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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%\beamersetuncovermixins{\opaqueness<1>{25}}{\opaqueness<2->{15}}
\title{Update on $\tau \to \mu \mu \mu$ searches}  
\author{M.Chrzaszcz$^{1,2}$,N. Serra$^1$,
}

%\date{\today} 
\begin{document}

{
\institute{$^1$ Zurich, $^2$ Krakow}
\setbeamertemplate{footline}{} 
\begin{frame}
\logo{
\vspace{2 mm}
\includegraphics[height=1cm,keepaspectratio]{images/ifj.png}~
\includegraphics[height=1cm,keepaspectratio]{images/uzh.jpg}}

  \titlepage
\end{frame}
}

\institute{UZH,IFJ} 


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


\begin{frame}\frametitle{MC samples}

\begin{enumerate}
\only<1>{
\item MC Samples; quite nice(mostly Krakow)
\begin{itemize}
\item All cool MC generator cuts.
\item Signal - DONE
\item Calibration channel - DONE
\item $b\overline{b}$ bck - DONE $18.1 pb^{-1}$
\item $c\overline{c}$ bck - $50$ DONE, $2.6pb^{-1}$  
\item $Ds\to \eta(\mu\mu \gamma)\mu\mu$ - DONE - $>5fb^{-1}$
\item $\tau \to p \mu \mu$ Hopefully not needed :)
\item Last night all samples got into ntuples.
\end{itemize}
\item $cc$, $bb$ cross section fixed for now(we will update if we have measurement for $cc$).
}

\end{enumerate}
\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%55
\begin{frame}\frametitle{Normalization}
\only<1>
{
\begin{center}
\begin{tiny}
	\begin{columns}
\column{2.5in}
\begin{center}
	$D_s \to \phi(\mu\mu)\pi$ in data.\\
  \includegraphics[scale=0.13]{Ds_Mass/Ds_mass_data.png} \\
  \begin{itemize}
  \item mean = $1970.3 \pm 0.9 MeV$
  \end{itemize}
\end{center}

\column{2.5in}
\begin{center}
$D_s \to \phi(\mu\mu)\pi$ in MC.\\
 \includegraphics[scale=0.13]{Ds_Mass/D_mass_base.png}\\
   \begin{itemize}
  \item mean = $1969.1 \pm 0.60 MeV$
  \end{itemize}
\end{center}
\end{columns}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5
	\begin{columns}
\column{2.5in}
\begin{center}
\begin{small}
   \begin{itemize}
  \item $m_{\tau \to 3\mu} = \dfrac{1970.3}{1969.1} \times 1777.7  =$\textcolor{blue}{$ 1778.8 \pm 1.1 MeV$}
  \end{itemize}
{~} \\ In agreement with 2011.
\end{small}
\end{center}


\column{2.5in}
\begin{center}
	Fit $\tau \to \mu\mu\mu$ in MC. \\
 \includegraphics[scale=0.11]{Ds_Mass/tau_mass_base.png}\\
%   \begin{itemize}
%  \item mean = $1777.7 \pm 0.4 MeV$ \\
%  \end{itemize} 
 
\end{center}
\end{columns}

\end{tiny}
\end{center}

}


\end{frame}

\begin{frame}\frametitle{Trigger}

\begin{enumerate}
\only<1>{
\item Here we really suck.
\begin{itemize}
\item Trigger lines changed between 2011 and 2012
\item In 2012 also lines have changed...
\item Need to evaluate the efficiency for each TCK.
\item I am preparing all possible ntuples for Jon to weight the efficiencies accordingly to TCK version.  
\item God have mercy on my soul... 
\end{itemize}

}

\end{enumerate}
\end{frame}

\begin{frame}\frametitle{DATA -MC comparison}
{~}


\only<1>
{	

	\begin{columns}
\column{2.5in}
  \includegraphics[scale=0.18]{Ds_Splot/p0_IP.png} \\



\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/p0_IPSig.png}\\


\end{columns}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	\begin{columns}
\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/p1_IP.png}\\



\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/p1_IPSig.png}\\


\end{columns}


}

	

