Selected article for: "field approximation and mean field"

Author: Machado, David; Mulet, Roberto
Title: From random point processes to hierarchical Cavity Master Equations for the stochastic dynamics of disordered systems in Random Graphs: Ising models and epidemics
  • Cord-id: lyeaw4zr
  • Document date: 2021_6_28
  • ID: lyeaw4zr
    Snippet: We start from the Theory of Random Point Processes to derive n-point coupled master equations describing the continuous dynamics of discrete variables in random graphs. These equations constitute a hierarchical set of approximations that generalize and improve the Cavity Master Equation (CME) recently obtained in other publications. Our derivation clarifies some of the hypotheses and approximations that originally lead to the CME, considered now as the first order of a more general technique. We
    Document: We start from the Theory of Random Point Processes to derive n-point coupled master equations describing the continuous dynamics of discrete variables in random graphs. These equations constitute a hierarchical set of approximations that generalize and improve the Cavity Master Equation (CME) recently obtained in other publications. Our derivation clarifies some of the hypotheses and approximations that originally lead to the CME, considered now as the first order of a more general technique. We tested the new scheme in the dynamics of three models defined over diluted graphs: the Ising ferromagnet, the Viana-Bray spin-glass and the susceptible-infectious-susceptible model for epidemics. In the first two, the new equations perform similarly to the best-known approaches in the literature. In the latter, they outperform the well-known Pair Quenched Mean-Field Approximation.

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