Computational Physics

Date: 27 April 2011, 07:50

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In 1999, when we started teaching this course at the Department of Physics in Oslo, Computational Physics and Computational Science in general were still perceived by the majority of physicists and scientists as topics dealing with just mere tools and number crunching, and not as subjects of their own. The computational background of most students enlisting for the course on computational physics could span from dedicated hackers and computer freaks to people who basically had never used a PC. The majority of graduate students had a very rudimentary knowledge of computational techniques and methods. Four years later most students have had a fairly
uniform introduction to computers, basic programming skills and use of numerical exercises in undergraduate courses. Practically every undergraduate student in physics has now made a Matlab or Maple simulation of e.g., the pendulum, with or without chaotic motion. These exercises
underscore the importance of simulations as a means to gain novel insights into physical systems, especially for those cases where no analytical solutions can be found or an experiment is to complicated or expensive to carry out. Thus, computer simulations are nowadays an integral part of contemporary basic and applied research in the physical sciences. Computation is becoming as important as theory and experiment. We could even strengthen this statement by saying that computational physics, theoretical physics and experimental are all equally important
in our daily research and studies of physical systems. Physics is nowadays the unity of theory, experiment and computation. The ability "to compute" is now part of the essential repertoire of research scientists. Several new ?elds have emerged and strengthened their positions in the last years, such as computational materials science, bioinformatics, computational mathematics and mechanics, computational chemistry and physics and so forth, just to mention a few. To be able to e.g., simulate quantal systems will be of great importance for future directions in ?elds like materials science and nanotechonology.

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