Add explanations and fix typos
Signed-off-by: Riccardo Finotello <riccardo.finotello@gmail.com>
This commit is contained in:
93
thesis.tex
93
thesis.tex
@@ -41,7 +41,7 @@
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\\
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I.N.F.N.\ -- sezione di Torino
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}
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\date{15th December 2020}
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\date{18th December 2020}
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\usetikzlibrary{decorations.markings}
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\usetikzlibrary{decorations.pathmorphing}
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@@ -378,21 +378,48 @@
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% \pause
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\begin{block}{T-duality}
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\textbf{Dirichlet b.c.} consequence of \textbf{T-duality} on $p$ directions:
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\begin{equation*}
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\overline{X}( z ) \mapsto - \overline{X}( z )
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\quad
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\Rightarrow
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\quad
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\eval{\partial_{\upsigma} X^i\qty( \uptau, \upsigma )}_{\upsigma = 0}^{\upsigma = \ell} = 0
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\quad
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\stackrel{T-duality}{\longrightarrow}
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\quad
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\eval{\partial_{\uptau} \widetilde{X}^i\qty( \uptau, \upsigma )}_{\upsigma = 0}^{\upsigma = \ell} = 0
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\end{equation*}
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thus \textbf{open strings} can be \textbf{constrained} to $D(D - p - 1)$-branes.
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\hfill
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\cite{Polchinski (1995, 1996)}
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\only<2>{%
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Consider \textbf{closed strings} on $\mathscr{M}^{1,D-1} = \mathscr{M}^{1,D-2} \otimes \mathrm{S}^1( R )$:
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\begin{equation*}
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\begin{split}
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\begin{cases}
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\upalpha_0^{D-1} & = \frac{1}{\sqrt{2 \upalpha'}} \qty( n \frac{\upalpha'}{R} + m R )
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\\
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\widetilde{\upalpha}_0^{D-1} & = \frac{1}{\sqrt{2 \upalpha'}} \qty( n \frac{\upalpha'}{R} - m R )
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\end{cases}
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\quad
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\Rightarrow
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\quad
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M^2
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=
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-p^{\upmu} p_{\upmu}
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& =
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\frac{2}{\upalpha'} \qty( \upalpha_0^{D-1} )^2 + \frac{4}{\upalpha'} \qty( \mathrm{N} + a )
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\\
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& =
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\frac{2}{\upalpha'} \qty( \widetilde{\upalpha}_0^{D-1} )^2 + \frac{4}{\upalpha'} \qty( \widetilde{\mathrm{N}} + a )
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\end{split}
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\end{equation*}
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\vfill
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}
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\only<3->{%
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\textbf{Dirichlet b.c.} consequence of \textbf{T-duality} on $p$ directions:
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\begin{equation*}
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\overline{X}( z ) \mapsto - \overline{X}( z )
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\quad
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\Rightarrow
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\quad
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\eval{\partial_{\upsigma} X^i\qty( \uptau, \upsigma )}_{\upsigma = 0}^{\upsigma = \ell} = 0
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\quad
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\stackrel{T-duality}{\longrightarrow}
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\quad
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\eval{\partial_{\uptau} \widetilde{X}^i\qty( \uptau, \upsigma )}_{\upsigma = 0}^{\upsigma = \ell} = 0
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\end{equation*}
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thus \textbf{open strings} can be \textbf{constrained} to $D(D - p - 1)$-branes.
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\hfill
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\cite{Polchinski (1995, 1996)}
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\vfill
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}
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\end{block}
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\end{frame}
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@@ -744,9 +771,9 @@
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\item classical action \textbf{larger} than factorised case
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\end{itemize}
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\hspace{0.65\columnwidth}\cite{RF, Pesando (2019)}
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\end{column}
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\end{columns}
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\vfill
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}
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\end{block}
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\end{frame}
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@@ -975,6 +1002,7 @@
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+
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\frac{1}{2} \qty( \sum\limits_{t = 1}^N \frac{n_{(t)} + \frac{\upepsilon_{(t)}}{2}}{z - x_{(t)}} )^2
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\end{equation*}
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\hfill\cite{RF, Pesando (2019)}
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\pause
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@@ -1144,7 +1172,7 @@
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Use \textbf{time-dependent orbifolds} to model \textbf{space-like singularities}:
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\begin{center}
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divergent \highlight{closed string} aplitudes
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divergent \highlight{closed string} amplitudes
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$\Rightarrow$
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gravitational backreaction?
