arXiv2007
Associated to a IFS one can consider a continuous map $\hatσ : [0,1]\times Σ\to [0,1]\times Σ$, defined by $\hatσ(x,w)=(τ_{X_{1}(w)}(x), σ(w))$ were $Σ=\{0,1, ..., d-1\}^{\mathbb{N}}$, $σ: Σ\to Σ$ is given by$σ(w_{1},w_{2},w_{3},...)=(w_{2},w_{3},w_{4}...)$ and $X_{k} : Σ\to \{0,1, ..., n-1\}$ is the projection on the coordinate $k$. A $ρ$-weighted system, $ρ\geq 0$, is a weighted system $([0,1], τ_{i}, u_{i})$ such that there exists a positive bounded function $h : [0,1] \to \mathbb{R}$ and probability $ν$ on $[0,1]$ satisfying $ P_{u}(h)=ρh, \quad P_{u}^{*}(ν)=ρν$. A probability $\hatν$ on $[0,1]\times Σ$ is called holonomic for $\hatσ$ if $ \int g \circ \hatσ d\hatν= \int g d\hatν, \forall g \in C([0,1])$. We denote the set of holonomic probabilities by ${\cal H}$. Via disintegration, holonomic probabilities $\hatν$ on $[0,1]\times Σ$ are naturally associated to a $ρ$-weighted system. More precisely, there exist a probability $ν$ on $[0,1]$ and $u_i, i\in\{0, 1,2,..,d-1\}$ on $[0,1]$, such that is $P_{u}^*(ν)=ν$. We consider holonomic ergodic probabilities. For a holonomic probability we define entropy. Finally, we analyze the problem: given $ϕ\in \mathbb{B}^{+}$, find the solution of the maximization pressure problem $$p(ϕ)=$$