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
Seminar
"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.]
Alessandro Torcini
(Istituto dei Sistemi Complessi, CNR, Sesto Fiorentino, Italy)
Stability of the splay state in pulse-coupled networks
[Abstract]
Andreas Bausch
(Biophysik (E22), Technische Universität München)
Physics of complex actin networks: from molecules to networks
[Abstract]
Otto E. Rössler
(Institut für Physikalische und Theoretische Chemie, Universität Tübingen)
New statistical mechanics - Clausisus and Chandrasekhar
[Abstract]
Hiroya Nakao
(Abteilung Physikalische Chemie, Fritz-Haber-Institut, Berlin)
Diffusion-induced instabilities on random networks
Abstract:
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.
Download the seminar program as PDF (ca. 96 kB)
last modified: May 30, 2008 / Oliver Rudzick