English

A formula for the Entropy of the Convolution of Gibbs probabilities on the circle

Dynamical Systems 2018-07-04 v3 Probability

Abstract

Consider the transformation T:S1S1T:S^1 \to S^1, such that T(x)=2xT(x)=2\, x (mod 1), and where S1S^1 is the unitary circle. Suppose J:S1RJ:S^1 \to \mathbb{R} is Holder continuous and positive, and moreover that, for any yS1y\in S^1, we have that xsuch thatT(x)=yJ(x)=1.\sum_{x\,\,\text{such that}\,\,\, T(x)= y} \, J(x)=1. We say that ρ\rho is a Gibbs probability for the Holder continuous potential logJ\log J, if LlogJ(ρ)=ρ,\mathcal{L}_{\log J}^* \,(\rho)=\rho , where LlogJ\mathcal{L}_{\log J} is the Ruelle operator for logJ\log J. We call JJ the Jacobian of ρ\rho. Suppose ν=μ1μ2\nu=\mu_1*\mu_2 is the convolution of two Gibbs probabilities μ1\mu_1 and μ2\mu_2 associated, respectively, to logJ1\log J_1 and logJ2\log J_2. We show that ν\nu is also Gibbs and its Jacobian J~\tilde{J} is given by J~(u)=J1(ux)dμ2(x)\tilde{J}(u) = \int J_1(u-x) d \mu_2(x) In this case, the entropy h(ν)h(\nu) is given by the expression h(ν)=[log(J1(r+sx)dμ2(x))dμ2(r)]dμ1(s). h(\nu) = - \int\,[\,\,\int\, \log \,(\,\int J_1(r+s-x) d \mu_2(x)\,) \, d \mu_2(r)\,\, ]\,\,d \mu_1 (s). For a fixed μ2\mu_2 we consider differentiable variations μ1t\mu_1^t, t(ϵ,ϵ)t \in (-\epsilon,\epsilon), of μ1\mu_1 on the Banach manifold of Gibbs probabilities, where μ10=μ1\mu_1^0=\mu_1, and we estimate the derivative of the entropy h(μ1tμ2)h(\mu_1^t * \mu_2) at t=0t=0. We also present an expression for the Jacobian of the convolution of a Gibbs probability ρ\rho with the invariant probability with support on a periodic orbit of period two. This expression is based on the Jacobian of ρ\rho and two Radon-Nidodym derivatives.

Keywords

Cite

@article{arxiv.1702.03134,
  title  = {A formula for the Entropy of the Convolution of Gibbs probabilities on the circle},
  author = {Artur O. Lopes},
  journal= {arXiv preprint arXiv:1702.03134},
  year   = {2018}
}