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- \newcommand{\pb}{\si{\pico\barn}}%
- \newcommand{\fb}{\si{\femto\barn}}%
- \newcommand{\invfb}{\si{\per\femto\barn}}
- \newcommand{\GeV}{\si{\giga\electronvolt}}
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- \begin{document}
- \title[$e$ Seeding Validation]{Offline Electron Seeding Validation \-- Update}
- \author[C. Fangmeier]{\textbf{Caleb Fangmeier} \\ Ilya Kravchenko, Greg Snow}
- \institute[UNL]{University of Nebraska \-- Lincoln}
- \date{EGamma Reco/Comm/HLT Meeting | February 16, 2018}
- \titlegraphic{%
- \begin{figure}
- \includegraphics[width=1in]{CMSlogo.png}\hspace{0.75in}\includegraphics[width=1in]{nebraska-n.png}
- \end{figure}
- }
- \begin{frame}[plain]
- \titlepage%
- \end{frame}
- \begin{frame}{Introduction}
- \begin{itemize}
- \item Our goal is to study \textbf{seeding} for the \textbf{offline} GSF tracking with the \textbf{new pixel detector}.
- \item Specifically, we want to optimize the new pixel-matching scheme from HLT for use in off-line reconstruction.
- \item This Talk:
- \begin{itemize}
- \item Show the effect of linearly scaling matching windows up and down
- \item Show first set of \textbf{optimized} windows
- \item Next steps
- \end{itemize}
- \item Full set of results is available here \url{https://eg.fangmeier.tech/seeding\_studies\_2018\_02\_15\_18/output/}
- \end{itemize}
- \end{frame}
- \begin{frame}{$\delta \phi$ Residuals}
- \begin{columns}
- \begin{column}{0.35\textwidth}
- {\small
- \begin{itemize}
- \item Distribution of $\delta \phi$ residuals for first matched hits in truth-matched seeds where the hit was in BPIX-L1
- \item Truth-matching requires sufficient (75\%) matched hits with a
- sim-track as well as less than 10\% energy discrepancy between
- super-cluster and sim-track.
- \item Differential in $E_T$ of the matched super-cluster
- \item Red line shows the default (aka HLT) window.
- \item Contour lines are biased by the matching cut necessarily being
- applied before deriving the contours.
- \end{itemize}
- }
- \end{column}
- \begin{column}{0.7\textwidth}
- \begin{figure}
- \includegraphics[width=\textwidth]{figures/dphi_B1_H1.png}
- \end{figure}
- \end{column}
- \end{columns}
- \vspace{-0.3in}
- \begin{center}
- Cut windows are specified as functions of $E_T$ for $\delta \phi$, and $\delta R/z$ for the first, second, and third matched hits.
- \end{center}
- \end{frame}
- \begin{frame}{Linear Scaling of Windows}
- \begin{columns}
- \begin{column}{0.32\textwidth}
- \begin{itemize}
- \item Modified windows with uniform scaling
- \begin{itemize}
- \item x0.5(\texttt{extra-narrow})
- \item x1.0(\texttt{narrow})
- \item x2.0(\texttt{wide})
- \item x3.0(\texttt{extra-wide})
- \end{itemize}
- \item Uniform scaling draws out a clear curve in Efficiency V. Purity.
- \item But can we do better? Find windows with points above the curve?
- \end{itemize}
- \end{column}
- \begin{column}{0.7\textwidth}
- \begin{figure}
- \includegraphics[width=\textwidth]{figures/linear_scaling_tracking_roc.png}
- \end{figure}
- \end{column}
- \end{columns}
- \end{frame}
- \begin{frame}{Finding more optimal windows (Ex. 1)}
- \begin{columns}
- \begin{column}{0.32\textwidth}
- \begin{itemize}
- \item Figure: first-hit $\delta \phi$ 99\% contours for all relevant\footnotemark pixel regions.
- \item Procedure: Select a cut that tends to reasonably follow the 99\% contours in the \texttt{extra-wide} windows.
- \item Repeat this for each of the five windows.
- \item In this case, the \texttt{narrow} window seemed appropriate so this particular window was unchanged.
- \end{itemize}
- \end{column}
- \begin{column}{0.7\textwidth}
- \begin{figure}
- \includegraphics[width=\textwidth]{figures/dphi_hit1.png}
- \end{figure}
- \end{column}
- \end{columns}
- \footnotetext[1]{meaning the sub-detectors that have a substantial portion of first hits}
- \end{frame}
- \begin{frame}{Finding more optimal windows (Ex. 2)}
- \begin{columns}
- \begin{column}{0.32\textwidth}
- \begin{itemize}
- \item Figure: second-hit $\delta \phi$ 99\% contours for all relevant pixel regions.
