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-
-
- \usetheme{Sybila}
- \title[$\Ptau \to \Pmu \Pmu \Pmu$ approval presentation ]{$\Ptau \to \Pmu \Pmu \Pmu$ approval presentation}
-
- \author[Paul Seyfert]{
- Johannes Albrecht\inst{1}, Marta Calvi\inst{2}, \underline{Marcin Chrzaszcz\inst{3,4}}, \\Laura Gavardi\inst{1}, Jon Harrison\inst{5}, Basem Khanji\inst{2}, George Lafferty\inst{5}, Tatiana Likhomanenko\inst{6}, Eduardo Rodrigues\inst{5}, \\Nicola Serra\inst{3}, Paul Seyfert\inst{7}\\{~}\\
- \textbf{Referees}:\\ Benoit Viaud (Chair) , Matteo Rama, Frederic Machefert (EB) }
- \institute[Uni Heidelberg]{
- \inst{1}Dortmund,
- \inst{2}Milano Bicocca,
- \inst{3}Zurich, \inst{4}IFJ Cracow, \inst{5}Manchester, \inst{6}Yandex, \inst{7}Uni. Heidelberg
- }
- \date{\today}
- \begin{document}
- % --------------------------- SLIDE --------------------------------------------
- \frame[plain]{\titlepage}
- \author{Marcin Chrz\k{a}szcz}
- % ------------------------------------------------------------------------------
- % --------------------------- SLIDE --------------------------------------------
-
- \institute{~(UZH, IFJ)}
-
-
- % \begin{frame}\frametitle{Outline}
- % \begin{enumerate}
- % \item introduction\vspace{.5em}
- % \item multivariate technique\vspace{.5em}
- % \item normalisation\vspace{.5em}
- % % \item backgrounds\vspace{.5em}
- % \item expected sensitivity\vspace{.5em}
- % \item model dependence\vspace{.5em} data from Reco14Stripping20(r1)
- % \end{enumerate}
- % Major news wrt.\ the $1~fb^{-1}$ analysis are highlighted in \textcolor{mygreen}{green}
- % \end{frame}
-
- \begin{frame}\frametitle{Outline}
- \tableofcontents
- \end{frame}
-
-
-
-
- \begin{frame}
- \frametitle{Yellow pages}
- \begin{itemize}
- \item TWiki: \href{https://twiki.cern.ch/twiki/bin/viewauth/LHCbPhysics/Tau_LFV_3fb}{\url{https://twiki.cern.ch/twiki/bin/viewauth/LHCbPhysics/Tau_LFV_3fb}}
- \item ANA note: \href{https://twiki.cern.ch/twiki/pub/LHCbPhysics/Tau_LFV_3fb/v8.pdf}{LHCb-ANA-2014-005}
- \item Paper draft: \href{https://twiki.cern.ch/twiki/pub/LHCbPhysics/Tau_LFV_3fb/paper_v1.pdf}{LHCb-PAPER-2014-X}
- \item Target journal: JHEP
- \item Conference: Tau 2014
- \end{itemize}
-
- \end{frame}
-
-
-
-
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- \section{Introduction}
-
- \begin{frame}
- \frametitle{Status of $\Ptau\to\Pmu\Pmu\Pmu$}
- \begin{columns}
- \begin{column}{.62\textwidth}
-
- \includegraphics[width=.95\textwidth]{feymn.png}
-
- {{
- \begin{itemize}
- \item Charged Lepton Flavour Violation process
- \item Possible as penguin with neutrino oscillation
- \item SM prediction is beyond experimental reach~$O(10^{-40})$
-
- \end{itemize}
- }}
- \end{column}
- \begin{column}{.45\textwidth}
- \begin{alertblock}{current limits ($ 90\,\%$ CL)}
-
- \begin{description}
- \item[BaBar] $3.3\times 10^{-8}$
- \item[Belle] $2.1\times 10^{-8}$
- \item[LHCb] $8.0\times 10^{-8}$
- \end{description}
- \end{alertblock}
- \begin{alertblock}{BSM predictions}
- \begin{description}
- \item[var.\ SUSY] $10^{-10}$
- \item[non universal $\PZprime$] $10^{-8}$
- \item[mSUGRA+seesaw] $10^{-9}$
- \item[and many more...]
