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  24. \begin{document}
  25. \title[$e$ Seeding Validation]{Offline Electron Seeding Validation \-- Update}
  26. \author[C. Fangmeier]{\textbf{Caleb Fangmeier} \\ Ilya Kravchenko, Greg Snow}
  27. \institute[UNL]{University of Nebraska \-- Lincoln}
  28. \date{EGamma Reco/Comm/HLT Meeting | February 16, 2018}
  29. \titlegraphic{%
  30. \begin{figure}
  31. \includegraphics[width=1in]{CMSlogo.png}\hspace{0.75in}\includegraphics[width=1in]{nebraska-n.png}
  32. \end{figure}
  33. }
  34. \begin{frame}[plain]
  35. \titlepage%
  36. \end{frame}
  37. \begin{frame}{Introduction}
  38. \begin{itemize}
  39. \item Our goal is to study \textbf{seeding} for the \textbf{offline} GSF tracking with the \textbf{new pixel detector}.
  40. \item Specifically, we want to optimize the new pixel-matching scheme from HLT for use in off-line reconstruction.
  41. \item This Talk:
  42. \begin{itemize}
  43. \item Show the effect of linearly scaling matching windows up and down
  44. \item Show first set of \textbf{optimized} windows
  45. \item Next steps
  46. \end{itemize}
  47. \item Full set of results is available here \url{https://eg.fangmeier.tech/seeding\_studies\_2018\_02\_15\_18/output/}
  48. \end{itemize}
  49. \end{frame}
  50. \begin{frame}{$\delta \phi$ Residuals}
  51. \begin{columns}
  52. \begin{column}{0.35\textwidth}
  53. {\small
  54. \begin{itemize}
  55. \item Distribution of $\delta \phi$ residuals for first matched hits in truth-matched seeds where the hit was in BPIX-L1
  56. \item Truth-matching requires sufficient (75\%) matched hits with a
  57. sim-track as well as less than 10\% energy discrepancy between
  58. super-cluster and sim-track.
  59. \item Differential in $E_T$ of the matched super-cluster
  60. \item Red line shows the default (aka HLT) window.
  61. \item Contour lines are biased by the matching cut necessarily being
  62. applied before deriving the contours.
  63. \end{itemize}
  64. }
  65. \end{column}
  66. \begin{column}{0.7\textwidth}
  67. \begin{figure}
  68. \includegraphics[width=\textwidth]{figures/dphi_B1_H1.png}
  69. \end{figure}
  70. \end{column}
  71. \end{columns}
  72. \vspace{-0.3in}
  73. \begin{center}
  74. Cut windows are specified as functions of $E_T$ for $\delta \phi$, and $\delta R/z$ for the first, second, and third matched hits.
  75. \end{center}
  76. \end{frame}
  77. \begin{frame}{Linear Scaling of Windows}
  78. \begin{columns}
  79. \begin{column}{0.32\textwidth}
  80. \begin{itemize}
  81. \item Modified windows with uniform scaling
  82. \begin{itemize}
  83. \item x0.5(\texttt{extra-narrow})
  84. \item x1.0(\texttt{narrow})
  85. \item x2.0(\texttt{wide})
  86. \item x3.0(\texttt{extra-wide})
  87. \end{itemize}
  88. \item Uniform scaling draws out a clear curve in Efficiency V. Purity.
  89. \item But can we do better? Find windows with points above the curve?
  90. \end{itemize}
  91. \end{column}
  92. \begin{column}{0.7\textwidth}
  93. \begin{figure}
  94. \includegraphics[width=\textwidth]{figures/linear_scaling_tracking_roc.png}
  95. \end{figure}
  96. \end{column}
  97. \end{columns}
  98. \end{frame}
  99. \begin{frame}{Finding more optimal windows (Ex. 1)}
  100. \begin{columns}
  101. \begin{column}{0.32\textwidth}
  102. \begin{itemize}
  103. \item Figure: first-hit $\delta \phi$ 99\% contours for all relevant\footnotemark pixel regions.
  104. \item Procedure: Select a cut that tends to reasonably follow the 99\% contours in the \texttt{extra-wide} windows.
  105. \item Repeat this for each of the five windows.
  106. \item In this case, the \texttt{narrow} window seemed appropriate so this particular window was unchanged.
  107. \end{itemize}
  108. \end{column}
  109. \begin{column}{0.7\textwidth}
  110. \begin{figure}
  111. \includegraphics[width=\textwidth]{figures/dphi_hit1.png}
  112. \end{figure}
  113. \end{column}
  114. \end{columns}
  115. \footnotetext[1]{meaning the sub-detectors that have a substantial portion of first hits}
  116. \end{frame}
  117. \begin{frame}{Finding more optimal windows (Ex. 2)}
  118. \begin{columns}
  119. \begin{column}{0.32\textwidth}
  120. \begin{itemize}
  121. \item Figure: second-hit $\delta \phi$ 99\% contours for all relevant pixel regions.