\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5
\begin{frame}\frametitle{$\PDs \to \eta(\mu \mu \gamma) \mu \nu$}
\only<1>
{
 \begin{exampleblock}{~}
\begin{enumerate}
\item The dominant background source of peaking background in this analysis is  \textcolor{blue}{$\PDs \to \eta(\mu\mu\gamma) \mu \nu$}\\
\item In 2011 we suffered from lack of MC statistics.
\item Thanks to generator cuts our pdfs became more stable.
\item Pdf used: $\mathcal{P} = exp(m) \times Pol^n(m)$
\item This is ready to go.
 \end{enumerate}
 \end{exampleblock}

	\begin{columns}
\column{2.5in}
\begin{center}

  \includegraphics[scale=0.09]{RD_meeting/pid_0_65_0_725geo-0_48_0_05.png} \\
\begin{tiny} PID:$0.65;0.725$,GEO:$-0.48;0.05$ \end{tiny}
\end{center}

\column{2.5in}
\begin{center}
 \includegraphics[scale=0.09]{RD_meeting/pid_0_725_0_86geo0_35_0_65.png}\\
\begin{tiny} PID:$0.725;0.0.86$,GEO:$0.35;0.65$ \end{tiny}

\end{center}
\end{columns}
}

%	\textref {M.Chrz\k{a}szcz 2013}

\end{frame}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5

\begin{frame}\frametitle{Isolating Parameter}
{~}


\only<1>
{	
\begin{itemize}
\item All the R\&D has finished.
\item I have an optimum isolating parameter for 5 different tau sources.
\item Only need to write a DV algorithm to put this inside zoontuple.
\item Also needs comparison to iso and non -isolating.(Still didn't get answer when can this happen). 
\end{itemize}


}

	

\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\begin{frame}\frametitle{MVA}
{~}


\only<1>
{	
\begin{itemize}
\item All the scripts are there
\item Limitation is the $cc$  bck sample. Would be nice to have two times more.
\item Let's hope this plot will stay the same :)

  \includegraphics[scale=0.27]{images/BDT_comparison.png}

\end{itemize}


}

	

\end{frame}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\begin{frame}\frametitle{Binning optimisation}
{~}


\only<1>
{	
\begin{itemize}
\item Also done(I used 2011 data, so just when we fix new BDT need to press Enter).
\item How ever last night I had an idea(Nico you won't like this one). What about use purelly Bayesian way to optimise? 
\item I am to curious to get discourage not to do it :)

\end{itemize}
	\begin{columns}
\column{2.5in}


	  \includegraphics[scale=0.13]{inflaton/punzi1.png}
	    \begin{itemize}
  \item FOM as a function of N. of bins.
  \end{itemize}
	\column{2.5in}
		  \includegraphics[scale=0.27]{RD_meeting/2d-data.pdf}
	    \begin{itemize}
  \item Signal efficiency in 2011 binning.
  \end{itemize}
	\end{columns}

}

	

\end{frame}

\begin{frame}\frametitle{Model dependence}
{~}


\only<1>
{	
\begin{itemize}
\item Paul implemented an "model independent" 3 scenarios.
\item he wants only to correct Normalization for studies.
\item With Nico we think multidimensional fir would be more fun.
\item Also would like to implement some SUSY models.

\end{itemize}


}
\begin{center}
\begin{columns}
\column{1.6in}
{~}$(\overline{L} \gamma_{\mu} L)(\overline{L} \gamma^{\mu} L)$\\
	{~}\includegraphics[scale=0.22]{images/gammallll.png}

\column{1.6in}
$(\overline{R}\gamma_{\mu} R)(\overline{L} \gamma^{\mu} L)$\\
	 \includegraphics[scale=0.22]{images/gammallrr.png}
\column{1.6in}
$g'(\overline{L}H\sigma_{\mu\nu}R)B^{\mu\nu}$\\
	 \includegraphics[scale=0.22]{images/gammarad.png}

\end{columns}
\end{center}

\end{frame}







\begin{frame}\frametitle{Conclusions}
{~}


\only<1>
{	
\begin{itemize}
\item Analysis is well under way.
\item I am determined to finish asap.
\item End of this year is possible if we won't do $\tau \to p \mu \mu$.

\end{itemize}


}

	

\end{frame}




%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\begin{frame}\frametitle{}


\begin{Huge}
BACKUP
\end{Huge}



\end{frame}



\begin{frame}\frametitle{Status}
\begin{columns}
\column{2in}
\begin{center}
$1 $fb$^{-1}$ analysis of  \textcolor{violet}{$\tau \to \mu \mu \mu$} and \textcolor{blue}{$\tau \to p \mu \mu$} appeared in PLB.

