-\vspace{-0.5em}
-It is easy to associate a Markov Matrix $M$ to such a graph $G(f)$
-as follows:
-
-$M_{ij} = \frac{1}{n}$ if there is an edge from $i$ to $j$ in $\Gamma(f)$ and $i \neq j$; $M_{ii} = 1 - \sum\limits_{j=1, j\neq i}^n M_{ij}$; and $M_{ij} = 0$ otherwise.
-
-\begin{xpl}
-The Markov matrix associated to the function $f^*$ is
-
-\[
-M=\dfrac{1}{3} \left(
-\begin{array}{llllllll}
-1&1&1&0&0&0&0&0 \\
-1&1&0&0&0&1&0&0 \\
-0&0&1&1&0&0&1&0 \\
-0&1&1&1&0&0&0&0 \\
-1&0&0&0&1&0&1&0 \\
-0&0&0&0&1&1&0&1 \\
-0&0&0&0&1&0&1&1 \\
-0&0&0&1&0&1&0&1
-\end{array}
-\right)
-\]
-
-
-
-
-
-\end{xpl}
+% \vspace{-0.5em}
+% It is easy to associate a Markov Matrix $M$ to such a graph $G(f)$
+% as follows:
+
+% $M_{ij} = \frac{1}{n}$ if there is an edge from $i$ to $j$ in $\Gamma(f)$ and $i \neq j$; $M_{ii} = 1 - \sum\limits_{j=1, j\neq i}^n M_{ij}$; and $M_{ij} = 0$ otherwise.
+
+% \begin{xpl}
+% The Markov matrix associated to the function $f^*$ is
+
+% \[
+% M=\dfrac{1}{3} \left(
+% \begin{array}{llllllll}
+% 1&1&1&0&0&0&0&0 \\
+% 1&1&0&0&0&1&0&0 \\
+% 0&0&1&1&0&0&1&0 \\
+% 0&1&1&1&0&0&0&0 \\
+% 1&0&0&0&1&0&1&0 \\
+% 0&0&0&0&1&1&0&1 \\
+% 0&0&0&0&1&0&1&1 \\
+% 0&0&0&1&0&1&0&1
+% \end{array}
+% \right)
+% \]
+%\end{xpl}