[guided]The purpose of this step is to turn a symbolic itinerary into an actual orbit point. Fix an admissible sequence $i = (i_n)_{n \in \mathbb Z} \in \Sigma_A$. For an integer $N \geq 0$, define
\begin{align*}
K_N(i) := \bigcap_{n=-N}^{N} f^{-n}(R_{i_n}).
\end{align*}
A point $x \in K_N(i)$ is a point whose orbit follows the prescribed rectangles from time $-N$ through time $N$: explicitly, $f^n(x) \in R_{i_n}$ for every $-N \leq n \leq N$.
We need two facts about $K_N(i)$. First, it is compact. Indeed, each $R_{i_n}$ is compact in $\Lambda$, and $f^n|_\Lambda: \Lambda \to \Lambda$ is continuous, so $f^{-n}(R_{i_n})$ is compact. A finite intersection of compact subsets of the compact [metric space](/page/Metric%20Space) $\Lambda$ is compact.
Second, $K_N(i)$ is nonempty. This is exactly where admissibility and the Markov property are used. The condition $i \in \Sigma_A$ says that
\begin{align*}
A_{i_n i_{n+1}} = 1
\end{align*}
for every $n \in \mathbb Z$. By the definition of the transition matrix, this means that each successive transition $R_{i_n} \to R_{i_{n+1}}$ is allowed. The Markov property of the partition says that every finite admissible word is realised by an orbit segment. Applied to the finite word
\begin{align*}
(i_{-N}, i_{-N+1}, \dots, i_N),
\end{align*}
it gives a point $x_N \in \Lambda$ such that $f^n(x_N) \in R_{i_n}$ for all $-N \leq n \leq N$. Therefore $x_N \in K_N(i)$.
The sets $K_N(i)$ form a nested family. Increasing $N$ adds more orbit constraints, so if $N_1 \leq N_2$, then
\begin{align*}
K_{N_2}(i) \subset K_{N_1}(i).
\end{align*}
Compactness and nesting alone would only give a nonempty intersection. To get a single point, we use hyperbolicity. By the shrinking property stated for the proper finite Markov partition, with respect to the Riemannian distance $d$ on $M$, there are constants $C_{\mathcal R} > 0$ and $\theta_{\mathcal R} \in (0,1)$ such that
\begin{align*}
\operatorname{diam}(K_N(i)) \leq C_{\mathcal R}\theta_{\mathcal R}^{N}
\end{align*}
for every $N \geq 0$. The reason behind this hypothesis is that agreeing on future symbols forces stable coordinates to approach exponentially in forward time, while agreeing on past symbols forces unstable coordinates to approach exponentially in backward time. Inside a Markov rectangle, local product structure combines those stable and unstable estimates into a full diameter estimate.
Now compactness gives
\begin{align*}
\bigcap_{N=0}^{\infty} K_N(i) \neq \varnothing.
\end{align*}
If $x$ and $y$ are both in this intersection, then $x,y \in K_N(i)$ for every $N$, so
\begin{align*}
d(x,y) \leq \operatorname{diam}(K_N(i)) \leq C_{\mathcal R}\theta_{\mathcal R}^{N}.
\end{align*}
Letting $N \to \infty$ gives $d(x,y)=0$, hence $x=y$. Thus the infinite itinerary determines exactly one point. We define $\pi(i)$ to be this unique point.[/guided]