Berlin 2024 – scientific programme

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BP: Fachverband Biologische Physik

BP 35: Active Matter V (joint session BP/DY)

BP 35.8: Talk

Friday, March 22, 2024, 11:45–12:00, H 1028

Analysis techniques for active matter simulations — Lukas Hecht, Kay-Robert Dormann, •Aritra Mukhopadhyay, Kai Spanheimer, Mahdieh Ebrahimi, Suvendu Mandal, and Benno Liebchen — Institut für Physik kondensierter Materie, Technische Universität Darmstadt, Hochschulstr. 8, D-64289 Darmstadt, Germany

Simulations of active matter systems provide a promising route to understand collective phenomena and the non-equilibrium physics of active matter. Prominent models for active matter systems comprise particle-based models such as the active Brownian particle model and continuum models such as the active model B+. To analyze the data obtained from the numerical solution of these models, currently, many researchers develop in-house code. Here, we present the Active Matter Evaluation Package (AMEP), a unified framework to analyze active matter simulations. This Python library is easy to use and provides a powerful and simple interface for handling large data sets. The package features various methods for calculating observables, visualizing results, and analyzing data from molecular-dynamics, Brownian-dynamics, and continuum simulations. These features allow the user, for example, to easily calculate spatial and temporal correlation functions, to perform cluster analyses, to visualize simulation results, and to study phase separation, pattern formation, and critical phenomena in active matter systems.

Keywords: data analysis; python; active matter; soft matter; computer simulation