Collective dynamics on small-world networks emerge in a broad range of systems with their spectra characterizing fundamental asymptotic features. Here we derive analytic mean field predictions for the spectra of small-world models that systematically interpolate between regular and random topologies by varying their randomness. These theoretical predictions agree well with the actual spectra (obtained by numerical diagonalization) for undirected and directed networks and from fully regular to strongly random topologies. These results may provide analytical insights to empirically found features of dynamics on small-world networks from various research fields, including biology, physics, engineering and social science
Mean-field analysis is an important tool for understanding dynamics on complex networks. However, su...
AbstractNew classes of random graphs have recently been shown to exhibit the small world phenomenon—...
We use techniques from applied matrix analysis to study small world cutoff in a Markov chain. Our mo...
Collective dynamics on small-world networks emerge in a broad range of systems with their spectra ch...
Complex networks exhibit a wide range of collective dynamic phenomena, including synchronization, di...
Mean-field analysis is an important tool for understanding dynamics on complex networks. However, su...
The small-world network model is a simple model of the structure of social networks, which simultan...
The study of spectral behavior of networks has gained enthusiasm over the last few years. In particu...
This chapter contains a brief introduction to complex networks, and in particular to small world and...
The small-world phenomenon formalized in this article as the coincidence of high local clustering an...
We compute spectra of symmetric random matrices describing graphs with general modular structure and...
New classes of random graphs have recently been shown to exhibit the small world phenomenon - they a...
We report on our numerical studies of the Axelrod model for social influence in small-world networks...
The famous Watts–Strogatz (WS) small-world network model does not approach the Erdős–Rényi (ER) rand...
We use techniques from applied matrix analysis to study small world cutoff in a Markov chain. Our mo...
Mean-field analysis is an important tool for understanding dynamics on complex networks. However, su...
AbstractNew classes of random graphs have recently been shown to exhibit the small world phenomenon—...
We use techniques from applied matrix analysis to study small world cutoff in a Markov chain. Our mo...
Collective dynamics on small-world networks emerge in a broad range of systems with their spectra ch...
Complex networks exhibit a wide range of collective dynamic phenomena, including synchronization, di...
Mean-field analysis is an important tool for understanding dynamics on complex networks. However, su...
The small-world network model is a simple model of the structure of social networks, which simultan...
The study of spectral behavior of networks has gained enthusiasm over the last few years. In particu...
This chapter contains a brief introduction to complex networks, and in particular to small world and...
The small-world phenomenon formalized in this article as the coincidence of high local clustering an...
We compute spectra of symmetric random matrices describing graphs with general modular structure and...
New classes of random graphs have recently been shown to exhibit the small world phenomenon - they a...
We report on our numerical studies of the Axelrod model for social influence in small-world networks...
The famous Watts–Strogatz (WS) small-world network model does not approach the Erdős–Rényi (ER) rand...
We use techniques from applied matrix analysis to study small world cutoff in a Markov chain. Our mo...
Mean-field analysis is an important tool for understanding dynamics on complex networks. However, su...
AbstractNew classes of random graphs have recently been shown to exhibit the small world phenomenon—...
We use techniques from applied matrix analysis to study small world cutoff in a Markov chain. Our mo...