Resolving Markov Chains Onto Bernoulli Shifts Via Positive Polynomials

Part A. Resolving Markov Chains onto Bernoulli Shifts: Introduction Weighted graphs and polynomial matrices The main results Markov chains and regular isomorphism Necessity of the conditions Totally conforming eigenvectors and the one-variable case Splitting the conforming eigenvector in the one-variable case Totally conforming eigenvectors for the general case Splitting the conforming eigenvector in the general case Bibliography Part B. On Large Powers of Positive Polynomials in Several Variables: Introduction Structure of ${\mathbf{Log}}({\mathbf(p}^{\mathbf n})$ Entropy and equilibrium distributions for ${\mathbf w}\in {\mathbf W}({\mathbf p})$ Equilibrium distributions and coefficients of ${\mathbf(p}^{\mathbf n})$ Proofs of the estimates Bibliography