\end{center}


\column{3in}

 \includegraphics[scale=0.197]{RD_meeting/PLB.png}
\end{columns}

\begin{exampleblock}{2011 results:} \begin{enumerate}
\item Obtained limit for $\tau \to \mu \mu \mu$: $8.0 \times 10^{-8}$. 
\item Belle(BaBar) results: $2.1 (3.2) \times 10^{-8}$ at $90\%$ CL.
\item For 2012 + 2011 planned to implement several improvements.

\end{enumerate}
\end{exampleblock}


%	\textref {M.Chrz\k{a}szcz 2013}

\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5
\begin{frame}\frametitle{Status}
For now we use:
\begin{enumerate}
\item Stripping 20.
\item Signal sample: official+Krakow produced sample $(1M+1M)$.
\item $bb$ and $cc$ samples: official+Krakow. In total 30M events.
\item General strategy stays the same as 2011.
\end{enumerate}


\end{frame}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%




\section{MC Samples}



\begin{frame}\frametitle{Cross section update}
\only<1>
{
Analysis uses the knowledge of $c\overline{c}$ and $b\overline{b}$ cross sections. In 2011 both were measured by LHCb. For 2012 for the moment we assume:
\begin{itemize}
\item $\sigma_{b\overline{b}}^{8TeV}=298\pm36 \mu b$ from LHCB-PAPER-2013-016 
\item $\sigma_{c\overline{c}}^{8TeV}=\sigma_{c\overline{c}}^{7TeV}\times \dfrac{8}{7} = 6950 \pm 1100 \mu b$

\end{itemize}

\begin{exampleblock}{Cross checks on $c\overline{c}$} 

\begin{enumerate}
\item Pythia cross section calculation.
\item Comparing $D_s$ yields in data.

\end{enumerate}
\end{exampleblock}


}

	%\textref {M.Chrz\k{a}szcz 2013}

\end{frame}


\begin{frame}\frametitle{Generated MC samples }
\only<1>
{

\begin{enumerate}
\item In the 2011 analysis one of the complications from MC was
the wrong mixture of tau sources.
\item For 2012 we solved this problem by simulating signal in 5 parts. One for each production channel:
\end{enumerate}

}

\begin{center}

 \fcolorbox{blue}{yellow}{
%\begin{equation}NUmber of ne

$\tau \to \mu \mu \mu =  \begin{cases}
\PB \to \Ptau \to \mu \mu \mu     &   11.6\% \\
\PB \to \PDs \to \tau \to \mu \mu \mu &  8.7\% \\
\PB \to \PD \to \tau \to \mu \mu \mu & 0.2\% \\
\PDs \to \tau \to \mu \mu \mu & 75.0\% \\
\PD \to \tau \to \mu \mu \mu & 4.4\% \\

\end{cases}$
%\end{equation}

 }
% $\HepParticle{B}{}{\pm} \to \HepParticle{D}{}{(\ast)} \tau^{\pm} \nu$}
\end{center}

	%\textref {M.Chrz\k{a}szcz 2013}

\end{frame}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%55
\begin{frame}\frametitle{MC Generator Cuts}
\only<1>
{
In order to use computing resources in more efficient way we introduced generator level cuts.
\begin{center}
  \begin{tabular}{ | c | c || l | c |}
    \hline
    \multicolumn{2}{|c|| }{Signal sample\footnote{$X \to \tau\to 3\mu$, $\PDs \to \eta(\mu\mu \gamma) \mu \nu$, $\PDs \to \phi(\mu\mu) \pi$ }} & \multicolumn{2}{|c| }{Background sample(Dimuon)\footnote{$c\bar{c}$, $b\bar{b}$ }} \\ \hline \hline
    $p_{t\mu}$ & $>250MeV$ & $p_{t\mu}$ & $>280MeV$ \\ \hline
    $p_{\mu}$ & $>2.5GeV$ & $p_{\mu}$ & $>2.9GeV$ \\     \cline{3-4}  
    & & $m(\mu\mu)$ & $<4.5GeV$\\  \cline{3-4}  
    & & DOCA$(\mu\mu)$ & $<0.35mm$\\ \hline
  \end{tabular}
\end{center}
}
Gain a factor of $\sim 2-3$ in signal statistics compared to 2011 and factor of ~8 in background.