  122. \item Quite low statistics in some regions + looking at tails of distribution results in high variability
  123. \item Despite this, estimate an appropriate cut to be 0.005
  124. \end{itemize}
  125. \end{column}
  126. \begin{column}{0.7\textwidth}
  127. \begin{figure}
  128. \includegraphics[width=\textwidth]{figures/dphi_hit2.png}
  129. \end{figure}
  130. \end{column}
  131. \end{columns}
  132. \end{frame}
  133. \begin{frame}{Proposed New Working Point Performance}
  134. \begin{columns}
  135. \begin{column}{0.32\textwidth}
  136. \begin{itemize}
  137. \item New Working Point lies basically on the linear-scaling curve
  138. \item However, NWP with extra-narrow first $\delta \phi$ window sets slightly above the curve
  139. \item Hints that better performance is achievable, but it's not obvious how to achieve
  140. \item Many ways to vary parameters...
  141. \end{itemize}
  142. \end{column}
  143. \begin{column}{0.7\textwidth}
  144. \begin{figure}
  145. \includegraphics[width=\textwidth]{figures/linear_scaling_tracking_roc_w_nwp.png}
  146. \end{figure}
  147. \end{column}
  148. \end{columns}
  149. \end{frame}
  150. \begin{frame}{Outlook}
  151. \begin{itemize}
  152. \item Next steps
  153. \begin{itemize}
  154. \item Testing with an complementary dataset (currently looking at $Z\rightarrow ee$ only)
  155. \item Possibly breaking down windows sizes in $\eta$ (code supports this, but is currently unused).
  156. \end{itemize}
  157. \item Other Thoughts
  158. \begin{itemize}
  159. \item What is an appropriate working point, and what performance can be deemed adequate?
  160. \item Are there different figures-of-merit that must be balanced (CPU performance, specific background rejections.)?
  161. \end{itemize}
  162. \end{itemize}
  163. \vspace{1.5in}
  164. \end{frame}
  165. \appendix
  166. \backupbegin
  167. \begin{frame}
  168. \begin{center}
  169. {\Huge BACKUP}
  170. \end{center}
  171. \end{frame}
  172. \begin{frame}
  173. \begin{itemize}
  174. \item \textbf{Sim-Track \--} A track from a simulated electron originating from the luminous region of CMS (beam-spot +- 5$\sigma$)
  175. \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})
  176. \item \textbf{GSF Track \--} A track from GSF-Tracking resulting from an \textbf{ECAL-Driven Seed}
  177. \item \textbf{Seeding Efficiency \--} The fraction of \textbf{Sim-Tracks} that have a matching \textbf{ECAL-Driven Seed} (based on simhit-rechit linkage)
  178. \item \textbf{GSF Tracking Efficiency \--} The fraction of \textbf{Sim-Tracks} that have a matching \textbf{GSF Track} (again, based on simhit-rechit linkage)
  179. \item \textbf{ECAL-Driven Seed Purity \--} The fraction of \textbf{ECAL-Driven Seeds} that have a matching \textbf{Sim-Track}
  180. \item \textbf{GSF Tracking Purity \--} The fraction of \textbf{GSF Tracks} that have a matching \textbf{Sim-Track}
  181. \end{itemize}
  182. \end{frame}
  183. \begin{frame}{Triplet Electron Seeding \-- Setup}
  184. \begin{columns}
  185. \begin{column}{0.45\textwidth}
  186. \begin{itemize}
  187. \item Begin with ECAL super cluster and beam spot
  188. \end{itemize}
  189. \end{column}
  190. \begin{column}{0.55\textwidth}
  191. \begin{figure}
  192. \includegraphics[width=\textwidth]{diagrams/seeding_base.png}
  193. \end{figure}
  194. \end{column}
  195. \end{columns}
  196. \end{frame}
  197. \begin{frame}{Triplet Electron Seeding - Introduce Seed}
  198. \begin{columns}
  199. \begin{column}{0.45\textwidth}
  200. \begin{itemize}
  201. \item Now, examine, one-by-one seeds from general tracking*
  202. \item Note that we do not look at all hits in an event, but rather rely on general tracking to identify seeds.
  203. \end{itemize}
  204. \vspace{0.1in}
  205. \midrule
  206. \vspace{0.1in}
  207. {\footnotesize *initialStepSeeds, highPtTripletStepSeeds, mixedTripletStepSeeds, pixelLessStepSeeds, tripletElectronSeeds, pixelPairElectronSeeds, stripPairElectronSeeds}
  208. \end{column}
  209. \begin{column}{0.55\textwidth}
  210. \begin{figure}
  211. \includegraphics[width=\textwidth]{diagrams/seeding_step1.png}
  212. \end{figure}
  213. \end{column}
  214. \end{columns}
  215. \end{frame}
  216. \begin{frame}{Triplet Electron Seeding - Match First Hit}
  217. \begin{columns}
  218. \begin{column}{0.5\textwidth}
  219. \begin{itemize}
  220. \item Using the beam spot, the SC position, and SC energy, propagate a path through the pixels.
