RG Nonlinear Dynamics in Complex Networks
- © TU Berlin
Team leader: Prof. Dr. Anna Mandel-Zakharova, Ph.D.
We investigate nonlinear dynamical systems, noise-induced dynamics, control of neural networks, synchronization patterns in dynamical networks, and stochastic effects in networks with time delay.
Project A1 (CRC 910). Control and dynamics of multilayer networks
The objective of the present project is to investigate emergent phenomena and their control in multilayer networks that offer better representation of the topology and dynamics of real-world systems in comparison with one-layer structures. We particularly aim to disclose the interconnections between multiplexing, communication delay, and stochasticity to develop efficient control strategies. For this purpose we study noise- and delay-induced dynamics as well as complex deterministic effects and synchronization patterns, and explore their underlying mechanisms in multilayer networks. We intend to develop control methods based on solely (i) multiplexing and on the (ii) interplay of multiplexing with time delay or/and noise.
Review of the book "Chimera Patterns in Networks" in Physics Today
Open for Submissions: In Memory of Vadim S. Anishchenko: Statistical Physics and Nonlinear Dynamics of Complex Systems
- © private
Submission Deadline: May 1, 2021
Chaos: An Interdisciplinary Journal of Nonlinear Science will be
publishing a Focus Issue titled In Memory of Vadim S. Anishchenko:
Statistical Physics and Nonlinear Dynamics of Complex Systems.
This focus issue is dedicated to the memory of Vadim S. Anishchenko, an eminent scientist in the field of nonlinear dynamics of deterministic and stochastic systems. Vadim's invaluable contributions to the field include the theory of nonlinear oscillations, bifurcations, dynamical chaos, synchronization, stochastic processes and noise in nonlinear systems, in particular stochastic resonance and coherence resonance, partial synchronization patterns in complex networks of coupled oscillators and coupled maps including chimera states, and applications of methods of nonlinear dynamics in biology and medicine. He spent most of his life as a Professor and Head of Radiophysics and Nonlinear Dynamics at Saratov State University, Russia, but he had also a strong affinity to Germany. For more than thirty years, he had been a regular visiting scientist in Berlin as an Alexander von Humboldt Awardee and later as Principal Investigator of the Collaborative Research Center CRC 910: Control of Self-Organizing Nonlinear Systems, where he led the first Russian Project in a German CRC. This Focus Issue will comprise a collection of articles related to Vadim Anishchenko‘s work, contributed by his colleagues.
Anna Mandel-Zakharova (TU Berlin)
Galina Strelkova (Saratov State University)
Eckehard Schoell (TU Berlin)
Juergen Kurths (Potsdam Institute for Climate Impact Research and Humboldt University of Berlin)
- © Springer
Chimera Patterns in Networks, Anna Zakharova, Springer International Publishing, ISBN 978-3-030-21713-6, (2020)
This is the first book devoted to chimera states - peculiar partial synchronization patterns in networks. Providing an overview of the state of the art in research on this topic, it explores how these hybrid states, which are composed of spatially separated domains of synchronized and desynchronized behavior, arise surprisingly in networks of identical units and symmetric coupling topologies. The book not only describes various types of chimeras, but also discusses the role of time delay, stochasticity, and network topology for these synchronization-desynchronization patterns. Moreover, it addresses the question of robustness and control of chimera states, which have various applications in physics, biology, chemistry, and engineering.
This book is intended for researchers with a background in physics, applied mathematics, or engineering. Of great interest to specialists working on related problems, it is also a valuable resource for newcomers to the field and other scientists working on the control of spatio-temporal patterns.