- \end{description}
- \end{alertblock}
- \end{column}
- \end{columns}
- \end{frame}
- %%%%%%%%%%%%%%%%%
- \begin{frame}
- \frametitle{Strategy}
- \begin{itemize}
- \item Following same approach as other RD searches.
- \item Loose stripping selection
- \item Multivariate classification in: mass, PID, ``geometry/topology''
- \item Binning optimisation.
- \item Relative normalisation ($\PDs\to\Pphi(\Pmu\Pmu)\Ppi$)
- \item Invariant mass fit for expected background in each likelihood bin: fit in $\left| m-m_{\Ptau} \right| >\unit{30}{\MeV}$
- \item ``middle sidebands'' for classifier evaluation and tests.($\unit{20}{\MeV}<\left| m-m_{\Ptau}\right| <\unit{30}{\MeV}$).
- \item CLs for limit calculation
- \end{itemize}
-
- \end{frame}
-
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- \begin{frame}
- \frametitle{$\Ptau$ production}
- \begin{itemize}
- \item Consider five production channels (fractions at $\unit{8}{\TeV}$):\begin{itemize}
- \item Prompt $\PDs\to\Ptau$ ($72.4\pm2.7\,\%$)
- \item Prompt $\PDplus\to\Ptau$ ($4.2\pm0.7\,\%$)
- \item Non-prompt $\PDs\to\Ptau$ ($8.5\pm1.7\,\%$)
- \item Non-prompt $\PDplus\to\Ptau$ ($0.17\pm0.04\,\%$)
- \item $X_{\Pbottom}\to\Ptau$ (meson or baryon) ($14.7\pm2.3\,\%$)
- \end{itemize}
- \item Use $\sigma(\Pbottom\APbottom)$ at $\unit{8}{\TeV}$ from LHCb
- \item Use Pythia scaling for $\sigma(\Pcharm\APcharm)$ at $\unit{8}{\TeV}$
- \end{itemize}
-
- \begin{columns}
- \column{0.8\textwidth}
- \begin{exampleblock}{$\mathcal{B}(\PDplus\to\Ptau)$}
- \begin{itemize}
- \item There is no measurement of $\mathcal{B}(\PDplus\to\Ptau)$
- \item One can calculate it form: $\mathcal{B}(\PDplus\to\Pmu\Pnum)$ + helicity suppression + phase space
- \item \texttt{hep-ex:0604043}
- \item $\mathcal{B}(\PDplus\to\Ptau\Pnut)=1.0\times10^{-3}$
- \end{itemize}
- \end{exampleblock}
- \column{0.2\textwidth}
- {~}
- \end{columns}
-
- \end{frame}
- \begin{frame}
- \frametitle{Datasets}
- \begin{itemize}
- \item Data from Reco14Stripping20(r1)
- \item Much MC\begin{itemize}
- \item 24M Inclusive background events ($\Pbottom\APbottom$ and $\Pcharm\APcharm$)
- \item 10M Exclusive background events ($\PDs\to\Peta(\Pmu\Pmu\Pphoton)\Pmu\Pnum$)
- \item 2M Signal events (split over 5 production channels)
- \item 12M $\PD \to \PK \Ppi \Ppi$ (missID studies)
- \item 10M $\PDstar \to \PD(\PK \Pmu \Pnum) \Ppi$ (missID studies)
-
- \end{itemize}
- \item[$\Rightarrow$] Generator level cuts for improved use of computing resources
- \begin{itemize}
- \item $\sim 14$ times more signal statistics after stripping
- \item $\sim 2$ times more background statistics
- \end{itemize}
- \item Mix $\Ptau$ production on ntuple level instead of reweighting.
