Papers › Fast algorithm to identify cluster synchrony through fibration symmetries in large...
Fast algorithm to identify cluster synchrony through fibration symmetries in large information-processing networks
Higor S. Monteiro, Ian Leifer, Saulo D. S. Reis, José S. Andrade, Jr., Hernan A. Makse
Recent studies revealed an important interplay between the detailed structure of fibration symmetric circuits and the functionality of biological and non-biological networks within which they have be identified. The presence of these circuits in complex networks are directed related to the phenomenon of cluster synchronization, which produces patterns of synchronized group of nodes. Here we present a fast, and memory efficient, algorithm to identify fibration symmetries over information-processing networks. This algorithm is specially suitable for large and sparse networks since it has runtime of complexity O(MlogN) and requires O(M+N) of memory resources, where N and M are the number of nodes and edges in the network, respectively. We propose a modification on the so-called refinement paradigm to identify circuits symmetrical to information flow (i.e., fibers) by finding the coarsest refinement partition over the network. Finally, we show that the presented algorithm provides an optimal procedure for identifying fibers, overcoming the current approaches used in the literature.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections