Analytically solvable processes on networks

Analytically solvable processes on networks

We introduce a broad class of analytically solvable processes on networks. In the special case, they reduce to random walk and consensus process, the two most basic processes on networks. Our class differs from previous models of interactions (such as the stochastic Ising model, cellular automata, i...

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Veröffentlicht in:Physical review. E, Statistical, nonlinear, and soft matter physics Statistical, nonlinear, and soft matter physics, 2011-07, Vol.84 (1 Pt 2), p.016104-016104, Article 016104
Hauptverfasser: Smilkov, Daniel, Kocarev, Ljupco
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Linear Models
Markov Chains
Models, Theoretical
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container_title Physical review. E, Statistical, nonlinear, and soft matter physics
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creator Smilkov, Daniel
Kocarev, Ljupco
description We introduce a broad class of analytically solvable processes on networks. In the special case, they reduce to random walk and consensus process, the two most basic processes on networks. Our class differs from previous models of interactions (such as the stochastic Ising model, cellular automata, infinite particle systems, and the voter model) in several ways, the two most important being (i) the model is analytically solvable even when the dynamical equation for each node may be different and the network may have an arbitrary finite graph and influence structure and (ii) when local dynamics is described by the same evolution equation, the model is decomposable, with the equilibrium behavior of the system expressed as an explicit function of network topology and node dynamics.
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Markov Chains
Models, Theoretical
title Analytically solvable processes on networks
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