DFG-Sonderforschungsbereich 555 "Komplexe Nichtlineare Prozesse"

Fritz-Haber-Institut der Max-Planck-Gesellschaft, Max-Delbrück-Centrum für molekulare Medizin Berlin, Otto-von-Guericke-Universität Magdeburg, Physikalisch-Technische Bundesanstalt, Technische Universität Berlin

"Complex Nonlinear Processes in Chemistry and Biology"

Honorary Chairman: Gerhard Ertl

Organizers:M. Bär, H. Engel, M. Falcke, M. Hauser, A. S. Mikhailov, P. Plath, H. Stark
Address:Richard-Willstätter-Haus, Faradayweg 10, 14195 Berlin-Dahlem. (Click here for a description how to get there.)

For information please contact Oliver Rudzick, Tel. (030) 8413 5300, rudzick@fhi-berlin.mpg.de.

[This is the old program from SS 2008. The current program and contact information can be found here.]

18 April 2008, 16:00

Alessandro Torcini (Istituto dei Sistemi Complessi, CNR, Sesto Fiorentino, Italy)
Stability of the splay state in pulse-coupled networks [Abstract]

09 May 2008, 16:00

Andreas Bausch (Biophysik (E22), Technische Universität München)
Physics of complex actin networks: from molecules to networks [Abstract]

30 May 2008, 16:00

Otto E. Rössler (Institut für Physikalische und Theoretische Chemie, Universität Tübingen)
New statistical mechanics - Clausisus and Chandrasekhar [Abstract]

06 June 2008, 16:00

Hiroya Nakao (Abteilung Physikalische Chemie, Fritz-Haber-Institut, Berlin)
Diffusion-induced instabilities on random networks

I will talk about two types of diffusion-induced instabilities exhibited by reaction-diffusion systems on networks.
(1) Turing patterns formed by activator-inhibitor systems on networks. As in the ordinary continuous media, when the inhibitor diffuses sufficiently faster than the activator, the uniform state of the system is destabilized and non-uniform patterns are formed. We formulate general linear stability analysis using the Laplacian eigenvectors of the network, and present numerical simulations of the Mimura-Murray prey-predator model on random networks. The final stationary patterns are largely different from the critical modes at the onset of instability. We show that these patterns can be explained based on a simple mean-field approximation of random networks.
(2) Diffusion-induced chaos exhibited by coupled limit-cycle oscillators on random networks. In this case, the uniformly oscillating states are destabilized and inhomogeneous chaotic states on the network emerge. I will briefly explain that the resulting chaotic states can be understood, to a certain extent, again by using the mean-field approximation.

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last modified: May 30, 2008 / Oliver Rudzick

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