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\title{Updates from Krakow}  
\author{Marcin Chrzaszcz}

\date{\today} 

\begin{document}

{
\institute{Institute of Nuclear Physics PAN}
\setbeamertemplate{footline}{} 
\begin{frame}
  \titlepage
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\institute{IFJ PAN}



%tutaj mamy pierwsza strone


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

%normal slides
\begin{frame}\frametitle{FITS}

Marc sugestions:
\begin{enumerate}
\item Check with different strategies
( RooFit::Strategy(4), etc.)
\item Change the mass window and see what happens. 
Mark said that if the fit will still be rising you have to prove, by changing the window get the rising fit and compare the expected number of events. If they don't change much it's ok.
\end{enumerate}
\end{frame}

\begin{frame}\frametitle{1st Point}

I checked all possible strategies, with different ranges(even 100 times to big). The fit is stable as hell =)
\end{frame}

\begin{frame}\frametitle{FITS}


\begin{columns}[c]
	
\newline	
\column{3.5in}
	\includegraphics[scale=0.35]{160_195.png}
\column{1.5in}
\begin{block}{Standard fit}
Not changed mass window
\end{block}
\end{columns}
\end{frame}


\begin{frame}\frametitle{FITS}





\begin{columns}[c]
	
\newline	
\column{3.5in}
	\includegraphics[scale=0.35]{b.png}
\column{1.5in}
\begin{block}{Different mass window}
Throwing away only one marked point gives flat distribution.

\end{block}
\end{columns}
\end{frame}



\begin{frame}
\begin{columns}[c]
	
\newline	
\column{3.5in}
	\includegraphics[scale=0.35]{a.png}
\column{1.5in}
\begin{block}{Different mass window}
Throwing away more point gives us droping distributions.

\end{block}
\end{columns}
\end{frame}









\begin{frame}\frametitle{FITS}
\begin{columns}[c]
	
\newline	
\column{3.5in}
	\includegraphics[scale=0.35]{pm80.png}
\column{1.5in}
\begin{block}{Different mass window}
$80MeV$ Mass window.
\end{block}
\end{columns}
\end{frame}


\begin{frame}\frametitle{Summary}
\begin{enumerate}
\item	I tested this in every way I could. 
\item	Consulted with coleagues that are doing fits all the time(they didn't find any mistake).
\item 	The most important: Different mass ranges change the expected number of backgrounds eventes arround $5\%$ so it's not relewant.
	\end{enumerate}
	
	
	
\end{frame}
	
	
\begin{frame}\frametitle{Updates on the numbers}

I changed the range the from which I extrapolate the number of backgorund from the same region $(1650,1900)\setminus(1743,1803)MeV$

\begin{scriptsize}

\begin{center}
\begin{tabular}{|c|c|c|c|c|c|}
\hline
\textbf{PID} & \textbf{GL}  & \textbf{Linear} & \textbf{Error lin } & \textbf{EXP} & \textbf{Error. Exp}\\

