Dynamic message-passing approach for kinetic spin models with reversible dynamics.
A method to approximately close the dynamic cavity equations for synchronous reversible dynamics on a locally treelike topology is presented. The method builds on (a) a graph expansion to eliminate loops from the normalizations of each step in the dynamics and (b) an assumption that a set of auxilary probability distributions on histories of pairs of spins mainly have dependencies that are local in time. The closure is then effectuated by projecting these probability distributions on n-step Markov processes. The method is shown in detail on the level of ordinary Markov processes (n=1) and outlined for higher-order approximations (n>1). Numerical validations of the technique are provided for the reconstruction of the transient and equilibrium dynamics of the kinetic Ising model on a random graph with arbitrary connectivity symmetry.
Department of Computational Biology, AlbaNova University Centre, SE-106 91 Stockholm, Sweden.
Gino
G
Del Ferraro
Department of Computational Biology, AlbaNova University Centre, SE-106 91 Stockholm, Sweden.|ACCESS Linnaeus Centre, KTH-Royal Institute of Technology, SE-100 44 Stockholm, Sweden.|Departments of Information and Computer Science and Applied Physics and Aalto Science Institute, Aalto University, P. O. Box 15400, FI-00076 Aalto, Finland.
Erik
E
Aurell
D007700:Kinetics; D008390:Markov Chains; D008962:Models, Theoretical; D011336:Probability