- \item Quite low statistics in some regions + looking at tails of distribution results in high variability
- \item Despite this, estimate an appropriate cut to be 0.005
- \end{itemize}
- \end{column}
- \begin{column}{0.7\textwidth}
- \begin{figure}
- \includegraphics[width=\textwidth]{figures/dphi_hit2.png}
- \end{figure}
- \end{column}
- \end{columns}
- \end{frame}
- \begin{frame}{Proposed New Working Point Performance}
- \begin{columns}
- \begin{column}{0.32\textwidth}
- \begin{itemize}
- \item New Working Point lies basically on the linear-scaling curve
- \item However, NWP with extra-narrow first $\delta \phi$ window sets slightly above the curve
- \item Hints that better performance is achievable, but it's not obvious how to achieve
- \item Many ways to vary parameters...
- \end{itemize}
- \end{column}
- \begin{column}{0.7\textwidth}
- \begin{figure}
- \includegraphics[width=\textwidth]{figures/linear_scaling_tracking_roc_w_nwp.png}
- \end{figure}
- \end{column}
- \end{columns}
- \end{frame}
- \begin{frame}{Outlook}
- \begin{itemize}
- \item Next steps
- \begin{itemize}
- \item Testing with an complementary dataset (currently looking at $Z\rightarrow ee$ only)
- \item Possibly breaking down windows sizes in $\eta$ (code supports this, but is currently unused).
- \end{itemize}
- \item Other Thoughts
- \begin{itemize}
- \item What is an appropriate working point, and what performance can be deemed adequate?
- \item Are there different figures-of-merit that must be balanced (CPU performance, specific background rejections.)?
- \end{itemize}
- \end{itemize}
- \vspace{1.5in}
- \end{frame}
- \appendix
- \backupbegin
- \begin{frame}
- \begin{center}
- {\Huge BACKUP}
- \end{center}
- \end{frame}
- \begin{frame}
- \begin{itemize}
- \item \textbf{Sim-Track \--} A track from a simulated electron originating from the luminous region of CMS (beam-spot +- 5$\sigma$)
- \item \textbf{ECAL-Driven Seed \--} A seed created via a matching procedure between Super-Clusters and General Tracking Seeds (Either from \texttt{ElectronSeedProducer} or \texttt{ElectronNHitSeedProducer})
- \item \textbf{GSF Track \--} A track from GSF-Tracking resulting from an \textbf{ECAL-Driven Seed}
- \item \textbf{Seeding Efficiency \--} The fraction of \textbf{Sim-Tracks} that have a matching \textbf{ECAL-Driven Seed} (based on simhit-rechit linkage)
- \item \textbf{GSF Tracking Efficiency \--} The fraction of \textbf{Sim-Tracks} that have a matching \textbf{GSF Track} (again, based on simhit-rechit linkage)
- \item \textbf{ECAL-Driven Seed Purity \--} The fraction of \textbf{ECAL-Driven Seeds} that have a matching \textbf{Sim-Track}
- \item \textbf{GSF Tracking Purity \--} The fraction of \textbf{GSF Tracks} that have a matching \textbf{Sim-Track}
- \end{itemize}
- \end{frame}
- \begin{frame}{Triplet Electron Seeding \-- Setup}
- \begin{columns}
- \begin{column}{0.45\textwidth}
- \begin{itemize}
- \item Begin with ECAL super cluster and beam spot
- \end{itemize}
- \end{column}
- \begin{column}{0.55\textwidth}
- \begin{figure}
- \includegraphics[width=\textwidth]{diagrams/seeding_base.png}
- \end{figure}
- \end{column}
- \end{columns}
- \end{frame}
- \begin{frame}{Triplet Electron Seeding - Introduce Seed}
- \begin{columns}
- \begin{column}{0.45\textwidth}
- \begin{itemize}
- \item Now, examine, one-by-one seeds from general tracking*
- \item Note that we do not look at all hits in an event, but rather rely on general tracking to identify seeds.
- \end{itemize}
- \vspace{0.1in}
- \midrule
- \vspace{0.1in}
- {\footnotesize *initialStepSeeds, highPtTripletStepSeeds, mixedTripletStepSeeds, pixelLessStepSeeds, tripletElectronSeeds, pixelPairElectronSeeds, stripPairElectronSeeds}
- \end{column}
- \begin{column}{0.55\textwidth}
- \begin{figure}
- \includegraphics[width=\textwidth]{diagrams/seeding_step1.png}
- \end{figure}
- \end{column}
- \end{columns}
- \end{frame}
- \begin{frame}{Triplet Electron Seeding - Match First Hit}
- \begin{columns}
- \begin{column}{0.5\textwidth}
- \begin{itemize}
- \item Using the beam spot, the SC position, and SC energy, propagate a path through the pixels.