	%\textref {M.Chrz\k{a}szcz 2013}

\end{frame}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\begin{frame}\frametitle{Trigger lines}
\only<1>
{
In 2011 we took all trigger lines into account. Studies shown we can gain on limiting ourselves to specific lines (2011 data sample).


\begin{center}
  \begin{tabular}{| c | c | c | c | c | }
    \hline
    Line Name & $\epsilon [\%]$ & $\epsilon' [\%]$ & $\beta [\%]$ &  $\beta' [\%]$ \\ \hline \hline
  Hlt2CharmSemilepD2HMuMu & $81.7$ & $81.7$ & $56.8$ & $56.8$ \\ \hline
  Hlt2DiMuonDetached & $75.0$ & $12.5$ & $54.1$ & $17.6$ \\ \hline
  Hlt2TriMuonTau & $66.3$ & $2.9$ & $60.0$ & $12.2$ \\ \hline 
  Others & - & $2.2$ & - & $11.6$ \\ \hline
  \end{tabular}
	  
\end{center}
, where $\epsilon$ is the signal efficiency (any Hlt2physics), $\epsilon'$ is the gain of the efficiency.\\ $\beta$ is the efficiency of background and $\beta'$ is the gain of the bck efficiency\\

Rule of thumb (using $\frac{s}{\sqrt{b}}$ FOM) tells us that we can gain $\mathcal{O}(5\%)$. 

}


	%\textref {M.Chrz\k{a}szcz 2013}

\end{frame}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%55
\section{Normalization}
\begin{frame}\frametitle{Normalization channel}
\only<1>
{
  As last year we will use \textcolor{blue}{$\PDs \to \phi(\mu\mu) \pi$}.Similarly to signal channels we produced them with correct proportion:
 \begin{exampleblock}{~}
\begin{enumerate}
\item $cc \to \PDs \to \phi (\mu\mu) \pi$   $89.7\%$ 
\item $bb \to \PDs \to \phi (\mu\mu) \pi$   $10.3\%$
\end{enumerate}
\end{exampleblock}
We avoid reweighting of the samples as in 2011.
 
}

	%\textref {M.Chrz\k{a}szcz 2013}

\end{frame}
\begin{frame}\frametitle{Mass correction}
\only<1>
{
\begin{center}
\begin{tiny}
	\begin{columns}
\column{2.5in}
\begin{center}
	$D_s \to \phi(\mu\mu)\pi$ in data.\\
  \includegraphics[scale=0.13]{Ds_Mass/Ds_mass_data.png} \\
  \begin{itemize}
  \item mean = $1970.3 \pm 0.9 MeV$
  \end{itemize}
\end{center}

\column{2.5in}
\begin{center}
$D_s \to \phi(\mu\mu)\pi$ in MC.\\
 \includegraphics[scale=0.13]{Ds_Mass/D_mass_base.png}\\
   \begin{itemize}
  \item mean = $1969.1 \pm 0.60 MeV$
  \end{itemize}
\end{center}
\end{columns}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5
	\begin{columns}
\column{2.5in}
\begin{center}
\begin{small}
   \begin{itemize}
  \item $m_{\tau \to 3\mu} = \dfrac{1970.3}{1969.1} \times 1777.7  =$\textcolor{blue}{$ 1778.8 \pm 1.1 MeV$}
  \end{itemize}
{~} \\ In agreement with 2011.
\end{small}
\end{center}


\column{2.5in}
\begin{center}
	Fit $\tau \to \mu\mu\mu$ in MC. \\
 \includegraphics[scale=0.11]{Ds_Mass/tau_mass_base.png}\\
%   \begin{itemize}
%  \item mean = $1777.7 \pm 0.4 MeV$ \\
%  \end{itemize} 
 
\end{center}
\end{columns}

\end{tiny}
\end{center}

}




	% \textref {M.Chrz\k{a}szcz 2013}

\end{frame}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5

\begin{frame}\frametitle{Background samples normalization}
\only<1>
{
	For the normalization of background samples($c\bar{c}$ and $b\bar{b}$) we used generator cuts efficiencies and corrected the nominal cross section accordingly:\\
	\begin{center}
 		$\mathcal{L} = \dfrac{N_{MC}}{\varepsilon_{acc} \times \varepsilon_{gen} \times \sigma_{LHCb}}$
 	\end{center}
The obtained luminosities(per 1M events):
\begin{exampleblock}{~}
\begin{enumerate}
\item $\mathcal{L}_{cc} = 0.25 \pm 0.04 pb^{-1}$
\item $\mathcal{L}_{bb} = 1.20 \pm 0.15 pb^{-1}$
 \end{enumerate}
 \end{exampleblock}
 
}
Dominant uncertainty from the cross section.


