Scientific Computing

Along with theory and experimentation, scientific computing (SC) is considered the third pillar of methodology in science. Its methods – mathematical modelling, visualisation, simulation and optimisation, image and data processing – coalesce to form a key technology for solving scientific and technical problems. Areas of application range from fuel cell design and chemical plant control optimisation to tumour diagnostics.
 
With the founding of the Interdisciplinary Center for Scientific Computing (IWR) in 1987, Heidelberg University recognised this trend and has continuously promoted SC methods. In its early days, the IWR focussed on mathematics, physics, chemistry, informatics and the life sciences. Now the methods of scientific computing are indispensable, over the years becoming increasingly important in economics, the social sciences, psychology, the cognitive sciences, and more recently in the humanities and cultural studies. Scientific computing creates a strong framework for research and a methodology portfolio linking the four Fields of Focus (FoFs).
 
Current examples of the cross-disciplinary research topics in scientific computing are:

• development of 2D and 3D analysis methods for virtual reconstruction of artefacts in the humanities (computational humanities);
• optimisation methods for the analysis of human decision-making behaviour in psychology;
• SC in the environmental sciences to study highly nonlinear dynamics, uncertain, heterogeneous multi-scale parameters and stochastic forcing;
• modelling and simulation of multi-scale processes in organic electronics.

Funds from the university’s institutional strategy are used to support interdisciplinary projects. “Twinning projects” involve researchers from at least two different disciplines to explore new application areas and stimulate interdisciplinary cooperation within the university. A steering committee comprising experts in SC and representatives from all the Fields of Focus select the projects for funding.

Since the initial funding phase of the Excellence Initiative, the Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences has joined the IWR.