\hline
 %$ 0.03 , 0.07 $ & $ -1.0 , 0.116 $ & $225.286975$ & $3.720377$ & $214.762667$ & $6.453331$  \\
 $ 0.03 , 0.07 $ & $ -1.00 , 0.116 $ & $223.681440$ & $4.285854$ & $215.951131$ & $4.703320$  \\
\hline
% $ 0.03 , 0.07 $ & $ 0.116 , 0.44 $ & $25.334704$ & $0.730938$ & $22.658613$ & $3.382960$  \\ 
 $ 0.03 , 0.07 $ & $ 0.116 , 0.44 $ & $22.170251$ & $0.770944$ & $20.381995$ & $2.351677$  \\ 
\hline
% $ 0.03 , 0.07 $ & $ 0.44 , 0.616 $ & $6.315243$ & $0.557466$ & $6.259470$ & $0.429338$  \\ 
 $ 0.03 , 0.07 $ & $ 0.44 , 0.616 $ & $6.432532$ & $0.685642$ & $6.389303$ & $0.297094$  \\ 
\hline
 $ 0.03 , 0.07 $ & $ 0.616 , 1.0 $ & $1.863888$ & $0.980816$ & $1.379745$ & $0.967495$  \\
 %$ 0.03 , 0.07 $ & $ 0.616 , 1.0 $ & $2.101699$ & $0.879121$ & $1.433717$ & $1.249549$  \\
\hline
%$ 0.07 , 1.0 $ & $ -1.0, 0.116 $ & $113.445685$ & $3.673353$ & $108.791320$ & $-3.605409$  \ 
$ 0.07, 1.0 $ & $ -1.0 , 0.116 $ & $112.765871$ & $3.022240$ & $106.582612$ & $4.852854$  \\ 
\hline
% $ 0.07 , 1.0 $ & $ 0.116 , 0.44 $ & $15.177247$ & $0.424522$ & $10.128789$ & $3.232027$  \\
  $ 0.07 , 1.0 $ & $ 0.116 , 0.44 $ & $13.728065$ & $0.462664$ & $10.022689$ & $2.584259$  \\
\hline
%$ 0.07 , 1.0 $ & $ 0.440 , 0.616 $ & $4.828111$ & $0.422406$ & $4.066456$ & $1.435559$  \\
$ 0.07 , 1.0$ & $ 0.440, 0.616 $ & $6.042397$ & $0.299367$ & $5.315554$ & $1.423532$  \\ 
\hline
% $ 0.07 , 1.0 $ & $ 0.616 , 1.0 $ & $3.871274$ & $1.701825$ & $3.372127$ & $1.346100$  \\
  $ 0.07 , 1.0 $ & $ 0.616 , 1.0 $ & $3.691082$ & $1.955345$ & $3.329173$ & $1.026430$  \\ 
\hline



\end{tabular}	
\end{center}
\end{scriptsize}
	
\end{frame}
	
	
	
\begin{frame}\frametitle{Updates on the numbers}

\begin{scriptsize}

\begin{center}
\begin{tabular}{|c|c|c|c|c|c|}
\hline
\textbf{PID} & \textbf{GL}  & \textbf{Linear} & \textbf{Error lin } & \textbf{EXP} & \textbf{Error. Exp}\\

\hline
 %$ 0.03 , 0.07 $ & $ -1.0 , 0.116 $ & $225.286975$ & $3.720377$ & $214.762667$ & $6.453331$  \\
 $ -0.03 , -0.005 $ & $ -1.0 , 0.116 $ & $612.515740$ & $5.517984$ & $608.152648$ & $3.209168$  \\
\hline
% $ 0.03 , 0.07 $ & $ 0.116 , 0.44 $ & $25.334704$ & $0.730938$ & $22.658613$ & $3.382960$  \\ 
 $ -0.03 , -0.005 $ & $ 0.116 , 0.44 $ & $48.887154$ & $2.455029$ & $48.605891$ & $1.225935$  \\ 
\hline
% $ 0.03 , 0.07 $ & $ 0.44 , 0.616 $ & $6.315243$ & $0.557466$ & $6.259470$ & $0.429338$  \\ 
$ -0.03 , -0.005 $ & $ 0.44 , 0.616 $ & $12.568007$ & $0.880412$ & $10.282640$ & $2.259703$  \\
\hline
$ -0.03 , -0.005 $ & $ 0.616 , 1.0 $ & $4.898097$ & $1.134637$ & $2.879837$ & $1.518258$  \\ 
 %$ 0.03 , 0.07 $ & $ 0.616 , 1.0 $ & $2.101699$ & $0.879121$ & $1.433717$ & $1.249549$  \\
\hline
%$ 0.07 , 1.0 $ & $ -1.0, 0.116 $ & $113.445685$ & $3.673353$ & $108.791320$ & $-3.605409$  \ 
 $ -0.005 , 0.03 $ & $ -1.0 , 0.116 $ & $388.613829$ & $4.015244$ & $385.164540$ & $3.033609$  \\
\hline
% $ 0.07 , 1.0 $ & $ 0.116 , 0.44 $ & $15.177247$ & $0.424522$ & $10.128789$ & $3.232027$  \\
 $ -0.005 , 0.03 $ & $ 0.116 , 0.44 $ & $37.193932$ & $0.995706$ & $32.771010$ & $3.456820$  \\
\hline
%$ 0.07 , 1.0 $ & $ 0.440 , 0.616 $ & $4.828111$ & $0.422406$ & $4.066456$ & $1.435559$  \\
$ -0.005 , 0.03 $ & $ 0.44 , 0.616 $ & $8.976528$ & $0.847767$ & $8.533797$ & $1.034161$  \\
\hline
% $ 0.07 , 1.0 $ & $ 0.616 , 1.0 $ & $3.871274$ & $1.701825$ & $3.372127$ & $1.346100$  \\
$ -0.005 , 0.03 $ & $ 0.616 , 1.0 $ & $5.757810$ & $0.896886$ & $5.176158$ & $1.295585$  \\
\hline