- \newline$\Rightarrow$ Ease up ntuple usage (no forgotten weighting, no double weighting, \dots)
- \end{itemize}
- \end{frame}
- \section{Selection}
- \begin{frame}
- \frametitle{Stripping and selection}
- {\footnotesize{
- \begin{tabular}{|c|cc|}
- \hline
- &$\Ptau\to\Pmu\Pmu\Pmu$&$\PDs\to\Pphi\Ppi$\\
- \hline
- $\mu^\pm$ , $ \pi^\pm$ &\multicolumn{2}{c|}{} \\
- $p_T$ &\multicolumn{2}{c|}{$>300\MeV$} \\
- Track $\chi^2$/ndf &\multicolumn{2}{c|}{$<3 $} \\
- IP $\chi^2$/ndf &\multicolumn{2}{c|}{$>9 $} \\
- track ghost probability &\multicolumn{2}{c|}{$<0.3 $} \\
- \hline
- $\mu$ pairs &\multicolumn{2}{c|}{} \\
- $m_{\mu^+\mu^-} - m_{\phi}$ & $>20\MeV$ & $<20\MeV$\\
- $m_{\mu^+\mu^-}$ & $> 450\MeV$ & - \\
- $m_{\mu^+\mu^+}$ & $> 250\MeV$ & - \\
- \hline
- $\tau^\pm$ and \PDs &\multicolumn{2}{c|}{} \\
- $\Delta m$ & $<400\MeV$ & $<50\MeV$\\
- Vertex $\chi^2$ &\multicolumn{2}{c|}{$<15$} \\
- IP $\chi^2$ &\multicolumn{2}{c|}{$<225 $} \\
- $\cos\alpha$ &\multicolumn{2}{c|}{$>0.99$} \\
- $c\tau$ (stripping) &\multicolumn{2}{c|}{$>\unit{100}{\mu m}$} \\
- &\multicolumn{2}{c|}{no PV refitting}\\
- decay time (offline) &\multicolumn{2}{c|}{$> -0.01$ ns \& $< 0.025$ ns}\\
- &\multicolumn{2}{c|}{PV refitting}\\
- \hline
- \end{tabular}
- }}
-
- \end{frame}
-
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-
- \begin{frame}
- \frametitle{Triggers}
- {\footnotesize{
- \begin{tabular}{l|c|c}
- & signal & normalisation \\\hline\hline
- L0$^1$ & \multicolumn{2}{c}{L0Muon TOS}\\\hline
- Hlt1$^1$ & \multicolumn{2}{c}{Hlt1TrackMuon TOS}\\\hline
- Hlt2 2011 & Hlt2CharmSemilepD2HMuMu TOS & Hlt2DiMuonDetached$^2$ TOS \\
- & $||$ Hlt2TriMuonTau TOS & \\\hline
- Hlt2 2012 & Hlt2TriMuonTau$^1$ TOS & Hlt2DiMuonDetached$^2$ TOS\\\hline
- \end{tabular}
- }
- }
- \only<1>{
- \begin{block}{$^1$ triggers in 2012}
- \begin{itemize}
- \item Cuts changed through 2012
- \item[$\rightarrow$]emulated two different TCKs for 2012
- \item[$\rightarrow$] Found negligible differences
- \item Choice of triggers were optimised based on $\dfrac{s}{\sqrt{b}}$ FOM.
- \end{itemize}
- \end{block}}
- % \only<2>{
- % \begin{block}{$^2$ word on Hlt2DiMuonDetached}
- % \begin{itemize}
- % \item keep it simple here
- % \item line unchanged in 2012
- % \item[$\rightarrow$] choice keeps Hlt2 trigger efficiency stable
- % \item $\PDs\to\Pphi\Ppi$ anyhow doesn't behave like $\Ptau\to\Pmu\Pmu\Pmu$ in the TriMuon trigger (requires misidentification)
- % \end{itemize}
- % \end{block}}
-
- \end{frame}
-
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- \section{Multivariate technique}
-
- \begin{frame}
- \frametitle{Geometric likelihood}
- Much work has been put in improving our geometric and kinematic classifier:
- \begin{itemize}
- \item Classify the displaced 3-body decay properties of a signal candidate
- \item Revisit variable choice
- \item Revisit classification technique
- \item More toolkits tried: MatrixNet, NeuroBayes, TMVA
- \item Retune input variables\newline($\PBs\to\Pmu\Pmu$ isolation $\rightarrow$ BDT isolation: CERN-THESIS-2013-259)
- \item Blending technique.