	% \textref {M.Chrz\k{a}szcz 2013}

\end{frame}




%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

\section{Peaking backgrounds}
\begin{frame}\frametitle{$\PDs \to \eta(\mu \mu \gamma) \mu \nu$}
\only<1>
{
 \begin{exampleblock}{~}
\begin{enumerate}
\item The dominant background source of peaking background in this analysis is  \textcolor{blue}{$\PDs \to \eta(\mu\mu\gamma) \mu \nu$}\\
\item In 2011 we suffered from lack of MC statistics.
\item Thanks to generator cuts our pdfs became more stable.
\item Pdf used: $\mathcal{P} = exp(m) \times Pol^n(m)$
 \end{enumerate}
 \end{exampleblock}

	\begin{columns}
\column{2.5in}
\begin{center}

  \includegraphics[scale=0.09]{RD_meeting/pid_0_65_0_725geo-0_48_0_05.png} \\
\begin{tiny} PID:$0.65;0.725$,GEO:$-0.48;0.05$ \end{tiny}
\end{center}

\column{2.5in}
\begin{center}
 \includegraphics[scale=0.09]{RD_meeting/pid_0_725_0_86geo0_35_0_65.png}\\
\begin{tiny} PID:$0.725;0.0.86$,GEO:$0.35;0.65$ \end{tiny}

\end{center}
\end{columns}
}

%	\textref {M.Chrz\k{a}szcz 2013}

\end{frame}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\begin{frame}\frametitle{$D \to \Ph \Ph \Ph $}
\only<1>
{
In 2011 we saw a triple miss-ID background: $\PDp \to \PK \Ppi \Ppi$. This background was in trash-bins that were not used in the analysis.\\
Also new sources of bck($D_x\to 3\pi$) are well under control.

	\begin{columns}
\column{1.6in}
\begin{center}
 \includegraphics[scale=0.17]{images/pipipi_peak_2011.pdf}\\
     \begin{itemize}
  \item 2011 data
  \end{itemize}
\end{center}
\column{1.6in}
\begin{center}
 \includegraphics[scale=0.17]{images/pipipi_peak_2012.pdf}\\
      \begin{itemize}
  \item 2012 data
  \end{itemize}
\end{center}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%55
\column{1.6in}
\begin{center}
 \includegraphics[scale=0.19]{images/FittoDkpipi_2012.pdf}\\{~}\\
      \begin{itemize}
  \item 2012 data
  \end{itemize}
\end{center}


\end{columns}
{~}\\
In 2012 there is still no significant amount of triple mis-ID background in the bins important to the analysis.




}

%	\textref {M.Chrz\k{a}szcz 2013}

\end{frame}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5




\section{MVA development}
\begin{frame}\frametitle{Isolating parameters}
{~}
\only<1>
{
Inputs for isolating parameter(based on Giampiero work):
\begin{center}
    \begin{tabular}{ | c | p{10cm} |}
    \hline
Variable & Description \\ \hline
    \hline
    IP $\chi^2$ & Impact parameter $\chi^2$ wrt any PV \\ \hline
    IP  & Impact parameter wrt any PV \\ \hline
    angle  & angle between $\mu$ and track \\ \hline 
    doca  & doca between the $\mu$ and the track \\    \hline
    PVdis & $\vert \overrightarrow{TV} - \overrightarrow{PV} \vert$, signed according to $z_{TV} - z_{PV}$. \\ \hline
    SVdis & $\vert \overrightarrow{TV} - \overrightarrow{SV} \vert$, signed according to $z_{STV} - z_{PV}$. \\ \hline
   fc & $\dfrac{\vert \overrightarrow{P_{\mu}} + \overrightarrow{P_{tr}} \times \alpha }{\vert \overrightarrow{P_{\mu}} + \overrightarrow{P_{tr}} \times \alpha + P_{T_{\mu}}+ P_{T_{tr}}}$\footnote{$\alpha$ is the angle between $\overrightarrow{P}_{\mu} + \overrightarrow{P}_{tr}$ and $\overrightarrow{PV} - \overrightarrow{TV}$  }\\ \hline
    
