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Seminar: Dynamics of Adaptive Networks - Summer Term 2019

Lupe
© TUB

LV-Nr. 3233 L 606 Nichtlineare Dynamik in komplexen Systemen

Prof. Dr. Eckehard Schöll, PhD
Dr. Anna Zakharova
Dr. Iryna Omelchenko Time: Tuesday 16:15 (c.t.) 
Room: EW 731
Begin: 09.04.2019 Durch den Besuch der Veranstaltung mit Vortrag und Ausarbeitung können 4 ECTS Punkte erworben werden.

The seminar offers perspectives on our current research in the area of Nonlinear Dynamics and Control. The seminar is particularly suitable for BSc and MSc students looking for a final project. Students, who want to obtain a Seminarschein, are welcome as well. In physics, chemistry, biology, technology, and social sciences, one can find many examples of networks whose topologies evolve in time. In adaptive networks, the dynamics on the nodes and the dynamics of the links between the nodes are coupled to each other, producing emergent behavior that would not be seen in static network topologies. Recent research has shown that such networks can exhibit a plethora of new phenomena which are ultimately required to describe many real-world networks. These include robust self-organization, formation of complex global topologies based on simple, local rules, plasticity as it occurs in learning processes in the brain, and the spontaneous emergence of hierarchical multicluster structures, in which an initially homogenous population of network nodes self-organizes into functionally distinct classes. In the focus of the seminar will be recent studies of adaptive networks, we will discuss the wide field of their applications, analytical studies, complex dynamics, modeling and predicting state-topology coevolution. Literature: www3.itp.tu-berlin.de/schoell/nlds/seminare/ Schedule and Organization: If you are interested in a particular topic, please contact one of the advisors. Final assignment of the topics will be done on 09.04.2019.

Zeitlicher Ablauf

Datum
Titel
Vortragender
Betreuer
09.04.
Introduction and organization

E. Schöll, A. Zakharova, I. Omelchenko
-
16.04
 
Flexibility of brain network modules

Narges Chinichian

ES
23.04.
 
Control of synchronization in power grids

Carl Totz

ES
30.04.
 
Self-similar hierarchical frequency clusters in adaptive networks of phase oscillators [BER19a]
Gabriel Cortambert

RB
07.05.
 
Controlling cluster synchronization by adapting the topology [LEH14]

Ben Böbel

JS
14.05.
  Adaptive oscillator networks with conserved overall coupling:  Sequential firing and near-synchronized states [PIC11a]
Sören Nagel

RB, IO
  Emerging meso- and macroscales from synchronization of adaptive networks [GUT11]
 

Isaak Mengesha

RB, IO
21.05.
  Noise-enhanced coupling between two oscillators with long-term plasticity [LUE16]
Max Thiele

IO
28.05.
 
 Hierarchical transitions in multiplex adaptive networks of oscillatory units [MAS18]




Felix Stoffregen

JS
04.06.
no seminar  






11.06.

 
Effect of disorder and noise in shaping the dynamics of power   grids [TUM18,TAH19]
 


Oskar Pfeffer
ES
18.06
Self-organized emergence of multi-layer structure and chimera states in dynamical networks with adaptive couplings [KAS17,KAS18a]

Jonah Friederich
 
AZ



 
The spacing principle for unlearning abnormal neuronal synchrony [POP15]
 


Gabriel Rein
IO
25.06.
 
Itinerant chimeras in an adaptive network of pulse-coupled oscillators [KAS19]

 

 
Sebastian Nagies

RB
02.07.
Chimera states of neuron networks with adaptive coupling [HUO19]

Fenja Drauschke

AZ
Wer Interesse an einem Vortrag hat, sollte sich mit den entsprechenden Betreuern in Verbindung setzen. Die Vortragsthemen werden dann spätestens in der ersten Seminarstunde am 09.04.2019 verteilt.

Literatur zu den Vorträgen

[BER19a] R. Berner, J. Fialkowski, V. Nekorkin, E. Schöll, and S. Yanchuk.  Self-similar hierarchical frequency clusters in adaptive networks of phase oscillators (2019).

[LEH14] J. Lehnert, P. Hövel, A. A. Selivanov, A. L. Fradkov, and E. Schöll, Controlling cluster synchronization by adapting the topology. Phys. Rev. E 90, 042914 (2014).

[PIC11a] C. B. Picallo and H. Riecke, Adaptive oscillator networks with conserved overall coupling: Sequential firing and near-synchronized states. Phys. Rev. E 83, 036206 (2011).

[GUT11] R. Gutiérrez, A. Amann, S. Assenza, J. Gómez-Gardeñes, V. Latora, and S. Boccaletti, Emerging Meso- and Macroscales from Synchronization of Adaptive Networks. Phys. Rev. Lett. 107, 234103 (2011).

[LUE16] L. Lücken, O. Popovych, P. Tass, and S. Yanchuk, Noise-enhanced coupling between two oscillators with long-term plasticity. Phys. Rev. E 93, 032210 (2016).

[TUM18] L. Tumash, S. Olmi, and E. Schöll, Effect of disorder and noise in shaping the dynamics of power grids, Europhys. Lett. 123, 20001 (2018).

[TAH19] H. Taher, S. Olmi, and E. Schöll, Enhancing power grid synchronization and stability through time delayed feedback control (2019).

[KAS18] D. V. Kasatkin and V. I. Nekorkin, Synchronization of chimera states in a multiplex system of phase oscillators with adaptive couplings. Chaos 28, 1054 (2018).

[MAS18] O. V. Maslennikov and V. I. Nekorkin, Hierarchical transitions in multiplex adaptive networks of oscillatory units. Chaos 28, 121101 (2018).

[BAC18a] I. Bacic, V. Klinshov, V. Nekorkin, M. Perc, and I. Franović, Inverse stochastic resonance in a system of excitable active rotators with adaptive coupling. EPL 124, 40004 (2018).

[KAS17] D. V. Kasatkin, S. Yanchuk, E. Schöll, and V. I. Nekorkin, Self-organized emergence of multi-layer structure and chimera states in dynamical networks with adaptive couplings. Phys. Rev. E 96, 062211 (2017).

[POP15] O. V. Popovych, M. N. Xenakis, and P. A. Tass, The Spacing Principle for Unlearning Abnormal Neuronal Synchrony. PLOS ONE 10, 1 (2015).

[KAS18a] D. V. Kasatkin and V. I. Nekorkin, The effect of topology on organization of synchronous behavior in dynamical networks with adaptive couplings. Eur. Phys. J. Spec. Top. 227, 1051 (2018).

[KAS19] D. V. Kasatkin, V. Klinshov, and V. I. Nekorkin, Itinerant chimeras in an adaptive network of pulse-coupled oscillators. Phys. Rev. E 99, 022203 (2019).

[HUO19] S. Huo, C. Tian, L. Kang, and Z. Liu, Chimera states of neuron networks with adaptive coupling. Nonlinear Dynamics (2019).

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