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\end{center}
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@@ -1257,6 +1285,10 @@
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So far:
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\begin{itemize}
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\item field theory presents \textbf{divergences} (even sQED $\rightarrow$ eikonal?)
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\pause
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\item obvious ways to regularise (Wilson lines, higher derivative couplings, etc.) \textbf{do not work}
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\pause
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@@ -1280,7 +1312,7 @@
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\colon
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\qty(%
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\frac{i}{\sqrt{2 \upalpha'}}\,
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\upxi \cdot \partial^2_x X( x,\, x )
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\upxi_{\upalpha} \partial^2_x X^{\upalpha}( x,\, x )
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+
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\qty( \frac{i}{\sqrt{2 \upalpha'}} )^2\,
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S_{\upalpha\upbeta}
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@@ -1296,7 +1328,7 @@
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\begin{center}
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\it
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string theory cannot do \textbf{better than field theory} (EFT) if the latter \textbf{does not exist} (even a Wilson line around $z$ does not prevent such behaviour)
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string theory cannot do \textbf{better than field theory} (EFT) if the latter \textbf{does not exist}
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\end{center}
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\end{frame}
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@@ -1361,12 +1393,14 @@
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\vspace{2em}
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\begin{center}
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\it
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spacetime singularities are \textbf{hidden into contact terms} and interactions with \textbf{massive states} (the gravitational eikonal deals with massless interactions)
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divergences are \textbf{hidden into contact terms} and interactions with \textbf{massive states} (the gravitational eikonal deals with massless interactions)
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\end{center}
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\begin{tikzpicture}[remember picture, overlay]
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\draw[line width=4pt, red] (0em, 4.5em) rectangle (40em, 1em);
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\end{tikzpicture}
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\hfill\cite{Arduino, RF, Pesando (2020)}
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\end{frame}
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@@ -1453,13 +1487,15 @@
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\pause
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\begin{block}{Machine Learning Approach}
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What is $\mathscr{R}$?
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What is $\mathscr{R}$ in \textbf{machine learning} approach?
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\begin{equation*}
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\mathscr{R}( M ) \longrightarrow \mathscr{R}_n( M;\, w )
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\qquad
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\text{s.t.}
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\qquad
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\lim\limits_{n \to \infty} \abs{\mathscr{R}( M ) - \mathscr{R}_n( M;\, w )} = 0
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\exists n > M > 0 \mid \mathcal{L}\qty(\mathscr{R}( M ),\, \mathscr{R}_n( M;\, w )) < \upepsilon
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\quad
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\forall \upepsilon > 0
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\end{equation*}
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\end{block}
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\end{frame}
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@@ -1532,6 +1568,8 @@
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Hodge numbers
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\end{center}
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\hfill\cite{Ruehle (2020); Erbin, RF (2020)}
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\pause
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\begin{columns}
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@@ -1598,13 +1636,14 @@
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\begin{column}{0.5\linewidth}
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\centering
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\textbf{Configuration Matrix Only}
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\includegraphics[width=0.8\columnwidth, trim={0 0 3.3in 0}, clip]{img/cicy_matrix_plots.pdf}
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\includegraphics[width=0.75\columnwidth, trim={0 0 3.3in 0}, clip]{img/cicy_matrix_plots.pdf}
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\end{column}
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\hfill\pause
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\begin{column}{0.5\linewidth}
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\centering
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\textbf{Best Training Set}
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\includegraphics[width=0.8\columnwidth, trim={0 0 3.3in 0}, clip]{img/cicy_best_plots.pdf}
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\cite{Erbin, RF (2020)}
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\includegraphics[width=0.75\columnwidth, trim={0 0 3.3in 0}, clip]{img/cicy_best_plots.pdf}
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\end{column}
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\end{columns}
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\end{frame}
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@@ -1699,7 +1738,9 @@
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\begin{column}{0.5\linewidth}
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\centering
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\textbf{Best Training Set}
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\includegraphics[width=\columnwidth]{img/cicy_best_plots.pdf}
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\cite{Erbin, RF (2020)}
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\only<1>{\includegraphics[width=0.8\columnwidth, trim={0 0 1.65in 0}, clip]{img/cicy_best_plots.pdf}}
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\only<2->{\includegraphics[width=\columnwidth]{img/cicy_best_plots.pdf}}
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\end{column}
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\hfill
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\begin{column}{0.5\linewidth}
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