        
        	
    \end{tabular}
\end{center}





}

\only<2>
{	

\begin{enumerate}

\item	In 2011 we used the isolation parameter developed for $\PBs \to \mu\mu$. For 2012 data we optimised the isolation parameter for our channel based on MVA(BDT).
\item We follow two approaches: train a MVA on signal vs. bkg tracks, and the isolating vs. non-isolating tracks.
\item We see a big improvement compared to old isolation.
 \end{enumerate}
 
	\begin{columns}
\column{1.6in}
\begin{center}

  \includegraphics[scale=0.15]{RD_meeting/mva_BDT.png} \\

\end{center}

\column{1.6in}
\begin{center}
 \includegraphics[scale=0.15]{RD_meeting/rejBvsS.png}\\

\end{center}

\column{1.6in}
\begin{center}
 \includegraphics[scale=0.15]{images/Laura/rejBvsS.png}\\

\end{center}

\end{columns}

}
	% \textref {M.Chrz\k{a}szcz 2013}

\end{frame}


\begin{frame}\frametitle{Ensemble Selection}
{~}

\begin{exampleblock}{~}
\begin{enumerate}
\item In the last few years people winning leading machine learning contests started to combine their classifiers to squeeze the best out of them.
\item This technique/method is know as Ensemble Selection or Blending.
\item The plan for $\tau \to \mu \mu \mu$ is to take it to the next level.
\item Combine not only different signal classifiers, but also different $\tau$ sources(slide 4).
\item Allows for usage different isolating parameters for each channel.
 \end{enumerate}
 \end{exampleblock}	
		
\end{frame}


\begin{frame}\frametitle{Ensemble Selection - How to}
{~}
How to make an Ensemble Selection
\begin{exampleblock}{~}
\begin{enumerate}
\item Construct a reduced training set.
\item Train you different models on the reduced training set.
\item Combine/Blend all the models on the rest of the data set.
\item The output is a function that mixes the individual model predictions into a blended prediction, hopefully better than any individual result.
 \end{enumerate}
 \end{exampleblock}	
		
\end{frame}

\begin{frame}\frametitle{Ensemble Selection}

%%%%%%%%%%%%%%%%%%%%%%%5
	\begin{columns}
\column{1.6in}
\begin{center}
  \includegraphics[scale=0.15]{RD_meeting/rejBvsS_21513000.png}\\
   \begin{itemize}
  \item $\PB \to \PD \to \tau$
  \end{itemize}
\end{center}

\column{1.6in}
\begin{center}
 \includegraphics[scale=0.15]{RD_meeting/rejBvsS_21513001.png}\\
    \begin{itemize}
  \item $\PD \to \tau$
  \end{itemize}
\end{center}

\column{1.6in}
\begin{center}
 \includegraphics[scale=0.15]{RD_meeting/rejBvsS_23513000.png}\\
     \begin{itemize}
  \item $\PB \to \PDs \to \tau$
  \end{itemize}
\end{center}


%\column{2.5in}
%\begin{center}
% \includegraphics[scale=0.15]{RD_meeting/rejBvsS_23513001.png}\\
%      \begin{itemize}
 % \item $\PDs \to \tau$
%  \end{itemize}
%\end{center}
\end{columns}

\end{frame}
\begin{frame}\frametitle{Ensemble Selection}

%	\begin{columns}
%\column{2.5in}
%	  \includegraphics[scale=0.2]{RD_meeting/rejBvsS_oryginal.png}
%	\column{2.5in}
%		  \includegraphics[scale=0.2]{RD_meeting/rejBvsS_blend.png}
%	\end{columns}



\begin{center}
  \includegraphics[scale=0.3]{images/BDT_comparison.png}
\end{center}



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

\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5555
\section{Binning optimisation}

\begin{frame}\frametitle{Binning optimisation}
{~}
\only<1>
{	
For the 2011 analysis we had two classifiers: $PIDNN$ and $M_{GEO}$. Each of them we optimised separately. For the 2012 analysis we are performing a simultaneous 2D optimisation.

	\begin{columns}
\column{2.5in}


	  \includegraphics[scale=0.13]{inflaton/punzi1.png}
	    \begin{itemize}
  \item FOM as a function of N. of bins.
  \end{itemize}
	\column{2.5in}
		  \includegraphics[scale=0.27]{RD_meeting/2d-data.pdf}
	    \begin{itemize}
  \item Signal efficiency in 2011 binning.
  \end{itemize}
	\end{columns}
	