\end{tabular}	
\end{center}
\end{scriptsize}
	
\end{frame}
\begin{frame}\frametitle{EvtGen model, without Geant}


	\includegraphics[scale=0.35]{old_new.png}
	
	Looks much better. On on "eye test" it very similar to the one found in Martas Paper.
	
	
	
\end{frame}
	
	
\begin{frame}\frametitle{News about the production}

I assume that the binning is well described in aboved chapters.

For each bin mention in previous chepter we calculate the expected background events, by fitting to the real data with cutten mass window exponential and linear function. The fitting mass range of $\tau$ is $(1600, 1747) \cap (1807,1950) MeV$. 
The expected number of backgrounds with errors are showned in below table.

\begin{center}
\begin{tabular}{|c|c|c|c|c|c|}
\hline
\textbf{PID} & \textbf{GL}  & \textbf{Linear} & \textbf{Error lin } & \textbf{EXP} & \textbf{Error. Exp}\\

\hline
 %$ 0.03 , 0.07 $ & $ -1.0 , 0.116 $ & $225.286975$ & $3.720377$ & $214.762667$ & $6.453331$  \\
 $ 0.03 , 0.07 $ & $ -1.00 , 0.116 $ & $223.681440$ & $4.285854$ & $215.951131$ & $4.703320$  \\
\hline
% $ 0.03 , 0.07 $ & $ 0.116 , 0.44 $ & $25.334704$ & $0.730938$ & $22.658613$ & $3.382960$  \\ 
 $ 0.03 , 0.07 $ & $ 0.116 , 0.44 $ & $22.170251$ & $0.770944$ & $20.381995$ & $2.351677$  \\ 
\hline
% $ 0.03 , 0.07 $ & $ 0.44 , 0.616 $ & $6.315243$ & $0.557466$ & $6.259470$ & $0.429338$  \\ 
 $ 0.03 , 0.07 $ & $ 0.44 , 0.616 $ & $6.432532$ & $0.685642$ & $6.389303$ & $0.297094$  \\ 
\hline
 $ 0.03 , 0.07 $ & $ 0.616 , 1.0 $ & $1.863888$ & $0.980816$ & $1.379745$ & $0.967495$  \\
 %$ 0.03 , 0.07 $ & $ 0.616 , 1.0 $ & $2.101699$ & $0.879121$ & $1.433717$ & $1.249549$  \\
\hline
%$ 0.07 , 1.0 $ & $ -1.0, 0.116 $ & $113.445685$ & $3.673353$ & $108.791320$ & $-3.605409$  \ 
$ 0.07, 1.0 $ & $ -1.0 , 0.116 $ & $112.765871$ & $3.022240$ & $106.582612$ & $4.852854$  \\ 
\hline
% $ 0.07 , 1.0 $ & $ 0.116 , 0.44 $ & $15.177247$ & $0.424522$ & $10.128789$ & $3.232027$  \\
  $ 0.07 , 1.0 $ & $ 0.116 , 0.44 $ & $13.728065$ & $0.462664$ & $10.022689$ & $2.584259$  \\