  221. \item Next, require the first hit to be within a $\delta\phi$ and $\delta z$ window. ($\delta\phi$ and $\delta R$ for FPIX)
  222. \item $\delta z$ window for first hit is huge as SC and beam spot positions give very little information about $z$.
  223. \end{itemize}
  224. \end{column}
  225. \begin{column}{0.5\textwidth}
  226. \begin{figure}
  227. \includegraphics[width=\textwidth]{diagrams/seeding_step2.png}
  228. \end{figure}
  229. \end{column}
  230. \end{columns}
  231. \end{frame}
  232. \begin{frame}{Triplet Electron Seeding - Extrapolate Vertex}
  233. \begin{columns}
  234. \begin{column}{0.45\textwidth}
  235. \begin{itemize}
  236. \item Once we have a matched hit, use it with the SC position, to find the vertex z.
  237. \item Vertex x and y are still the beam spot's.
  238. \item Just a simple linear extrapolation.
  239. \end{itemize}
  240. \end{column}
  241. \begin{column}{0.55\textwidth}
  242. \begin{figure}
  243. \includegraphics[width=\textwidth]{diagrams/vertex_z.png}
  244. \end{figure}
  245. \end{column}
  246. \end{columns}
  247. \end{frame}
  248. \begin{frame}{Triplet Electron Seeding - Match Other Hits}
  249. \begin{columns}
  250. \begin{column}{0.45\textwidth}
  251. \begin{itemize}
  252. \item Now forget the SC position, and propagate a new track based on the vertex and first hit positions, and the SC energy.
  253. \item Progress one-by-one through the remaining hits in the seed and require each one fit within a specified window around the track.
  254. \item Quit when all hits are matched, or a hit falls outside the window. No skipping is allowed.
  255. \item However, \emph{layer} skipping is not ruled out if the original seed is missing a hit in a layer
  256. \end{itemize}
  257. \end{column}
  258. \begin{column}{0.55\textwidth}
  259. \begin{figure}
  260. \includegraphics[width=\textwidth]{diagrams/seeding_step3.png}
  261. \end{figure}
  262. \end{column}
  263. \end{columns}
  264. \end{frame}
  265. \begin{frame}{Triplet Electron Seeding - Window Sizes}
  266. \begin{columns}
  267. \begin{column}{0.55\textwidth}
  268. \begin{itemize}
  269. \item The $\delta\phi$ and $\delta R/z$ windows for each hit are defined using three parameters.
  270. \begin{itemize}
  271. \item \texttt{highEt}
  272. \item \texttt{highEtThreshold}
  273. \item \texttt{lowEtGradient}
  274. \end{itemize}
  275. \item From these, the window size is calculated as \\
  276. $\texttt{highEt} + \min(0,\texttt{Et}-\texttt{highEtThreshold})*\texttt{lowEtGradient}$.
  277. \item For the first hit, these parameters for the $\delta \phi$ window are,
  278. \begin{itemize}
  279. \item $\texttt{highEt}=0.05$
  280. \item $\texttt{highEtThreshold}=20$
  281. \item $\texttt{lowEtGradient}=-0.002$
  282. \end{itemize}
  283. \end{itemize}
  284. \end{column}
  285. \begin{column}{0.45\textwidth}
  286. \begin{figure}
  287. \includegraphics[width=\textwidth]{figures/dphi1_max.png}
  288. \end{figure}
  289. \end{column}
  290. \end{columns}
  291. \vspace{0.1in} \hrule \vspace{0.1in}
  292. These parameters can be specified for each successive hit, and in bins of $\eta$, so optimization is a challenge!
  293. \end{frame}
  294. \begin{frame}{Triplet Electron Seeding - Handle Missing Hits}
  295. \begin{columns}
  296. \begin{column}{0.45\textwidth}
  297. \begin{itemize}
  298. \item Finally, calculate the expected number of hits based on the number of working pixel modules the track passes through.
  299. \item Require exact$^1$ number of matched hits depending on the expected number of hits.
  300. \begin{itemize}
  301. \item If $N_{\textrm{exp}}=4$, require $N_{\textrm{match}}=3$
  302. \item If $N_{\textrm{exp}}<4$, require $N_{\textrm{match}}=2$
  303. \end{itemize}
  304. \item If the seed passes all requirements, all information, including
  305. \begin{itemize}
  306. \item Super cluster
  307. \item Original Seed
  308. \item Residuals (For both charge hypotheses)
  309. \end{itemize}
  310. are wrapped up and sent downstream to GSF tracking
  311. \end{itemize}
  312. \end{column}
  313. \begin{column}{0.55\textwidth}
  314. \begin{figure}
  315. \includegraphics[width=\textwidth]{diagrams/seeding_step4.png}
  316. \end{figure}
  317. \end{column}
  318. \end{columns}
  319. \vspace{0.1in} \hrule \vspace{0.1in}
  320. {\footnotesize $^1$Exact, rather than minimum to deal with duplicate seeds in input collection. Could switch to minimum with offline cross-cleaned seeds.}
  321. \end{frame}
  322. \backupend
  323. \end{document}