Computing bounds for entropy of stationary Z^d Markov random fields

2012/04/12 by Brian Marcus, Marcus, Brian, Ronnie Pavlov +1
Computer Science · Mathematics · #Algorithms and Data Compression #Cellular Automata and Applications #Dynamical Systems (math.DS) #FOS: Mathematics #FOS: Physical sciences #Mathematical Dynamics and Fractals #Mathematical Physics (math-ph) #Probability (math.PR)

paper · pdf · doi:10.48550/arxiv.1204.2612

openalex publication_date 2012/04/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

For any stationary \mZ^d-Gibbs measure that satisfies strong spatial mixing, we obtain sequences of upper and lower approximations that converge to its entropy. In the case, d=2, these approximations are efficient in the sense that the approximations are accurate to within ε and can be computed in time polynomial in 1/ε.

Citations

• Strong spatial mixing for list coloring of graphs

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