}

\end{frame}

\section{Model dependence}
\begin{frame}\frametitle{Model dependence}
\begin{exampleblock}{Minimal Lepton Flavour Violation Model\footnote{arXiv:0707.0988}}
\begin{itemize}
\item In effective-field-theory we introduce new operators that at electro-weak scale are compatible with $SU(2)_L \times U(1)$.
\item Left handed lepton doublets add right handed lepton singlets follow the group symmetry: $G_{LF} = SU(3)_L \times SU(3)_E$.
\item LFV arises from breaking this group.
\item We focus on three operators that have dominant contribution to NP:
\begin{enumerate}
\item Purely left handed iterations: $(\overline{L} \gamma_{\mu} L)(\overline{L} \gamma^{\mu} L)$
\item Mix term: $(\overline{R}\gamma_{\mu} R)(\overline{L} \gamma^{\mu} L)$
\item Radiative operator: $g'(\overline{L}H\sigma_{\mu\nu}R)B^{\mu\nu}$
\end{enumerate}
\end{itemize}
 \end{exampleblock}	

\end{frame}


\begin{frame}\frametitle{Reweighting  MC samples}
\only<1>{
\begin{center}
\begin{columns}
\column{2.5in}
{~}Reconstruction:\\
	{~}\includegraphics[scale=0.22]{images/acceptance.png}

\column{2.5in}
Offline:\\
	 \includegraphics[scale=0.22]{images/offline.png}


\end{columns}
\end{center}
}

\only<2>{
\begin{center}
\begin{columns}
\column{1.6in}
{~}$(\overline{L} \gamma_{\mu} L)(\overline{L} \gamma^{\mu} L)$\\
	{~}\includegraphics[scale=0.22]{images/gammallll.png}

\column{1.6in}
$(\overline{R}\gamma_{\mu} R)(\overline{L} \gamma^{\mu} L)$\\
	 \includegraphics[scale=0.22]{images/gammallrr.png}
\column{1.6in}
$g'(\overline{L}H\sigma_{\mu\nu}R)B^{\mu\nu}$\\
	 \includegraphics[scale=0.22]{images/gammarad.png}

\end{columns}
\end{center}
}

\begin{equation}
\epsilon_{gen\&rec} = C\epsilon^{LHCbMC}_{gen\&rec} \sum \rho^{model}(m_{12},m_{23})
\end{equation}

\only<1>{
\begin{itemize}
\item Simulated signal events with PHSP
\item Take into account reconstruction and selection.
\item Reweight accordingly to a given distribution.
\end{itemize}


}


\only<2>{
\begin{itemize}
\item Simulated signal events with PHSP
\item Take into account reconstruction and selection.
\item Reweight accordingly to a given distribution.
\end{itemize}


}

\end{frame}











\section{Conclusions}

\begin{frame}\frametitle{Conclusions}
{~}
\only<1>
{	
\begin{exampleblock}{~}
\begin{enumerate}
\item Analysis is well underway.
\item More efficient use of computing resources and increased MC
      statistics helps at all ends
\item Hope to improve the MVA/binning.
 \end{enumerate}
 \end{exampleblock}	
}
 \includegraphics[scale=0.4]{RD_meeting/phd052805.png}\\



\end{frame}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

\begin{frame}
{~}
\begin{Huge}
BACKUP
\end{Huge}


\end{frame}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%55

\begin{frame}\frametitle{$B \to \tau$}
{~}\\
We really suck in selecting this channel.

\includegraphics[scale=0.4]{tmva/ROC_31113002.png}



	% \textref {M.Chrz\k{a}szcz 2013}
\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5
\begin{frame}\frametitle{$B \to D_s \to \tau$}
{~}\\
On the biggest contributing channel we are quite optimal.


\includegraphics[scale=0.4]{tmva/ROC_23513000.png}



	% \textref {M.Chrz\k{a}szcz 2013}
\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5
\begin{frame}\frametitle{$D_s \to \tau$}
{~}\\
On the biggest contributing channel we are quite optimal.


\includegraphics[scale=0.4]{tmva/ROC_23513001.png}



	%\textref {M.Chrz\k{a}szcz 2013}
\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5
\begin{frame}\frametitle{$B \to D^+ \to \tau$}
{~}\\
On the biggest contributing channel we are quite optimal.


