+
+\section{Temps de mélange pour une distribution uniforme}
+\frame{\frametitle{Outline}\tableofcontents[currentsection,hideallsubsections]}
+
+
+\frameselect{true}{
+ \begin{frame}
+ \frametitle{Mixing time upper bound}
+ \begin{itemize}
+ \item Evaluated in a (lazy) context
+ \item $t_{\rm mix}(\varepsilon)$: the steps required to be sure to be $\varepsilon$-close
+ to the stationary uniform distribution
+ \item Theoretical result: $t_{\rm mix}\leq 32N^2+16N\ln (N+1)=O(N^2)$
+ \item In practice: in $N\ln(N)$
+ \end{itemize}
+ \end{frame}
+}
+
+
+\section{Experiments}
+\frame{\frametitle{Outline}\tableofcontents[currentsection,hideallsubsections]}
+
+
+
+\frameselect{true}{
+ \begin{frame}
+ \frametitle{Functions with DSCC Matrix and smallest MT}
+ \begin{center}
+\begin{scriptsize}
+ \begin{tabular}{|c|c|c|c|}
+ \hline
+Function $f$ & $f(x)$, for $x$ in $(0,1,2,\hdots,2^n-1)$ & $\mathsf{N}$ & $b$
+\\
+\hline
+%%%%% n= 4
+$\textcircled{a}$&[13,10,9,14,3,11,1,12,15,4,7,5,2,6,0,8]&4&64\\
+\hline
+%%%%% n= 5
+$\textcircled{b}$&
+[29, 22, 25, 30, 19, 27, 24, 16, 21, 6, 5, 28, 23, 26, 1, 17, & 5 & 78 \\
+&
+ 31, 12, 15, 8, 10, 14, 13, 9, 3, 2, 7, 20, 11, 18, 0, 4]
+&&\\
+%%%%% n= 6
+\hline
+&
+[55, 60, 45, 44, 58, 62, 61, 48, 53, 50, 52, 36, 59, 34, 33, 49,
+&&\\
+&
+ 15, 42, 47, 46, 35, 10, 57, 56, 7, 54, 39, 37, 51, 2, 1, 40, 63,
+&&\\
+$\textcircled{c}$&
+ 26, 25, 30, 19, 27, 17, 28, 31, 20, 23, 21, 18, 22, 16, 24, 13,
+&6&88\\
+&
+12, 29, 8, 43, 14, 41, 0, 5, 38, 4, 6, 11, 3, 9, 32]
+&&\\
+%%%%% n= 7
+\hline
+&
+[111, 124, 93, 120, 122, 114, 89, 121, 87, 126, 125, 84, 123, 82,
+&&\\
+&112, 80, 79, 106, 105, 110, 75, 107, 73, 108, 119, 100, 117, 116,
+&&\\
+&103, 102, 101, 97, 31, 86, 95, 94, 83, 26, 88, 24, 71, 118, 69,
+&&\\
+&68, 115, 90, 113, 16, 15, 76, 109, 72, 74, 10, 9, 104, 7, 6, 65,
+&&\\
+$\textcircled{d}$ &70, 99, 98, 64, 96, 127, 54, 53, 62, 51, 59, 56, 60, 39, 52, 37, &7 &99\\
+&36, 55, 58, 57, 49, 63, 44, 47, 40, 42, 46, 45, 41, 35, 34, 33,
+&&\\
+&38, 43, 50, 32, 48, 29, 28, 61, 92, 91, 18, 17, 25, 19, 30, 85,
+&&\\
+&22, 27, 2, 81, 0, 13, 78, 77, 14, 3, 11, 8, 12, 23, 4, 21, 20,
+&&\\
+&67, 66, 5, 1]
+&&\\
+
+
+%%%%%n=8
+\hline
+$\textcircled{e}$& \ldots &8&109\\
+ \hline
+\end{tabular}
+\end{scriptsize}
+\end{center}
+\end{frame}
+}
+
+\frameselect{true}{
+ \begin{frame}
+ \frametitle{Nist Test Results}
+\begin{itemize}
+\item Embedded PRNG \textit{Random}: Mersenne Twister algorithm~\footnote{Mersenne twister: a 623-dimensionally
+ equidistributed uniform pseudo-random number generator, (TOMACS) 8 , 3--30}
+\item Adding chaos properties for Mersenne Twister algorithm: security is not reduced w.r.t. NIST
+\end{itemize}
+\end{frame}
+}
+
+\section{Conclusion}
+
+\frameselect{true}{
+ \begin{frame}
+ \frametitle{Summary}
+\begin{itemize}
+\item Chaos properties can be added to PRNGs
+\item Iterated map: built by removing from a $\mathsf{N}$-cube a balanced Hamiltonian cycle
+\item Efficient method to compute balanced Hamiltonian cycles
+\item Upper bound (quadratic) on the number of iterations
+that is sufficient to obtain an uniform distribution of the output
+\item The first time a full automatic method to provide chaotic PRNGs is given
+\end{itemize}
+\end{frame}
+}
+
+
+\frameselect{true}{
+ \begin{frame}
+ \frametitle{Perspectives}
+\begin{itemize}
+\item Actuellement: si le cycle hamiltonien
+change le $l^{\textrm{ème}}$ bit entre les n{\oe}uds $X$ et $Y$, alors
+le $l^{\textrm{ème}}$ bit entre $Y$ et $Z$, ne peut pas être changé.
+\item Si le cycle hamiltonien est globalement équilibré:
+la probabilité de changer un bit $l'$, $ l' \neq l$, entre $Y$ et $Z$
+est $\frac{1}{\mathsf{N}-1}$ $\leadsto$ à intégrer.
+\item Actuellement: marcher dans une partie d'un $\mathsf{N}$-cube
+\item Futur: modifier plusieurs bits en une seule itération (sauter dans cette partie du $\mathsf{N}$-cube)
+\end{itemize}
+\end{frame}
+}
+
+