Inferring the collective dynamics of active particle by data assimilation (B07)

• Subject Area: Mathematics
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 318763901

Project B07 brings biophysical experiments, stochastic modelling, statistical analysis, and data assimilation together to better understand how active particles, for example living cells, move, interact and form patterns. Whereas we investigated the inference of parameter distributions for heterogeneous ensembles of active particles based on observations of individual trajectories in the previous funding period, we will now turn to the study of collective pattern formation in interacting systems. This research focuses on data-driven inference, analysis and model verification for pattern formation in active matter at various length- and timescales, particularly enabling to relate the interactions at the particle level with emergent structures at the meso- or macroscale.

• DFG Programme: Collaborative Research Centres
• Subproject of: SFB 1294: Data Assimilation – The Seamless Integration of Data and Models
• Applicant Institution: Universität Potsdam
• Project Heads: Professor Dr. Carsten Beta, since 7/2021; Dr. Robert Großmann, since 7/2021; Professor Dr. Manfred Opper, from 7/2021 until 12/2025