\documentclass[xcolor=svgnames]{beamer} \usepackage[utf8]{inputenc} \usepackage[english]{babel} \usepackage{polski} %\usepackage{amssymb,amsmath} %\usepackage[latin1]{inputenc} %\usepackage{amsmath} %\newcommand\abs[1]{\left|#1\right|} \usepackage{amsmath} \newcommand\abs[1]{\left|#1\right|} \usepackage{hepnicenames} \usepackage{hepunits} \usepackage{color} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5 \definecolor{mygreen}{cmyk}{0.82,0.11,1,0.25} \usetheme{Sybila} \title[Cross checks]{Cross checks} \author{Marcin Chrz\k{a}szcz$^{1}$, Nicola Serra$^{1}$} \institute{$^1$~University of Zurich} \date{\today} \begin{document} % --------------------------- SLIDE -------------------------------------------- \frame[plain]{\titlepage} \author{Marcin Chrz\k{a}szcz{~}} \institute{(UZH)} % ------------------------------------------------------------------------------ % --------------------------- SLIDE -------------------------------------------- \section{Background studies} \begin{frame}\frametitle{Comparison MoM with LL fit} \begin{columns} \begin{column}{2.5in} \includegraphics[width=0.9\textwidth]{obs/Fl.pdf}\\ \includegraphics[width=0.9\textwidth]{obs/S3.pdf} \end{column} \begin{column}{2.5in} \includegraphics[width=0.9\textwidth]{obs/Fs.pdf}\\ \includegraphics[width=0.9\textwidth]{obs/S4.pdf} \end{column} \end{columns} \end{frame} \begin{frame}\frametitle{Comparison MoM with LL fit} \begin{columns} \begin{column}{2.5in} \includegraphics[width=0.9\textwidth]{obs/S5.pdf}\\ \includegraphics[width=0.9\textwidth]{obs/S6.pdf} \end{column} \begin{column}{2.5in} \includegraphics[width=0.9\textwidth]{obs/S7.pdf}\\ \includegraphics[width=0.9\textwidth]{obs/S8.pdf} \end{column} \end{columns} \end{frame} \begin{frame}\frametitle{Expected differences, MoM vs fit} \begin{itemize} \item We checked this already but as number of sigma is a bit to large for me. \item Let me put once again all the numbers I have in once place. \end{itemize} \only<1>{ \begin{itemize} \item Here Signal only, WITH acceptance. \end{itemize} \begin{tiny} \begin{tabular}{ |c |c | c | c| c| c| c| c|c|} \hline {~} & \multicolumn{8}{|c|}{ absolute expected difference at $68\%$ CL} \\ \hline $q^2 [GeV^2 /c^4]$ & $F_l$ & $S_3$ & $S_4$ & $S_5$ & $S_6$ & $S_7$ & $S_8$ & $S_9$ \\ \hline $0.1 - 0.98$ & $0.035$ & $0.021$ & $0.044$ & $0.028$ & $0.073$ & $0.025$ & $0.038$ & $0.062$ \\ \hline $1.1 - 2.5$ & $0.062$ & $0.065$ & $0.082$ & $0.061$ & $0.073$ & $0.065$ & $0.084$ & $0.062$ \\ \hline $2.5 - 4.0$ & $0.062$ & $0.067$ & $0.085$ & $0.077$ & $0.065$ & $0.072$ & $0.080$ & $0.042$ \\ \hline $4.0 - 6.0$ & $0.043$ & $0.044$ & $0.059$ & $0.056$ & $0.027$ & $0.052$ & $0.054$ & $0.038$ \\ \hline $6.0 - 8.0$ & $0.038$ & $0.042$ & $0.056$ & $0.053$ & $0.028$ & $0.045$ & $0.051$ & $0.027$ \\ \hline $15.0 - 17.0$ & $0.027$ & $0.044$ & $0.051$ & $0.042$ & $0.032$ & $0.034$ & $0.045$ & $0.034$ \\ \hline $17.0 - 19.0$ & $0.034$ & $0.059$ & $0.066$ & $0.055$ & $0.044$ & $0.043$ & $0.056$ & $0.049$ \\ \hline \end{tabular} \end{tiny} } \end{frame} \begin{frame}\frametitle{Pull distribution} \begin{itemize} \item Take the observed difference($S_x^{MoM}-S_x^{Fit}$) and divide by the expected difference from table above. \end{itemize} \includegraphics[width=0.6\textwidth]{obs/pull.pdf} \begin{itemize} \item Important note: The fit I do is weighted, but the pull was obtained using Christoph fit which is unweighed, aka we are comparing apples to oranges here. \item Now repeat the exercise with my own fit weighted fit. \end{itemize} \end{frame} \begin{frame}\frametitle{Comparison MoM with LL fit} \begin{columns} \begin{column}{2.5in} \includegraphics[width=0.9\textwidth]{obs2/Fl.pdf}\\ \includegraphics[width=0.9\textwidth]{obs2/S3.pdf} \end{column} \begin{column}{2.5in} \includegraphics[width=0.9\textwidth]{obs2/Fs.pdf}\\ \includegraphics[width=0.9\textwidth]{obs2/S4.pdf} \end{column} \end{columns} \end{frame} \begin{frame}\frametitle{Comparison MoM with LL fit} \begin{columns} \begin{column}{2.5in} \includegraphics[width=0.9\textwidth]{obs2/S5.pdf}\\ \includegraphics[width=0.9\textwidth]{obs2/S6.pdf} \end{column} \begin{column}{2.5in} \includegraphics[width=0.9\textwidth]{obs2/S7.pdf}\\ \includegraphics[width=0.9\textwidth]{obs2/S8.pdf} \end{column} \end{columns} \end{frame} \begin{frame}\frametitle{Pull distribution} \begin{itemize} \item Take the observed difference($S_x^{MoM}-S_x^{Fit}$) and divide by the expected difference from table above. \end{itemize} \includegraphics[width=0.6\textwidth]{obs2/pull.pdf} \begin{itemize} \item Now oranges to oranges. \end{itemize} \end{frame} \begin{frame}%\frametitle{~} \begin{Huge} \center{BACKUP} \end{Huge} \end{frame} \begin{frame}\frametitle{Comparison MoM with LL fit} \begin{columns} \begin{column}{2.5in} \includegraphics[width=0.9\textwidth]{obs/S5_P.pdf} \end{column} \begin{column}{2.5in} \includegraphics[width=0.9\textwidth]{obs/S9.pdf}\\ \end{column} \end{columns} \begin{itemize} \item My personal opinion: Despite what is expected the left plot scares the hell out of me! \end{itemize} \end{frame} \begin{frame}\frametitle{Expected differences, MoM vs fit} \begin{itemize} \item We checked this already but as number of sigma is a bit to large for me. \item Let me put once again all the numbers I have in once place. \end{itemize} \only<1>{ \begin{itemize} \item Here Signal only, no acceptance. \end{itemize} \begin{tiny} \begin{tabular}{ |c |c | c | c| c| c| c| c|c|} \hline {~} & \multicolumn{8}{|c|}{ absolute expected difference at $68\%$ CL} \\ \hline $q^2 [GeV^2 /c^4]$ & $F_l$ & $S_3$ & $S_4$ & $S_5$ & $S_6$ & $S_7$ & $S_8$ & $S_9$ \\ \hline $0.1 - 0.98$ & $0.015$ & $0.014$ & $0.023$ & $0.014$ & $0.013$ & $0.012$ & $0.019$ & $0.021$ \\ \hline $1.1 - 2.5$ & $0.021$ & $0.025$ & $0.026$ & $0.024$ & $0.015$ & $0.024$ & $0.025$ & $0.020$ \\ \hline $2.5 - 4.0$ & $0.020$ & $0.022$ & $0.024$ & $0.025$ & $0.013$ & $0.023$ & $0.024$ & $0.016$ \\ \hline $4.0 - 6.0$ & $0.016$ & $0.017$ & $0.021$ & $0.020$ & $0.010$ & $0.019$ & $0.019$ & $0.015$ \\ \hline $6.0 - 8.0$ & $0.015$ & $0.017$ & $0.021$ & $0.018$ & $0.011$ & $0.016$ & $0.018$ & $0.015$ \\ \hline $15.0 - 17.0$ & $0.015$ & $0.022$ & $0.025$ & $0.018$ & $0.017$ & $0.014$ & $0.021$ & $0.018$ \\ \hline $17.0 - 19.0$ & $0.018$ & $0.026$ & $0.030$ & $0.022$ & $0.021$ & $0.018$ & $0.025$ & $0.024$ \\ \hline \end{tabular} \end{tiny} } \end{frame} \begin{frame}\frametitle{Expected differences, MoM vs fit} \begin{tiny} \begin{tabular}{ |c |c | c | c| c| c| c| c|c|} \hline {~} & \multicolumn{8}{|c|}{ observed difference in terms of sigmas} \\ \hline $q^2 [GeV^2 /c^4]$ & $F_l$ & $S_3$ & $S_4$ & $S_5$ & $S_6$ & $S_7$ & $S_8$ & $S_9$ \\ \hline $0.1 - 0.98$ & $-0.618$ & $-0.827$ & $-0.074$ & $0.794$ & $0.447$ & $-0.807$ & $0.581$ & $0.2374$ \\ \hline $1.1 - 2.5$ & $-0.624$ & $-1.687$ & $-0.518$ & $-1.4854$ & $0.932$ & $1.334$ & $0.5260$ & $-0.632$ \\ \hline $2.5 - 4.0$ & $-0.106$ & $-0.842$ & $0.240$ & $0.0223$ & $0.935$ & $-0.174$ & $-0.296$ & $1.098$ \\ \hline $4.0 - 6.0$ & $-2.063$ & $-0.1230$ & $-0.105$ & $1.0441$ & $-0.583$ & $-0.129$ & $2.394$ & $-1.921$ \\ \hline $6.0 - 8.0$ & $-1.1236$ & $0.5489$ & $-0.4824$ & $2.001$ & $-0.628$ & $0.059$ & $0.800$ & $-2.329$ \\ \hline $15.0 - 17.0$ & $ 0.1852$ & $0.128$ & $-0.560$ & $-0.230$ & $-0.573$ & $-0.572$ & $0.411$ & $0.062$ \\ \hline $17.0 - 19.0$ & $-0.859$ & $-1.215$ & $1.148$ & $0.757$ & $0.105$ & $-0.0927$ & $-0.529$ & $-0.304$ \\ \hline \end{tabular} \end{tiny} \end{frame} \end{document}