- \end{itemize}
-
- \end{frame}
-
- \begin{frame}
- \frametitle{Basic Setup - Step I}
- \begin{itemize}
- \item Train $1/3$ signal MC against $1/2$ background MC
- \item variables \begin{itemize}
- \item DOCA
- \item Vertex $\chi^2$
- \item $\tau$ decay time
- \item $\tau$ IP$\chi^2$
- \item min.\ $\mu$ IP$\chi^2$
- \item $\Ptau$ pointing angle
- \item $\tau$ $p_T$
- \item max.\ track $\chi^2$
- \item $\PBs\to\Pmu\Pmu$ track isolation
- \item Cone isolation
- \item BDT isolation
- \end{itemize}
- \item Using these variables, train several classifiers (''Base'') \\for each of the $\Ptau$ source
- \end{itemize}
- \end{frame}
-
-
- \begin{frame}
- \frametitle{Step II}
- \begin{itemize}
- \item Train using second $1/3$ signal MC against second $1/2$ background MC.
- \item Introduce Blending technique
- \end{itemize}
- \begin{exampleblock}{Blending technique}
- \begin{itemize}
- \item For each signal channel we train: one BDT, three Fisher classifier, four MLPs, one FDA, one LD classifier and MatrixNet classifier.
- \item One final MatrixNet classifier using the 13 base variables and the base classifiers as input
-
- \end{itemize}
- \end{exampleblock}
- \begin{itemize}
- \item All evaluation is done on $3rd$ $1/3$ signal sample and middle side-bands.
- \item Splitting into independent samples makes the procedure insensitive to
- overtraining.
- \end{itemize}
-
-
- \end{frame}
-
-
-
- \begin{frame}
- \frametitle{Performance of Blend classifier}
- \begin{itemize}
- \item Classifier prefers $\Ptau$ from prompt $\PDs$
- \end{itemize}
- \begin{columns}
- \begin{column}{.48\textwidth}
- \begin{exampleblock}{MC response for different\newline $\Ptau$ production channels}
- \includegraphics[width=.95\textwidth]{./mn_sig.png}
- \end{exampleblock}
- \end{column}
- \begin{column}{.48\textwidth}
- \begin{exampleblock}{response for $\PDs\to\Pphi\Ppi$\newline data and MC}
- \includegraphics[width=.95\textwidth]{./MN_BLEND_FLAT.png}
- \end{exampleblock}
- \end{column}
- \end{columns}
- \end{frame}
-
- \begin{frame}
- \frametitle{Calibration}
- \begin{itemize}
- \item Assume all differences between $\Ptau\to\Pmu\Pmu\Pmu$ and $\PDs\to\Pphi\Ppi$ come from kinematics (mass, resonance, decay time)
- \item Get correction $\PDs\leadsto\Ptau$ from MC
- \item Apply corrections to $\PDs\to\Pphi\Ppi$ on data
- \end{itemize}
- \begin{block}{validation}
- \begin{itemize}
- \item done for 2011 analysis, treating smeared MC as data
- \end{itemize}
- \end{block}
- \begin{columns}
- \begin{column}{.45\textwidth}
- \begin{itemize}
- \item $\PDs\to\Pphi\Ppi$ well modelled in MC
- % \item[$\rightarrow$] i.e.\ also badly pointing non-prompt $\PDs$
- \end{itemize}
- \end{column}
- \begin{column}{.45\textwidth}
- \includegraphics[width=.95\textwidth]{MN_BLEND_FLAT.png}
- \end{column}
- \end{columns}
- \end{frame}
-
- \begin{frame}
- \frametitle{PID}
- \begin{itemize}
- \item We used ProbNNmu already in the previous round of the analysis
- \item Now use MC12TuneV2 (latest)
- \item Two-fold reason:\begin{itemize}
- \item Expect better performance than CombDLL variables
- \item ``one variable for everything'':\newline with CombDLL we needed both CombDLL($\mu-\pi$) and CombDLL($\mu-K$)
- \end{itemize}
- \end{itemize}
- \end{frame}
-
- \begin{frame}
- \frametitle{PID calibration }
- \begin{itemize}
- \item Since PIDCalib tool didn't work for us, we choose a phenomenological approach.
