% This program can be redistributed and/or modified under the terms
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% Seth Brown, Ph.D.
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% title slide definition
\title{Update}
%\subtitle{a bias report}
\author{ Marcin Chrz\k{a}szcz$^{1,2}$}
\institute[UTH, IFJ]
{
 %\begin{tiny}
$ ^1$ University of Zurich , $ ^2$ Institute of Nuclear Physics, Krakow,  
 %\end{tiny}smallsmall
}
  

\date{ \today}

%--------------------------------------------------------------------
%                           Introduction
%--------------------------------------------------------------------

\begin{document}




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%--------------------------------------------------------------------
%                          OUTLINE
%--------------------------------------------------------------------




\section[Outline]{}
\begin{frame}
\tableofcontents
\end{frame}


%-------------------------------------------------------------------
%                          Introduction
%-------------------------------------------------------------------
%
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% Insert infoline
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\title{Update on analysis}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\section{PID + GeoMVA}
\begin{frame}\frametitle{Reminder}
{~}\\
Last week I shown that we might gain quite a lot by putting PID inside our GEOMVA. Let's see if we are sensitive to poor description of PID in MC(credits to \textbf{Helge Voss}):

  \includegraphics[scale=0.32]{pidmva/ROC_Zoom1.png}


	\textref {M.Chrz\k{a}szcz, N.Serra 2013}
\end{frame}

\begin{frame}\frametitle{Closer look}
{~}\\

  \includegraphics[scale=0.32]{pidmva/ROC_Zoom2.png}


	\textref {M.Chrz\k{a}szcz, N.Serra 2013}
\end{frame}




\begin{frame}\frametitle{Conclusion}
{~}\\
\only<1>
{
\begin{enumerate}
\item Clearly our optimistic MC has no impact on our MVA performance. 
\item Tools ready to train it with different information loose="smearing"
\end{enumerate}


}
\only<2>
{
  \includegraphics[scale=0.25]{pidmva/pidsmeared.png}

}
	\textref {M.Chrz\k{a}szcz, N.Serra 2013}
\end{frame}


\section{Calibration of PGMVA}




%\section{Work done so far}
\begin{frame}\frametitle{Calibration of PGMVA=PID + GeoMVA}
{~}\\
\only<1>{
\begin{itemize}
\item The biggest worry is if we can calibrate this channel.
\item The following idea allowes to calibrate our channel on $\PDs \to \phi \pi$.
\item It looks that calibration can be even simpler than the one we make. 
\item Ok enough of building attention, let's caught to the chase

\end{itemize}
}

\only<2>
{
What we have:


\begin{columns}
\column{2in}
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\column{3.05in}
\begin{itemize}
\item For free we have 2 mu PID.
\item For signal we need 3.
\item Let's take our $\PDs \to \phi \pi$ and bin our muons in 3D bins of $n_{trk}$, $P_{t,\mu}$, and $\eta_{mu}$.
\item For each of the bins we have a PID distribution for muon
\item Then for the $\pi$ in a given bin we choose a PID according to $\mu$ PID in this bin.
\item $\PB \to K^{*} \mu \mu$ uses a similar approach. 

\end{itemize}
\end{columns}





}
\only<3>
{
What we have:


\begin{columns}
\column{2in}
  \includegraphics[scale=0.3]{pidmva/topos.pdf}
\column{3.05in}
\begin{itemize}
\item Calibration is in principle easier.
\item Use only one channel, instead of two.



\end{itemize}
\end{columns}





}

	\textref {M.Chrz\k{a}szcz, N.Serra 2013}
\end{frame}




\end{document}