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DY: Fachverband Dynamik und Statistische Physik

DY 22: Poster: Statistical Physics

DY 22.20: Poster

Mittwoch, 19. März 2025, 10:00–12:00, P3

Brownian particles for unconventional computing — •Alessandro Pignedoli, Atreya Majumdar, and Karin Everschor-Sitte — Faculty of Physics and Center for Nanoin- tegration Duisburg-Essen (CENIDE), University of Duisburg-Essen

Brownian particles naturally explore a system’s configuration space offering an energy efficient approach to optimisation problems [1]. We demonstrate that interacting Brownian particles can solve optimisation problems [2,3] more efficiently than individual particles acting alone. This collective efficiency arises from their local interactions, which mimic the principles of swarm intelligence, where the whole systems emergent behaviour outperforms the sum of its individual components [4].

[1] C. H. Bennett, Int. J. Theor. Phys. 21, 905 (1982); [2] German Patent Application DE 10 2023 131 171, K. Everschor-Sitte, A. Pignedoli, B. Dörschel (2023); [3] German Patent Application DE 10 2023 131 706, K. Everschor-Sitte, A. Pignedoli, B. Dörschel (2023); [4] Bonabeau, et al, Oxford University Press (1999).

Keywords: Unconventional computing; Swarm intelligence; Brownian motion