- \item Many thanks to Barbara Sciascia for help understanding this problem.
- \end{itemize}
- \begin{exampleblock}{phenomenologic treatment}
- \begin{itemize}
- \item correlations are small in $\PDs\to\Pphi\Ppi$ data and MC
- \newline $\varepsilon(\text{cut on one muon})^2 = \varepsilon(\text{cut on two muons})$
- \item[$\Rightarrow$] use $c^3=(\varepsilon(\text{cut and fit})/\varepsilon(\text{PIDCalib}))^3$ as correction to PIDCalib for $\Ptau\to\Pmu\Pmu\Pmu$
- \item assign error of $0.02$ for $c$
- \end{itemize}
- \end{exampleblock}
- \begin{itemize}
- \item Many x-checks done.
- \item Everything works fine.
- \end{itemize}
-
- \end{frame}
-
-
-
- \begin{frame}
- \frametitle{Binning optimisation}
- \begin{itemize}
- \item How to optimise the binning in two classifiers?
- \item $\unit{1}{\reciprocal\femtobarn}$ CONF note: two one-dimensional optimisations as in $\PBs\to\Pmu\Pmu$
- \item $\unit{1}{\reciprocal\femtobarn}$ PAPER: iterative loop of one-dimensional optimisations\newline optimising one classifier on the sensitive range of the other classifier
- \item Now: optimise two-dimensions (optimise bin boundaries in both dimensions at the same time)
- \item Unchanged: don't use lowest likelihood bins\newline(reflection backgrounds, no sensitivity gain)
- \end{itemize}
- \end{frame}
- \begin{frame}
- \frametitle{Impact of new binning optimisation}
- \begin{itemize}
- \item Removal of tiny bins which contribute negligible sensitivity
- \item Colour: limit obtained, using only this particular bin
- \item Number: rank of that bin (1=best sensitivity bin)
- \end{itemize}
-
- ~
-
- \begin{columns}
- \begin{column}{.5\textwidth}
- old analysis
-
- ~
-
- \includegraphics[width=.95\textwidth]{./90CLonebinlimit.pdf}
- \end{column}
- \begin{column}{.5\textwidth}
- new analysis
-
- (2011 data)
- \includegraphics[width=.95\textwidth]{./rank.pdf}
- \end{column}
- \end{columns}
- \end{frame}
-
- \begin{frame}
- \frametitle{Mass shape}
- \begin{itemize}
- \item Double-Gaussian with fixed fraction ($70\,\%$ inner Gaussian)
- \item Fix fraction to ease calibration:\newline
- $\sigma_{data}^{\Ptau} = \frac{\sigma_{MC}^{\Ptau}}{\sigma_{MC}^{\PDs}}\times\sigma_{data}^{\PDs}$
- \end{itemize}
- \includegraphics[width=.44\textwidth]{./Ds_data_2011.pdf}
- \includegraphics[width=.44\textwidth]{./Ds_data_2012.pdf}
-
- {\footnotesize{
- \begin{tabular}{|c|c|c|}
- \hline
- Calibrated $\Ptau$ Mass shape & 7~TeV & 8~TeV\\
- \hline
- Mean ($\MeV$) & $1779.1 \pm 0.1$ & $1779.0 \pm 0.1$\\
