Antagonistic Phenomena in Network Dynamics

  title={Antagonistic Phenomena in Network Dynamics},
  author={Adilson E. Motter and Marc Timme},
  journal={Annual review of condensed matter physics},
  • A. Motter, M. Timme
  • Published 12 March 2018
  • Art
  • Annual review of condensed matter physics
Recent research on the network modeling of complex systems has led to a convenient representation of numerous natural, social, and engineered systems that are now recognized as networks of interacting parts. Such systems can exhibit a wealth of phenomena that not only cannot be anticipated from merely examining their parts, as per the textbook definition of complexity, but also challenge intuition even when considered in the context of what is now known in network science. Here we review the… 
Parity and time-reversal elucidate decisions in high-dimensional state space -- application to attractor scaling in critical Boolean networks
A general principle is demonstrated: a system's relationship to its time reversal and state-space inversion constrains its repertoire of emergent behaviors, suggesting that regulatory networks sustain many more stable phenotypes than expected by chance in standard models, inviting investigation into the biology underlying this surprising phenotypic diversity.
Geometric unfolding of synchronization dynamics on networks.
We study the synchronized state in a population of network-coupled, heterogeneous oscillators. In particular, we show that the steady-state solution of the linearized dynamics may be written as a
Complex networks of interacting stochastic tipping elements: Cooperativity of phase separation in the large-system limit.
This work analyzes the response to the perturbation of a single node in a system that initially resides in an unstable equilibrium and derives an analytical prediction for the evolution of the expectation.
Contrariety and inhibition enhance synchronization in a small-world network of phase oscillators
The nonmonotonic behavior in synchronization is due to the weakening of the defects already formed in the pure conformist and excitatory agent model in SW networks, and the optimal fraction of contrarians and inhibitors remains unchanged for the rewiring probabilities up to ∼0.15, above which synchronization falls monotonically, like the random network.
Stochastic Transport Models on Simple Networks: Phase Diagrams and Braess Paradox
It is shown that Braess’ paradox occurs in large regions of the phase space in the networks with added periodic boundary conditions and random-sequential dynamics and is also realized if intelligent particles, which individually choose their routes, use the network.
Observability and synchronization of dynamical networks: a numerical study
This work focuses on the observability and synchronization properties of dynamical networks—that is, interconnected systems where each node is modeled as an individual dynamical system and develops a Bayesian filtering framework, based on particle filtering, for application as a benchmark in observability studies.
Detecting Hidden Units and Network Size from Perceptible Dynamics
A detection matrix is introduced that suitably arranges multiple transient time series from the subset of accessible units to detect network size via matching rank constraints, applicable across system types and interaction topologies, and applies to nonstationary dynamics near fixed points.
Diversity enhanced synchronization in a small-world network of phase oscillators
In this work, we study the synchronization of a group of phase oscillators (rotors) in the small-world (SW) networks. The distribution of intrinsic angular frequency of the rotors are given by a
Validity and Limitations of the Detection Matrix to Determine Hidden Units and Network Size from Perceptible Dynamics.
  • M. Porfiri
  • Computer Science
    Physical review letters
  • 2020
A profound connection is unveiled between the rank of the detection matrix and the control-theoretic notion of observability, upon which it is concluded when and how it is feasible to exactly infer the size of a network dynamical system.
Parity and time reversal elucidate both decision-making in empirical models and attractor scaling in critical Boolean networks
A general principle is demonstrated: A system’s relationship to its time reversal and state-space inversion constrains its repertoire of emergent behaviors, and a novel attractor identification algorithm implemented for Boolean networks under stochastic dynamics is presented.


Symmetry in Complex Networks
A few interrelated concepts about graphs, such as their degree, entropy, or their symmetry/asymmetry levels are analyzed, to highlight their close relation with measures of information and entropy in Complex Networks.
Realistic control of network dynamics.
This framework permits reprogramming a network to a desired task, as well as rescuing networks from the brink of failure-which is illustrated through the mitigation of cascading failures in a power-grid network and the identification of potential drug targets in a signalling network of human cancer.
Chimera states in mechanical oscillator networks
A simple experiment with mechanical oscillators coupled in a hierarchical network is devised to show that chimeras emerge naturally from a competition between two antagonistic synchronization patterns, and a mathematical model shows that the self-organization observed is controlled by elementary dynamical equations from mechanics that are ubiquitous in many natural and technological systems.
Network synchronization landscape reveals compensatory structures, quantization, and the positive effect of negative interactions
It is shown that networks with best complete synchronization, least coupling cost, and maximum dynamical robustness, have arbitrary complexity but quantized total interaction strength, which constrains the allowed number of connections.
Interaction Control to Synchronize Non-synchronizable Networks
This paper explains how a simple binary control may localize interactions in state space and thereby synchronize networks and proposes the concept of interaction control, generalizing transient uncoupling, to induce desired collective dynamics in complex networks.
Computational models of chemical systems inspired by Braess’ paradox
This study modeled a set of reactions inspired by Braess’ paradox, an interesting phenomenon whereby the introduction of additional capacity in some simple network systems can lead to an unexpected reduction in the overall flow rate of “traffic” through the system.
Cluster synchronization and isolated desynchronization in complex networks with symmetries.
A new framework and techniques are presented and techniques for the analysis of network dynamics that shows the connection between network symmetries and cluster formation are developed that could guide the design of new power grid systems or lead to new understanding of the dynamical behaviour of networks ranging from neural to social.
Nonlocal failures in complex supply networks by single link additions
It is demonstrated that and how adding new links may not only promote but also degrade stable operation of a network, and how the resulting overloads may emerge remotely from where such a link is added, thus resulting in nonlocal failures.
Congestion induced by the structure of multiplex networks
Here, it is proved analytically that the structure of multiplex networks can induce congestion for flows that otherwise would be decongested if the individual layers were not interconnected.
Dynamic information routing in complex networks
This work identifies a generic mechanism to route information on top of collective dynamical reference states in complex networks and demonstrates the power of this generic mechanism specifically for oscillatory dynamics and analyzes how individual unit properties, the network topology and external inputs coact to systematically organize information routing.