\hline
%$ 0.07 , 1.0 $ & $ 0.440 , 0.616 $ & $4.828111$ & $0.422406$ & $4.066456$ & $1.435559$  \\
$ 0.07 , 1.0$ & $ 0.440, 0.616 $ & $6.042397$ & $0.299367$ & $5.315554$ & $1.423532$  \\ 
\hline
% $ 0.07 , 1.0 $ & $ 0.616 , 1.0 $ & $3.871274$ & $1.701825$ & $3.372127$ & $1.346100$  \\
  $ 0.07 , 1.0 $ & $ 0.616 , 1.0 $ & $3.691082$ & $1.955345$ & $3.329173$ & $1.026430$  \\ 
\hline
 %$ 0.03 , 0.07 $ & $ -1.0 , 0.116 $ & $225.286975$ & $3.720377$ & $214.762667$ & $6.453331$  \\
 $ -0.03 , -0.005 $ & $ -1.0 , 0.116 $ & $612.515740$ & $5.517984$ & $608.152648$ & $3.209168$  \\
\hline
% $ 0.03 , 0.07 $ & $ 0.116 , 0.44 $ & $25.334704$ & $0.730938$ & $22.658613$ & $3.382960$  \\ 
 $ -0.03 , -0.005 $ & $ 0.116 , 0.44 $ & $48.887154$ & $2.455029$ & $48.605891$ & $1.225935$  \\ 
\hline
% $ 0.03 , 0.07 $ & $ 0.44 , 0.616 $ & $6.315243$ & $0.557466$ & $6.259470$ & $0.429338$  \\ 
$ -0.03 , -0.005 $ & $ 0.44 , 0.616 $ & $12.568007$ & $0.880412$ & $10.282640$ & $2.259703$  \\
\hline
$ -0.03 , -0.005 $ & $ 0.616 , 1.0 $ & $4.898097$ & $1.134637$ & $2.879837$ & $1.518258$  \\ 
 %$ 0.03 , 0.07 $ & $ 0.616 , 1.0 $ & $2.101699$ & $0.879121$ & $1.433717$ & $1.249549$  \\
\hline
%$ 0.07 , 1.0 $ & $ -1.0, 0.116 $ & $113.445685$ & $3.673353$ & $108.791320$ & $-3.605409$  \ 
 $ -0.005 , 0.03 $ & $ -1.0 , 0.116 $ & $388.613829$ & $4.015244$ & $385.164540$ & $3.033609$  \\
\hline
% $ 0.07 , 1.0 $ & $ 0.116 , 0.44 $ & $15.177247$ & $0.424522$ & $10.128789$ & $3.232027$  \\
 $ -0.005 , 0.03 $ & $ 0.116 , 0.44 $ & $37.193932$ & $0.995706$ & $32.771010$ & $3.456820$  \\
\hline
%$ 0.07 , 1.0 $ & $ 0.440 , 0.616 $ & $4.828111$ & $0.422406$ & $4.066456$ & $1.435559$  \\
$ -0.005 , 0.03 $ & $ 0.44 , 0.616 $ & $8.976528$ & $0.847767$ & $8.533797$ & $1.034161$  \\
\hline
% $ 0.07 , 1.0 $ & $ 0.616 , 1.0 $ & $3.871274$ & $1.701825$ & $3.372127$ & $1.346100$  \\
$ -0.005 , 0.03 $ & $ 0.616 , 1.0 $ & $5.757810$ & $0.896886$ & $5.176158$ & $1.295585$  \\
\hline



\end{tabular}	
\end{center}


\end{frame}








\end{document}