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Wednesday, August 08, 2012
3:00 PM - 4:00 PM
CNLS Conference Room (TA-3, Bldg 1690)


Maxentropic Markov Chains

Andrew M. Fraser
Los Alamos National Laboratory

I describe an algorithm that calculates, for any strongly connected directed graph, the set of branching probabilities for the edges that yields a Markov process with the maximum possible entropy rate. I developed the algorithm as a tool for quantifying uncertainty about an equation of state. I will introduce the entropy maximization problem in terms of Information Theory as I first encountered it in the homework problems for chapter 4 of Cover and Thomas’ text (problems 4.7 and 4.16 in the second edition). Although I will present the set of polynomial equations from Graph Theory that the solution must satisfy, the operationally useful algorithm relies on the power method for calculating eigenvalues.

Host: Garrett Kenyon,, 7-1900, IS & T