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frame-stspl-findings.tex
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% SPDX-License-Identifier: CC-BY-4.0
% Copyright 2018 Toni Dietze
\documentclass[beamer]{standalone}
\input{preamble.tex}
\title{\jobname}
\begin{document}
\begin{standaloneframe}{\jobname}
\setlength{\topsep}{-\parskip}%
\setlength{\partopsep}{0pt}%
\begin{lemma}[{{\small proper splitting preserves weights of trees}}]\label{lemma:proper-split}
\begin{tabbing}
\textbf{let} \= $ℳ$, $ℳ'$ be semi-probabilistic wta over $\varSigma$,
%\\\>
$\pi$ be a $ℳ$-splitter;
\\
\textbf{if} $ℳ'$ is a proper $\pi$-split of $ℳ$, \textbf{then} $\forall t \in \trees{\varSigma}\colon ⟦ℳ⟧(t) = ⟦ℳ'⟧(t)$
\end{tabbing}
\end{lemma}
\begin{lemma}[{{\small merging preserves semi-probabilistic}}]
\begin{tabbing}
\textbf{let} \= $ℳ'$ be a semi-probabilistic wta,
\\\>
$\pi$ be a $ℳ'$-merger,
\\\>
$\lambda$ be a $\pi$-distributor;
\\
\textbf{then} $\mrg_\pi^\lambda(ℳ')$ is semi-probabilistic
\end{tabbing}
\end{lemma}
\begin{lemma}[{{\small composition of merges}}]
\begin{tabbing}
$\mrg_{\pi_2}^{\lambda_2}(\mrg_{\pi_1}^{\lambda_1}(ℳ)) = \mrg_{\pi}^\lambda(ℳ)$,
\\
\quad \textbf{where} \= $\pi = \pi_2 \circ \pi_1$,
\\
\> $\lambda(q) = \lambda_1(q) \cdot \lambda_2(\pi_1(q))$ for every $q \in Q$
\end{tabbing}
\end{lemma}
\end{standaloneframe}
\end{document}