Title: Thermodynamic Insights into Network Dynamics: Statistical Mechanics Perspective
Abstract: Our study delves into the thermodynamic behaviors of extensive walks on non-random, connected graphs with potential random alterations and transportation noise. It employs statistical mechanics to gauge structural attributes crucial for network dynamics, revealing a Fermi–Dirac distribution of node fugacity in response to modifications. Notably, nodes with lower centrality are predisposed to future alterations. The analysis extends to finite graphs, emphasizing the applicability beyond random structures. This approach sheds light on complex network dynamics, especially in urban environments, elucidating the impacts of structural irregularities on mobility patterns. Ultimately, the research elucidates the statistical mechanics governing network evolution, crucial for understanding and optimizing complex systems.
Bio: Dr Dimitri Volchenkov is a Professor of Applied Mathematics and Statistics at the Texas Tech University (USA), former Chair Professor at the Artificial Intelligence Key Laboratory of Sichuan Province, School of Automation and Information Engineering, Sichuan University of Science and Engineering (China), former qualified professor in France and Germany, admitted as the TTU SIAM professor of the year 2021/2022, “Nationally recognized talent” of China (“1000 Talent Plan of China”), awarded by the G. Zaslavsky award in Nonlinear Science and Complexity (USA), Cheung Kong Scholarship (China), Alexander von Humboldt and Volkswagen Fellowships (Germany), NATO/OTAN and C.N.R.S Fellowships (France), George Soros Fellowship (USA), and Scientists Federal Awards (Russia).