Regensburg 2022 – wissenschaftliches Programm
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DY: Fachverband Dynamik und Statistische Physik
DY 3: Statistical Physics far from Thermal Equilibrium
DY 3.5: Vortrag
Montag, 5. September 2022, 11:00–11:15, H18
Renormalized Fluctuation Expansion for Non-Equilibrium Disordered Networks — •Michael Dick1,2,3, Alex van Meegen1,4, and Moritz Helias1,5 — 1Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-BRAIN Institute I, Jülich Research Centre, 52425 Jülich, Germany — 2Department of Computer Science 3 - Software Engineering, RWTH Aachen University, Aachen, Germany — 3Peter Grünberg Institut (PGI-1) and Institute for Advanced Simulation (IAS-1), Jülich Research Centre, 52425 Jülich, Germany — 4Institute of Zoology, University of Cologne, 50674 Cologne, Germany — 5Department of Physics, Faculty 1, RWTH Aachen University, Aachen, Germany
It is frequently hypothesized that cortical networks display hallmarks of critical dynamics. Such critical dynamics are beyond the validity of a mean-field approximation because it inherently neglects fluctuations. Thus, a renormalized theory is necessary. We consider an archetypal neural network model which displays a magnetic as well as a chaotic transition. Based on the analogue of a quantum effective action, we derive self-consistency equations for the first two renormalized Greens functions. Their self-consistent solution reveals critical slowing down near the transition to the ferromagnetic state and an optimal level of disorder which favors collective behavior. The quantitative theory explains the shape of the single-unit autocorrelation function, featuring multiple temporal scales, and the population autocorrelation function.