Oscillations of complex networks

A complex network processing information or physical flows is usually characterized by a number of macroscopic quantities such as the diameter and the betweenness centrality. An issue of significant theoretical and practical interest is how such a network responds to sudden changes caused by attacks or disturbances. By introducing a model to address this issue, we find that, for a finite-capacity network, perturbations can cause the network to \emph{oscillate} persistently in the sense that the characterizing quantities vary periodically or randomly with time. We provide a theoretical estimate of the critical capacity-parameter value for the onset of the network oscillation. The finding is expected to have broad implications as it suggests that complex networks may be structurally highly dynamic.Comment: 4 pages, 4 figures. submitte

The multiple effects of gradient coupling on network synchronization

Recent studies have shown that synchronizability of complex networks can be significantly improved by asymmetric couplings, and increase of coupling gradient is always in favor of network synchronization. Here we argue and demonstrate that, for typical complex networks, there usually exists an optimal coupling gradient under which the maximum network synchronizability is achieved. After this optimal value, increase of coupling gradient could deteriorate synchronization. We attribute the suppression of network synchronization at large gradient to the phenomenon of network breaking, and find that, in comparing with sparsely connected homogeneous networks, densely connected heterogeneous networks have the superiority of adopting large gradient. The findings are supported by indirect simulations of eigenvalue analysis and direct simulations of coupled nonidentical oscillator networks.Comment: 4 pages, 4 figure

A robust relativistic quantum two-level system with edge-dependent currents and spin polarization

This work was supported by AFOSR under Grant No. FA9550-15-1-0151. LH was supported by NSFC under Grant No. 11422541.Peer reviewedPostprin

Transition to turbulence in Taylor-Couette ferrofluidic flow

Y.D. was supported by Basic Science Research Program of the Ministry of Education, Science and Technology under Grant No. NRF-2013R1A1A2010067. Y.C.L. was supported by AFOSR under Grant No. FA9550-12-1-0095.Peer reviewedPublisher PD

Ring bursting behavior en route to turbulence in quasi two-dimensional Taylor-Couette flows

We investigate the quasi two-dimensional Taylor-Couette system in the regime where the radius ratio is close to unity - a transitional regime between three and two dimensions. By systematically increasing the Reynolds number we observe a number of standard transitions, such as one from the classical Taylor vortex flow (TVF) to wavy vortex flow (WVF), as well as the transition to fully developed turbulence. Prior to the onset of turbulence we observe intermittent burst patterns of localized turbulent patches, confirming the experimentally observed pattern of very short wavelength bursts (VSWBs). A striking finding is that, for Reynolds number larger than the onset of VSWBs, a new type of intermittently bursting behaviors emerge: burst patterns of azimuthally closed rings of various orders. We call them ring-burst patterns, which surround the cylinder completely but remain localized and separated by non-turbulent mostly wavy structures in the axial direction. We use a number of quantitative measures, including the cross-flow energy, to characterize the ring-burst patterns and to distinguish them from the background flow. The ring-burst patterns are interesting because it does not occur in either three- or two-dimensional Taylor-Couette flow: it occurs only in the transition, quasi two-dimensional regime of the system, a regime that is less studied but certainly deserves further attention so as to obtain deeper insights into turbulence

Reconstructing propagation networks with natural diversity and identifying hidden sources

Our ability to uncover complex network structure and dynamics from data is fundamental to understanding and controlling collective dynamics in complex systems. Despite recent progress in this area, reconstructing networks with stochastic dynamical processes from limited time series remains to be an outstanding problem. Here we develop a framework based on compressed sensing to reconstruct complex networks on which stochastic spreading dynamics take place. We apply the methodology to a large number of model and real networks, finding that a full reconstruction of inhomogeneous interactions can be achieved from small amounts of polarized (binary) data, a virtue of compressed sensing. Further, we demonstrate that a hidden source that triggers the spreading process but is externally inaccessible can be ascertained and located with high confidence in the absence of direct routes of propagation from it. Our approach thus establishes a paradigm for tracing and controlling epidemic invasion and information diffusion in complex networked systems.Comment: 20 pages and 5 figures. For Supplementary information, please see http://www.nature.com/ncomms/2014/140711/ncomms5323/full/ncomms5323.html#