Computerorientierte Theoretische Physik

DPG Physics School "Computational Physics of Complex and disordered Systems"

Organized by A.K. Hartmann and A.P. Young (UCSC).

21-25. September, Physik Zentrum Bad Honnef, Germany

A general overview, including scope, invited lecturers and program is ready for download.

Material of the school (slides, exercise code etc.), can be found here.

Please remember that there will be a poster session, where all participants can exhibit a poster showing their own research project(s).

An essential part of the school will be hands-on exercises. For this purpose you should bring your own laptop to the school (at least half of the participants should have a laptop). We do not require a specific operation system/development environment, but should be be able to:

  1. Edit source code files in C/Python/Perl (e.g., using emacs)
  2. compile C programs (e.g., using cc/gcc), and run Python/Perl scripts.
  3. runs programs/scripts including passing parameters (e.g., from a shell)
  4. plot resulting data files, mainly x-y format (e.g., using gnuplot)

    Note that we strongly recommend to use Linux/Unix/Mac(Xcode), because high-performance scientific computing is based almost everywhere on this class of operating systems.

For some exercises, you need also specific programs:

Here, we provide a couple of sample packages, which allow you to test your system. Each package contains detailed information what programs should be additionally available. it is very important that you download these packages, install the required software (all are freely available, some require a bit of work, e.g. to install the correct version etc) and make sure that they run. Only in this way you can enjoy the exercises.


1. package for Katzgraber/Ochoa exercises (needs editor, C compiler, make, gnuplot)

2. package for Kob/Coslovich exercises (needs editor, C/Fortran compiler, gnuplot, visual Python, see package for details)

3. package for Sinatra/Barzel exercises (needs Gephi, Python with NetworkX, see package for details)

4. For Krauth exercises, standard editor, Python 2.X with numpy and the matplotlib are sufficient.