systems
Numerical
methods for the quantum one-body problem
Quantum
many-body problems (electronic structure problem) and effective lattice
models (e.g. spin chains and Hubbard model)
Hartree-Fock 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/warm-up in the first week
This course (6EC) takes place in block 5 (semester 2), see course
catalogue or datanose.
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