The sectional curvature of the infinite dimensional manifold of Hölder equilibrium probabilities

Abstract Here we consider the discrete time dynamics described by a transformation $T:M \to M$ , where T is either the action of shift $T=\sigma$ on the symbolic space $M=\{1,2, \ldots,d\}^{\mathbb{N}}$ , or, T describes the action of a d to 1 expanding transformation $T:S^1 \to S^1$ of class $C^{1+\alpha}$ (for example $x \to T(x) =\mathrm{d} x $ (mod 1)), where $M=S^1$ is the unit circle. It is known that the infinite-dimensional manifold $\mathcal{N}$ of Hölder equilibrium probabilities is an analytical manifold and carries a natural Riemannian metric. Given a certain normalized Hölder potential A denote by $\mu_A \in \mathcal{N}$ the associated equilibrium probability. The set of tangent vectors X (functions $X: M \to \mathbb{R}$ ) to the manifold $\mathcal{N}$ at the point µ A (a subspace of the Hilbert space $L^2(\mu_A)$ ) coincides with the kernel of the Ruelle operator for the normalized potential A . The Riemannian norm $|X|=|X|_A$ of the vector X , which is tangent to $\mathcal{N}$ at the point µ A , is described via the asymptotic variance, that is, satisfies $ |X|^2 = \langle X, X \rangle = \lim_{n \to \infty} \frac{1}{n} \int (\sum_{i=0}^{n-1} X\circ T^i )^2 \,\mathrm{d} \mu_A$ . Consider an orthonormal basis X i , $i \in \mathbb{N}$ , for the tangent space at µ A . For any two orthonormal vectors X and Y on the basis, the curvature $K(X,Y)$ is \begin{equation*}K(X,Y) = \frac{1}{4}[ \sum_{i=1}^\infty (\int X Y X_i \,\mathrm{d} \mu_A)^2 - \sum_{i=1}^\infty \int X^2 X_i \,\mathrm{d} \mu_A \int Y^2 X_i \,\mathrm{d} \mu_A ].\end{equation*} When the equilibrium probabilities µ A is the set of invariant Markov probabilities on $\{0,1\}^{\mathbb{N}}\subset \mathcal{N}$ , introducing an orthonormal basis $\hat{a}_y$ , indexed by finite words y , we show explicit expressions for $K(\hat{a}_x,\hat{a}_z)$ , which is a finite sum. These values can be positive or negative depending on A and the words x and z . Words $x,z$ with large length can eventually produce large negative curvature $K(\hat{a}_x,\hat{a}_z)$ . If $x, z$ do not begin with the same letter, then $K(\hat{a}_x,\hat{a}_z)=0$ .

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Publication Details

Journal
Proceedings of the Edinburgh Mathematical Society
Published
2024-12-18
DOI
https://doi.org/10.1017/s0013091524000725
Primary Topic
Mathematical Dynamics and Fractals
Type
article
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article

The sectional curvature of the infinite dimensional manifold of Hölder equilibrium probabilities

Artur O. Lopes, Rafael O. Ruggiero
Proceedings of the Edinburgh Mathematical Society
Mathematical Dynamics and Fractals
article

The sectional curvature of the infinite dimensional manifold of Hölder equilibrium probabilities

Artur O. Lopes, Rafael O. Ruggiero
article en

Abstract

Abstract Here we consider the discrete time dynamics described by a transformation $T:M \to M$ , where T is either the action of shift $T=\sigma$ on the symbolic space $M=\{1,2, \ldots,d\}^{\mathbb{N}}$ , or, T describes the action of a d to 1 expanding transformation $T:S^1 \to S^1$ of class $C^{1+\alpha}$ (for example $x \to T(x) =\mathrm{d} x $ (mod 1)), where $M=S^1$ is the unit circle. It is known that the infinite-dimensional manifold $\mathcal{N}$ of Hölder equilibrium probabilities is an analytical manifold and carries a natural Riemannian metric. Given a certain normalized Hölder potential A denote by $\mu_A \in \mathcal{N}$ the associated equilibrium probability. The set of tangent vectors X (functions $X: M \to \mathbb{R}$ ) to the manifold $\mathcal{N}$ at the point µ A (a subspace of the Hilbert space $L^2(\mu_A)$ ) coincides with the kernel of the Ruelle operator for the normalized potential A . The Riemannian norm $|X|=|X|_A$ of the vector X , which is tangent to $\mathcal{N}$ at the point µ A , is described via the asymptotic variance, that is, satisfies $ |X|^2 = \langle X, X \rangle = \lim_{n \to \infty} \frac{1}{n} \int (\sum_{i=0}^{n-1} X\circ T^i )^2 \,\mathrm{d} \mu_A$ . Consider an orthonormal basis X i , $i \in \mathbb{N}$ , for the tangent space at µ A . For any two orthonormal vectors X and Y on the basis, the curvature $K(X,Y)$ is \begin{equation*}K(X,Y) = \frac{1}{4}[ \sum_{i=1}^\infty (\int X Y X_i \,\mathrm{d} \mu_A)^2 - \sum_{i=1}^\infty \int X^2 X_i \,\mathrm{d} \mu_A \int Y^2 X_i \,\mathrm{d} \mu_A ].\end{equation*} When the equilibrium probabilities µ A is the set of invariant Markov probabilities on $\{0,1\}^{\mathbb{N}}\subset \mathcal{N}$ , introducing an orthonormal basis $\hat{a}_y$ , indexed by finite words y , we show explicit expressions for $K(\hat{a}_x,\hat{a}_z)$ , which is a finite sum. These values can be positive or negative depending on A and the words x and z . Words $x,z$ with large length can eventually produce large negative curvature $K(\hat{a}_x,\hat{a}_z)$ . If $x, z$ do not begin with the same letter, then $K(\hat{a}_x,\hat{a}_z)=0$ .

Proceedings of the Edinburgh Mathematical SocietyVol. 68(2)
Universidade Federal do Rio Grande do Sul (BR), Pontifícia Universidade Católica do Rio de Janeiro (BR)
Openalex Percentile: Top 61%
Mathematical Dynamics and Fractals
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