For every fixed k ≥ 2 the cyclic attractor detection problem is NP-complete precisely when the local Boolean function class contains majority-like self-dual rules or mixed conjunctive-disjunctive monotone families, and polynomial-time solvable in all other Post classes.
Complex Networks
5 Pith papers cite this work. Polarity classification is still indexing.
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Introduces graph-to-image prediction of per-node dynamic stability landscapes in oscillator networks from topology, releases two 10k-graph datasets, and shows GNN-CNN models achieve good accuracy with cross-size generalization.
Logarithmic centroid method recovers adiabatic Kramers scaling in coherence resonance for SRK model with Feller noise despite bathtub effect, identifies strong-noise breakdown, and demonstrates noise-induced transition to functional synchronization in gap-junction coupled systems.
Coupling threshold for extreme events in networked systems shows a power-law dependence on edge density and algebraic connectivity that holds across systems and extreme-event mechanisms.
Simulations show information overload decreases source localization effectiveness in networks, with Erdős-Rényi graphs more resilient than Barabási-Albert ones and a reversal where less dense networks perform better under strong overload.
citing papers explorer
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Cyclic Attractor Detection in Boolean Network Dynamics under Local Logical Constraints
For every fixed k ≥ 2 the cyclic attractor detection problem is NP-complete precisely when the local Boolean function class contains majority-like self-dual rules or mixed conjunctive-disjunctive monotone families, and polynomial-time solvable in all other Post classes.
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Learning Dynamic Stability Landscapes in Synchronization Networks
Introduces graph-to-image prediction of per-node dynamic stability landscapes in oscillator networks from topology, releases two 10k-graph datasets, and shows GNN-CNN models achieve good accuracy with cross-size generalization.
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Breakdown of Adiabatic Scaling and Noise-Induced Functional Synchronization in Deeply Quiescent Excitable Systems
Logarithmic centroid method recovers adiabatic Kramers scaling in coherence resonance for SRK model with Feller noise despite bathtub effect, identifies strong-noise breakdown, and demonstrates noise-induced transition to functional synchronization in gap-junction coupled systems.
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Complex network topological and spectral determinants of extreme events
Coupling threshold for extreme events in networked systems shows a power-law dependence on edge density and algebraic connectivity that holds across systems and extreme-event mechanisms.
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Nonlinear dynamics of information overload: Impact on source localization in complex networks
Simulations show information overload decreases source localization effectiveness in networks, with Erdős-Rényi graphs more resilient than Barabási-Albert ones and a reversal where less dense networks perform better under strong overload.