Stochastic processes and their applications for the simulations of complex systems
Date: 4 – 9 March 2019
Convenors: Frithjof Karsch (Bielefeld, GER), Ion-Olimpiu Stamatescu (Heidelberg, GER)
Exploiting the complexity of strongly interacting systems quite often requires large-scale numerical simulations. Stochastic processes play a major role in advanced simulation and data analysis.
In physics the theory of strong interactions, Quantum Chromodynamics, has been studied since many years very successfully through numerical simulations involving stochastic algorithms. With ever increasing speed of computers, these simulations became more realistic creating thereby vast amounts of data. Using stochastic processes in data analysis is relatively new and, to some extent, unfamiliar. The amount of data, however, and the complexity of the information that one aims to extract requires the development of new analysis strategies in parallel to new simulation methods. Techniques developed in the statistical machine learning approach are promoting exciting new developments in theoretical physics. Other fields dealing with complex systems, such as computational biology, econophysics or computer vision also are intensively studied with the help of stochastic algorithms. Also these studies became increasingly confronted with the necessity of performing large simulations and the managing of huge amounts of data. In all these areas there is steady effort to develop new algorithms to optimise the simulations based on stochastic processes. These efforts profit from the interaction among the various fields and the existence and further development of a firm mathematical basis.
The proposed workshop is intended to bring together scientists involved in the development and application of stochastic processes. The aim is to exchange ideas for new algorithm developments and inform about experience made with various newly proposed techniques. It should provide a platform for discussions between mathematicians and physicists from elementary particles theory and the theory of complex systems, including biophysics, econophysics and machine learning. Emphasis is put on allowing much time for discussions both in plenum and in ad-hoc subgroups.