Dresden 2026 – wissenschaftliches Programm

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DY: Fachverband Dynamik und Statistische Physik

DY 61: Brownian Motion and Anomalous Transport

DY 61.4: Vortrag

Freitag, 13. März 2026, 10:15–10:30, ZEU/0118

Leveraging Interactions for Efficient Swarm-Based Brownian Computing — •Alessandro Pignedoli, Atreya Majumdar, and Karin Everschor-Sitte — University of Duisburg-Essen, CENIDE Center for Nanointegration Duisburg-Essen

Brownian particles naturally explore a system's configuration space through thermal fluctuations, requiring no external energy input. This intrinsic property makes them an energy-efficient basis for addressing optimisation problems [1]. Inspired by swarm intelligence [2], we show that short-range interactions between Brownian quasiparticles induce dynamic clustering around the global minimum of a complex temperature landscape [3,4]. By varying the interaction strength and particle density, we identify a broad range of physical conditions in which collective behaviour enhances optimization accuracy. Our results highlight that the emergent collective dynamics of interacting Brownian particles provide a scalable, energy-efficient framework for unconventional computing.

[1] C. H. Bennett, Int. J. Theor. Phys. 21, 905 (1982);

[2] Bonabeau, et al, Oxford University Press (1999);

[3] German Patent Application DE 10 2023 131 171, K. Everschor-Sitte, A. Pignedoli, B. Dörschel (2023);

[4] German Patent Application DE 10 2023 131 706, K. Everschor-Sitte, A. Pignedoli, B. Dörschel (2023);

Keywords: optimization problems; Brownian computing; quasiparticles