- \hline
- $\sigma_1$ ($\MeV$) & $7.7 \pm 0.1$ & $7.6 \pm 0.1$\\
- \hline
- $\sigma_2$ ($\MeV$) & $12.0 \pm 0.8$ & $11.5 \pm 0.5$\\
- \hline
- \end{tabular}
- }
- }
- \end{frame}
-
-
-
- \section{Normalisation}
-
- \begin{frame}
- \frametitle{Relative normalisation}
- $\mathcal{B}(\Ptau\to\Pmu\Pmu\Pmu) = \frac{\mathcal{B}(\PDs\to\Pphi\Ppi)}{\mathcal{B}(\PDs\to\Ptau\Pnut)} \times f_{\PDs}^{\Ptau} \times \frac{\varepsilon_\text{norm} }{\varepsilon_\text{sig} } \times \frac{N_\text{sig}}{N_\text{norm}} = \alpha\times N_\text{sig}$
- \begin{itemize}
- \item where $\varepsilon$ stands for trigger, reconstruction, selection
- \item $\text{norm}$ = normalisation channel $\PDs\to\Pphi\Ppi$
- \item $f_{\PDs}^{\Ptau}$ is the fraction of $\Ptau$ coming from $\PDs$
- \newline i.e.\ $(83\pm3)\,\%$ for 2012
- \end{itemize}
- \includegraphics[width=.47\textwidth]{./Ds_data_2011.pdf}
- \includegraphics[width=.47\textwidth]{./Ds_data_2012.pdf}
- \end{frame}
-
- \begin{frame}[allowframebreaks]
- \frametitle{Normalisation in numbers}
- {\footnotesize{
- $\begin{array}{c|c|c}
- & \rm{7~TeV} & \rm{8~TeV}\\
- \hline
- \rm{\epsilon\mathstrut_{sig}}^{GEN} (\%) & 8.989 \pm 0.40 & 9.21 \pm 0.35\\
- \hline
- \rm{\epsilon_{cal}}^{GEN} (\%) & 11.19 \pm 0.34 & 11.53 \pm 0.32\\
- \hline
- \rm{\epsilon_{sig}}^{REC,isMuon,SEL} (\%) & 9.927 \pm 0.028 & 9.261 \pm 0.023 \\
- \hline
- \rm{\epsilon_{cal}}^{REC,isMuon,SEL} (\%) & 7.187 \pm 0.022 & 6.690 \pm 0.022 \\
- \hline
- \frac{\rm{c_{cal}}^{track}}{\rm{c_{sig}}^{track}} & 0.997 \pm 0.009 \pm 0.026 & 0.996 \pm 0.009 \pm 0.026 \\
- \hline
- \frac{\rm{c_{cal}}^{\mu ID}}{\rm{c_{sig}}^{\mu ID}} & 0.9731 \pm 0.0031 \pm 0.0264 & 1.0071 \pm 0.0022 \pm 0.0204 \\
- \hline
- \rm{c}^{\phi} & \multicolumn{2}{c}{0.98 \pm 0.01} \\
- \hline
- \rm{c}^{\tau} & 1.032 \pm 0.006 & 1.026 \pm 0.006\\
- \hline
- \rm{c}^{trash} & 1.89 \pm 0.12 & 1.96 \pm 0.12\\
- \hline
- \rm{\epsilon\mathstrut_{sig}}^{TRIG} (\%) & 35.52 \pm 0.14 \pm 0.14 & 39.3 \pm 1.7 \pm 2.0 \\
- \hline
- \rm{\epsilon\mathstrut_{cal}}^{TRIG} (\%) & 23.42 \pm 0.14 \pm 0.09 & 20.62 \pm 0.76 \pm 1.07 \\
- \end{array}$
- }}
-
- \framebreak
-
- {\footnotesize{
- $\begin{array}{c|c|c}
- & \rm{7~TeV} & \rm{8~TeV}\\
- \hline
- \mathcal{B}(PDs \to \Pphi \Ppi) & \multicolumn{2}{c}{(1.317 \pm 0.099) \times 10^{-5}}\\
- \hline
- f^{\tau}_{D_{s}} & 0.78 \pm 0.04 & 0.80 \pm 0.03 \\
- \hline
- \mathcal{B} (\PDs \to \Ptau \Pnut) & \multicolumn{2}{c}{0.0561 \pm 0.0024}\\
- \hline
