Modern mathematical modelling and simulation methods have become a fundamental resource for scientific and technological progress. Mathematical modelling and simulation is therefore a key methodological area of great relevance for the natural sciences and engineering and for economic, social, life and environmental sciences. As a consequence, many Leibniz Institutes invest in these methods.

Methods from a wide range of mathematical fields are used (statistics, mathematical finance, optimisation/operations research, numerical methods for partial differential equations, mathematical image processing, etc.), to investigate problems on every conceivable temporal and spatial scale (from nanoparticles to immense cosmic structures, from femtoseconds to the age of the universe) with widely differing levels of complexity (from an individual company to the entire global economy, from local environmental events to global climate models).

The common factor in all these methods is that they are based on mathematical principles. This means they are cross-sectional in nature and can generally be used outside of the context in question, to help solve problems in completely different branches of science. There is great potential here for effective utilisation.

One of the key aims of this Leibniz Research Network is therefore to systematically exploit this potential for effective use and synergies. An important question is which is the fastest, most suitable and error-free of the current mathematical research methods to use in each case – to ensure that the available software and hardware resources are used effectively and sustainably.


Dr Torsten Köhler
Weierstrass Institute for Applied Analysis and Stochastics (WIAS), Berlin
T +49 30 20372582