activity
20072011
most citedMaster Stability Functions for Coupled Near-Identical Dynamical Systems

179 citations · 313 across the 6 of their papers we have counts for

collaborators

6 papers

nlin.CD201186 cited

Robustness of Optimal Synchronization in Real Networks

Bhargava Ravoori, Adam B. Cohen, Jie Sun +3

Experimental studies of synchronization properties on networks with controlled connection topology can provide powerful insights into the physics of complex networks. Here, we repo…

nlin.CD2008179 cited

Master Stability Functions for Coupled Near-Identical Dynamical Systems

Jie Sun, Erik M. Bollt, Takashi Nishikawa

We derive a master stability function (MSF) for synchronization in networks of coupled dynamical systems with small but arbitrary parametric variations. Analogous to the MSF for id…

physics.data-an200810 cited

Dynamic Computation of Network Statistics via Updating Schema

Jie Sun, James P. Bagrow, Erik M. Bollt +1

In this paper we derive an updating scheme for calculating some important network statistics such as degree, clustering coefficient, etc., aiming at reduce the amount of computatio…

cond-mat.dis-nn20082 cited

Sequence Nets

Jie Sun, Takashi Nishikawa, Daniel ben-Avraham

We study a new class of networks, generated by sequences of letters taken from a finite alphabet consisting of letters (corresponding to types of nodes) and a fixed set of…

nlin.CD200823 cited

Constructing Generalized Synchronization Manifolds by Manifold Equation

Jie Sun, Erik M. Bollt, Takashi Nishikawa

Full understanding of synchronous behavior in coupled dynamical systems beyond the identical case requires an explicit construction of the generalized synchronization manifold, whe…

q-fin.GN200713 cited

Phase transition in the rich-get-richer mechanism due to finite-size effects

James P. Bagrow, Jie Sun, Daniel ben-Avraham

The rich-get-richer mechanism (agents increase their ``wealth'' randomly at a rate proportional to their holdings) is often invoked to explain the Pareto power-law distribution obs…