- \rm{\epsilon\mathstrut_{cal}}^{REC\&SEL}/
- \rm{\epsilon\mathstrut_{sig}}^{REC\&SEL}
- & 0.898 \pm 0.060 & 0.912 \pm 0.054 \\
- \hline
- \rm{\epsilon\mathstrut_{cal}}^{TRIG}/
- \rm{\epsilon\mathstrut_{sig}}^{TRIG}
- & 0.6593 \pm 0.0058 & 0.525 \pm 0.040\\
- \hline
- N_{cal} & 28,207 \pm 440 & 52,131 \pm 695\\
- \hline & \\[-0.8em]\hline
- \alpha & (3.81 \pm 0.46) \times 10^{-9} & (1.72 \pm 0.23) \times 10^{-9}\\
- \alpha^{trash} & (7.20 \pm 0.98) \times 10^{-9} & (3.37 \pm 0.50) \times 10^{-9}\\
- \end{array}$
- }}
- \end{frame}
-
-
- \section{Backgrounds}
-
- \begin{frame}
- \frametitle{Misidentification}
- \begin{itemize}
- \item Most dominant: $\PDplus\to\PK\Ppi\Ppi$
- \item Experience from last round: cut away low ProbNNmu range
- \item Check remaining data under $\PK\Ppi\Ppi$ hypothesis for $\PDplus$ peak
- \item[$\Rightarrow$] misid safely contained in ``trash'' bin
- \item $\PDplus\to\Ppi\Ppi\Ppi$ and $\PDs\to\Ppi\Ppi\Ppi$ start to become visible in 2012
- \end{itemize}
- \includegraphics[width=.45\textwidth]{./Dp2Kpipi_all_2012_senseBins.pdf}
- \includegraphics[width=.45\textwidth]{./FittoD23pi_2012.pdf}
- \end{frame}
-
- \begin{frame}
- \frametitle{Evil backgrounds}
- \begin{itemize}
- \item $\Pphi\to\Pmu\Pmu + X$: narrow veto on dimuon mass
- \item $\PDs\to\Peta(\Pmu\Pmu\Pphoton)\Pmu\Pnum$: not so easy
- \begin{itemize}
- \item Modelled in CONF note
- \item Optimised veto in PAPER
- \item Right now: both versions in the ANA note
- \end{itemize}
- \item Baseline: veto $m_{\APmuon\Pmuon} < \unit{450}{\MeV}$
- \begin{itemize}
- \item Fits better understood
- \item Sensitivity unchanged when removing veto
- \item Smaller uncertainty on expected background
- \end{itemize}
- \end{itemize}
- \end{frame}
-
- \begin{frame}
- \frametitle{Remaining backgrounds}
- \begin{itemize}
- \item Fit exponential to invariant mass spectrum in each likelihood bin
- \item Don't use $\pm \unit{30}{\MeV}$ in the fit
- \item[$\rightarrow$] Compatible results blinding only $\pm \unit{20}{\MeV}$\footnote{partially used in classifier developement}
- \end{itemize}
- {\begin{center}
- Example of most sensitive regions in 2011 and 2012
- \includegraphics[width=0.9\textwidth]{./fits.png}
-
- \end{center}}
- \end{frame}
-
- \section{Expected limit}
-
- \begin{frame}
- \frametitle{expected limit}
- \begin{itemize}
- \item Consider nuisance parameters from background fit, signal pdf calibration, normalisation
- \item Nuisance parameters due to $\Ptau$ production, normalization.