\includegraphics[scale=0.4]{tmva/21513000_roc2.png}



	% \textref {M.Chrz\k{a}szcz 2013}
\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5
\begin{frame}\frametitle{$D^+ \to \tau$}
{~}\\
On the biggest contributing channel we are quite optimal.


\includegraphics[scale=0.4]{tmva/ROC_21513001.png}



	%\textref {M.Chrz\k{a}szcz 2013}
\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5

\begin{frame}\frametitle{Comparison on mix sample}
{~}\\
On the biggest contributing channel we are quite optimal.


\includegraphics[scale=0.4]{tmva/mix.png}



	%\textref {M.Chrz\k{a}szcz 2013}
\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5
\begin{frame}\frametitle{Conclusions on TMVA}
{~}\\
\begin{itemize}
\item Each of the signal components is enormously larger than MVA trained on mix.
\item Method looks very promising if we can find a nice blending method(work for next week).
\item Mayby discusion on TMVA/MatrixNet/Neurobayes is next to leading order effect compared to this method?


\end{itemize}


%	\textref {M.Chrz\k{a}szcz 2013}
\end{frame}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5
\begin{frame}\frametitle{Comparison on mix sample}
{~}\\
	\begin{columns}
\column{2.5in}


	  \includegraphics[scale=0.27]{RD_meeting/rejBvsS_oryginal.png}
	
	\column{2.5in}
		  \includegraphics[scale=0.27]{RD_meeting/rejBvsS_blend.png}

	\end{columns}


	%\textref {M.Chrz\k{a}szcz 2013}
\end{frame}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\begin{frame}\frametitle{$D_s$ correction}
{~}


\only<1>
{	

	\begin{columns}
\column{2.5in}
  \includegraphics[scale=0.18]{Ds_Splot/cdf1.png} \\



\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/cdf2.png}\\


\end{columns}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	\begin{columns}
\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/ciso.png}\\



\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/doca12.png}\\


\end{columns}


}



\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5555
\begin{frame}\frametitle{$D_s$ correction}
{~}


\only<1>
{	

	\begin{columns}
\column{2.5in}
  \includegraphics[scale=0.18]{Ds_Splot/doca23.png} \\



\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/doca13.png}\\


\end{columns}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	\begin{columns}
\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/FD.png}\\



\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/FDE.png}\\


\end{columns}


}

	

\end{frame}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5555
\begin{frame}\frametitle{$D_s$ correction}
{~}


\only<1>
{	

	\begin{columns}
\column{2.5in}
  \includegraphics[scale=0.18]{Ds_Splot/IP.png} \\



\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/isoa.png}\\


\end{columns}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	\begin{columns}
\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/isob.png}\\



\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/isoc.png}\\


\end{columns}


}

	

\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5555
\begin{frame}\frametitle{$D_s$ correction}
{~}


\only<1>
{	

	\begin{columns}
\column{2.5in}
  \includegraphics[scale=0.18]{Ds_Splot/isod.png} \\



\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/isoe.png}\\


\end{columns}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	\begin{columns}
\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/isof.png}\\



\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/Life_time.png}\\


\end{columns}


}

	

\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5555
\begin{frame}\frametitle{$D_s$ correction}
{~}


\only<1>
{	

	\begin{columns}
\column{2.5in}
  \includegraphics[scale=0.18]{Ds_Splot/p0_IP.png} \\



\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/p0_IPSig.png}\\


\end{columns}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	\begin{columns}
\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/p1_IP.png}\\



\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/p1_IPSig.png}\\


\end{columns}


}

	

\end{frame}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5555
\begin{frame}\frametitle{$D_s$ correction}
{~}


\only<1>
{	

	\begin{columns}
\column{2.5in}
  \includegraphics[scale=0.18]{Ds_Splot/p2_IP.png} \\



\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/p2_IPSig.png}\\


\end{columns}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	\begin{columns}
\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/pangle.png}\\



\column{2.5in}
 \includegraphics[scale=0.18]{Ds_Splot/pt.png}\\


\end{columns}


}

	

\end{frame}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5555
\begin{frame}\frametitle{$D_s$ correction}
{~}


\only<1>
{	


  \includegraphics[scale=0.18]{Ds_Splot/vtxchi2.png} \\



}

	

\end{frame}



\end{document}