- \item Next, require the first hit to be within a $\delta\phi$ and $\delta z$ window. ($\delta\phi$ and $\delta R$ for FPIX)
- \item $\delta z$ window for first hit is huge as SC and beam spot positions give very little information about $z$.
- \end{itemize}
- \end{column}
- \begin{column}{0.5\textwidth}
- \begin{figure}
- \includegraphics[width=\textwidth]{diagrams/seeding_step2.png}
- \end{figure}
- \end{column}
- \end{columns}
- \end{frame}
- \begin{frame}{Triplet Electron Seeding - Extrapolate Vertex}
- \begin{columns}
- \begin{column}{0.45\textwidth}
- \begin{itemize}
- \item Once we have a matched hit, use it with the SC position, to find the vertex z.
- \item Vertex x and y are still the beam spot's.
- \item Just a simple linear extrapolation.
- \end{itemize}
- \end{column}
- \begin{column}{0.55\textwidth}
- \begin{figure}
- \includegraphics[width=\textwidth]{diagrams/vertex_z.png}
- \end{figure}
- \end{column}
- \end{columns}
- \end{frame}
- \begin{frame}{Triplet Electron Seeding - Match Other Hits}
- \begin{columns}
- \begin{column}{0.45\textwidth}
- \begin{itemize}
- \item Now forget the SC position, and propagate a new track based on the vertex and first hit positions, and the SC energy.
- \item Progress one-by-one through the remaining hits in the seed and require each one fit within a specified window around the track.
- \item Quit when all hits are matched, or a hit falls outside the window. No skipping is allowed.
- \item However, \emph{layer} skipping is not ruled out if the original seed is missing a hit in a layer
- \end{itemize}
- \end{column}
- \begin{column}{0.55\textwidth}
- \begin{figure}
- \includegraphics[width=\textwidth]{diagrams/seeding_step3.png}
- \end{figure}
- \end{column}
- \end{columns}
- \end{frame}
- \begin{frame}{Triplet Electron Seeding - Window Sizes}
- \begin{columns}
- \begin{column}{0.55\textwidth}
- \begin{itemize}
- \item The $\delta\phi$ and $\delta R/z$ windows for each hit are defined using three parameters.
- \begin{itemize}
- \item \texttt{highEt}
- \item \texttt{highEtThreshold}
- \item \texttt{lowEtGradient}
- \end{itemize}
- \item From these, the window size is calculated as \\
- $\texttt{highEt} + \min(0,\texttt{Et}-\texttt{highEtThreshold})*\texttt{lowEtGradient}$.
- \item For the first hit, these parameters for the $\delta \phi$ window are,
- \begin{itemize}
- \item $\texttt{highEt}=0.05$
- \item $\texttt{highEtThreshold}=20$
- \item $\texttt{lowEtGradient}=-0.002$
- \end{itemize}
- \end{itemize}
- \end{column}
- \begin{column}{0.45\textwidth}
- \begin{figure}
- \includegraphics[width=\textwidth]{figures/dphi1_max.png}
- \end{figure}
- \end{column}
- \end{columns}
- \vspace{0.1in} \hrule \vspace{0.1in}
- These parameters can be specified for each successive hit, and in bins of $\eta$, so optimization is a challenge!
- \end{frame}
- \begin{frame}{Triplet Electron Seeding - Handle Missing Hits}
- \begin{columns}
- \begin{column}{0.45\textwidth}
- \begin{itemize}
- \item Finally, calculate the expected number of hits based on the number of working pixel modules the track passes through.
- \item Require exact$^1$ number of matched hits depending on the expected number of hits.
- \begin{itemize}
- \item If $N_{\textrm{exp}}=4$, require $N_{\textrm{match}}=3$
- \item If $N_{\textrm{exp}}<4$, require $N_{\textrm{match}}=2$
- \end{itemize}
- \item If the seed passes all requirements, all information, including
- \begin{itemize}
- \item Super cluster
- \item Original Seed
- \item Residuals (For both charge hypotheses)
- \end{itemize}
- are wrapped up and sent downstream to GSF tracking
- \end{itemize}
- \end{column}
- \begin{column}{0.55\textwidth}
- \begin{figure}
- \includegraphics[width=\textwidth]{diagrams/seeding_step4.png}
- \end{figure}
- \end{column}
- \end{columns}
- \vspace{0.1in} \hrule \vspace{0.1in}
- {\footnotesize $^1$Exact, rather than minimum to deal with duplicate seeds in input collection. Could switch to minimum with offline cross-cleaned seeds.}
- \end{frame}
- \backupend
- \end{document}
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