- \item Limit for combined 2011+2012 analysis
- \end{itemize}
- \end{frame}
-
- \begin{frame}
- \frametitle{Sensitivity}
- $\mathcal{B}(\Ptau\to\Pmu\Pmu\Pmu)<5.0 \times 10^{-8}$ at 90\% CL
-
- \includegraphics[width=.8\textwidth]{./banana.png}
- \end{frame}
-
-
-
- \section{Model dependence}
-
- \begin{frame}
- \frametitle{Model dependence}
- \begin{itemize}
- \item $\Peta$ veto $\Rightarrow$ our limit not applicable to New Physics with small $m_{\APmuon\Pmuon}$
- \item Model description in \texttt{arXiv:0707.0988}
- \item 5 relevant Dalitz distributions: 2 four-point operators, 1 radiative operator, 2 interference terms
- \end{itemize}
- \only<2->{
- \begin{itemize}
- \item With radiative distribution limit gets worse by $51\,\%$ (dominantly from the $\Peta$ veto)
- \item The other four Dalitz distributions behave nicely (within $7\,\%$)
- \end{itemize}
- }
- \only<1>{
- \includegraphics[width=.331\textwidth]{./gammallll.pdf}
- \includegraphics[width=.331\textwidth]{./gammallrr.pdf}
- \includegraphics[width=.331\textwidth]{./gammarad.pdf}
-
- \includegraphics[width=.331\textwidth]{./gammarad-llll.pdf}
- \includegraphics[width=.331\textwidth]{./gammarad-llrr.pdf}
- }
-
- \end{frame}
-
-
- % \begin{frame}
- % \frametitle{Conclusion}
- % \begin{columns}
- % \begin{column}{.55\textwidth}
- % \begin{itemize}
- % \item finally all pieces put together
- % \item model (in)dependence of $\Peta$ veto investigated
- % \item expected sensitivity computed\newline $5.6\times 10^{-8}$
- % \end{itemize}
- % \end{column}
- % \begin{column}{.45\textwidth}
- % \includegraphics[width=\textwidth]{party-music-hd-wallpaper-1920x1200-3850.jpg}
- % \end{column}
- % \end{columns}
-
- % \end{frame}
-
-
- \section{Unblinded results}
-
- \begin{frame}
- \frametitle{Unblinding 1}
- \begin{columns}
- \column{1in}{~}
- \column{3in}
- ''
- THERE came a day at summer’s full \\
- Entirely for us \\
- I thought that such were for the saints, \\
- Where revelations be. ''\footnote{E.Dickinson} \\
- \column{1in}{~}
- \end{columns}
- {~}\\
- {~}\\
- \begin{Large}
- On Monday $4^{th}$ of August we were given the permission to unblind.
- \end{Large}
-
-
- \end{frame}
-
-
-
- \begin{frame}
- \frametitle{Unblinding 2}
- \begin{itemize}
- \item Unfortunately no big ''revelations'' were there:
- \item 2011 numbers:
- \end{itemize}
- \includegraphics[width=1.\textwidth]{2011.png}
-
- \end{frame}
-
- \begin{frame}
- \frametitle{Unblinding 3}
- \begin{itemize}
- \item Unfortunately no big ''revelations'' were also in 2012 data:
-
- \end{itemize}
- \includegraphics[width=1.1\textwidth]{2012.png}
-
- \end{frame}
-
-
-
- \begin{frame}
- \frametitle{Unblinding 4}
-
- \begin{center}
- \includegraphics[width=0.7\textwidth]{banana_line.pdf}
- \end{center}
- \begin{columns}
-
- \column{0.2in}{~}
- \column{2in}
- Limits(PHSP):\\
- Observed(Expected)\\
- $4.6~(5.0)\times 10^{-8}$ at $90\%$ CL\\
- $5.6~(6.1)\times 10^{-8}$ at $95\%$ CL\\
-
- \column{3in}
- \includegraphics[width=0.5\textwidth]{model.png}
- \end{columns}
- \end{frame}
-
- \begin{frame}
- \frametitle{Conclusions}
- \begin{columns}
- \column{2.5in}
- \begin{itemize}
- \item We didn't find NP (yet).
- \item Limits set with full LHCb dataset.
- \item Awaiting for the future data!
- \end{itemize}
- \column{2.5in}
-
- \includegraphics[width=1\textwidth]{TauLFV_UL_2013001.pdf}
-
-
-
- \end{columns}
- \begin{itemize}
- \item We would like to thank our referees for very friendly,thorough and fruitful review.
- \item With this presentation we ask collaboration for approval.
- \end{itemize}
-
-
- \end{frame}
-
-
-
- \end{document}