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\clearpage
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\section {Analysis Demonstrations}
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A wide variety of physics analysis demonstrations were
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prepared by the
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physics groups for CSA06 in order to test the analysis workflow for
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CSA06. The analyses conducted on the CSA-produced data
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samples numbered approximately 30, with nearly 70
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active participants.
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These demonstrations proved to be useful training
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exercises for collaborators in the new software and computing tools as well.
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The list of specialized calibration and
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alignment streams produced at the Tier-0 and analyzed is discussed in
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Section~\ref{sec:offlineswalca}. The list of general physics analysis
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skims produced at the Tier-1 centres is covered in
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Table~\ref{tab:tier1skim}. Table~\ref{tab:analyses} lists the physics
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analyses that were conducted as part of CSA06. Details on these
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analyses are contained in the following subsections.
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%Unless noted,
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%CRAB was used to submit the analysis jobs.
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\begin{table}[phtb]
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\centering
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\caption{List of CSA06 analyses.}
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\vspace{3mm}
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\label{tab:analyses}
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\begin{tabular}{|l|l|l|l|}
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\hline
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Group & Analysis & People & Dataset \\ \hline
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eg & ECAL isol. electron calib. & L.Agostino (CERN), P. Govoni (Milan), & AlCaReco \\
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& & L.Malgeri (CERN), R.Ofierzynski (CERN) & \\
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eg & ECAL Phi symmetry calib. & D.Futyan (IC) & minbias AlCaReco \\
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eg & Z$\rightarrow ee$ reco. & P.Meridiani (Rome) & Zee AlCaReco \\
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\hline
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jm & HCAL Phi symmetry calib. & O.Kodolova (Moscow) & minbias AlCaReco \\
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jm & HCAL isol. trk. calib. & M.Szleper (Northwestern), & minbias AlCaReco \\
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& & S.Petrushanko (Moscow) & \\
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jm & Jet calib. & R.Harris, M.Cardaci (FNAL) & Jets \\
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\hline
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tk & Partial Tracker alignment & L.Edera, F.Ronga, and
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O.Buchmuller (CERN), & Zmumu AlcaReco \\
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& & F.-P. Schilling (Karlsruhe), & \\
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tk & Misalignments effects on track reco & M.Abbrescia, G.Cuscela,
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N.De Filippis, & Zmumu skim \\
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& & G.Donvito, G.Maggi, S.My (Bari) & \\
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\hline
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mu & Muon alignment & J.Fernandez, P.Martinez,
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& Muon AlCaReco \\
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& & F.Matorras (IFCA, Santander) & \\
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mu & W$\rightarrow\mu\nu$ & M.Biasotto, U.Gasparini, M.Margoni, & EWK, Soft Muon skims \\
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& & E.Torassa (Padova) & \\
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mu & J/Psi and Z$\rightarrow\mu\mu$ & J.Alcaraz, J.Hernandez,
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J.Caballero & EWK, Soft Muon skims \\
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& & P.Garcia Abia (CIEMAT) & \\
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mu & Z$\rightarrow\mu\mu$ and muon effic. & C.Liu and N.Neumeister (Purdue) & EWK skim \\
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& & M.Schmitt (Northwestern) & \\
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mu & Dimuon reconstruction & B.Kim (Florida) & SoftMuon, minbias \\
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\hline
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hg & Selection of Z$\rightarrow 2\tau$ &
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K.Petridis (IC), A.Kalinowski (Warsaw) & EWK skims \\
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hg & jet$\rightarrow \tau$ mis id &
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F.Blekman (IC), C.Siamitros (Brunel) & Z+jet\\
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hg & tau tagging efficiency from Z$\rightarrow 2\tau$ &
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S.Gennai and G.Bagliesi (Pisa), & EWK skims \\
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& & A.Goussiou and R.Vasques Sierra (FNAL) & \\
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hg & tau HLT with pixel trigger using Z$\rightarrow 2\tau$ &
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D.Kotlinski and P.Trueb (PSI) & EWK skims \\
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hg & Background to H$\rightarrow WW\rightarrow \ell\ell$ &
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F. Stoeckli (ETH) & TTbar \\
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hg & Z+2Jet background to qqH, H$\rightarrow$inv &
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J.Brooke and S.Metson (Bristol), & EWK skims \\
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& & K. Mazumdar (TIFR), S.Bansal (Panjab) & \\
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\hline
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sm & underlying event/minbias & L.Fano and F.Ambroglini (Pisa) &
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m.b., Jets, D-Y skims \\
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& & P.Bartalini and R.Field (Florida) & \\
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& & F.Bechtel (Hamburg) & \\
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sm & T-Tbar dilepton selection & I.Gonzalez-Caballero (IFCA, Santander), & TTbar skim \\
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& & J.Cuevas Maestro (Oviedo) & \\
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sm & T-Tbar inclusive & I.Gonzalez-Caballero (IFCA, Santander), & TTbar skims \\
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& & J.Vizan (Oviedo) & \\
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& & J.Heynick (Brussels) & \\
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& & J.Vizan (Oviedo) & \\
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sm & W mass & M.Malberti (Milan) & EWK skim \\
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\hline
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su & LM1 Jets + MET & M.Tytgat, M.Spiropulu (CERN) & Exotic, TTbar skims \\
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su & Di-tau + MET & L.Houchu, D.J.Mangeol (Strasbourg) & Exotic \\
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su & LM1 electron cleanup & F.Moortgat, L.Pape & Exotic \\
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su & LM1 b-tagging & R.Stringer (Riverside) & Exotic \\
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su & Dijet mass & R.Harris, M.Cardaci (FNAL) & QCD, Exotic skims\\
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su & High energy $e^+e^-$ & P.Vanlaer (Brussels),
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D.Evans (Bristol), & Exotic, EWK skims \\
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& & C.Shepherd-Themistocleous (RAL) & \\
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su & Z$'\rightarrow \mu^+\mu^-$ & M.Tytgat, M.Spiropulu (CERN) & Exotic \\
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su & Z$'\rightarrow \mu^+\mu^-$ & A.Lanyov, S.Shmatov (Dubna) & Exotic \\
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\hline
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\end{tabular}
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\end{table}
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\subsection {Calibration}
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\label{sec:calib}
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\input{calib_ana.tex}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\subsection {Alignment}
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\label{sec:align}
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\subsubsection{Tracker Alignment}
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A tracker alignment CSA06 exercise was carried out with the goal to
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demonstrate the full work- and dataflow of the alignment process.
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The exercise followed closely the ideas and concepts
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developed during the T0-RTAG~\cite{tier0rtag}.
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The exercise comprised the following steps:
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\begin{itemize}
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\item Reading of alignment constants from the offline database during prompt
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reconstruction;
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\item Writing dedicated AlCaReco streams for alignment;
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\item Defining a misalignment scenario and insertion of the corresponding
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object into the offline database;
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\item Running an alignment algorithm at the Tier-0;
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\item Inserting the resulting alignment corrections into the database;
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\item Running re-reconstruction at a Tier-1 centre reading this alignment
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object;
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\item Running analysis jobs in which ideal, misaligned
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and aligned distributions are compared.
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\end{itemize}
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The steps regarding production of the dedicated AlCaReco streams
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as well as enabling the prompt reconstruction to read alignment
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constants from the offline database were already described in
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section~\ref{sec:offlineswalca}. In the following, a short
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summary of the exercise is given. For more details,
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see~\cite{alcacsa06note}.
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The following misalignment scenario was defined for this exercise: The
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sensors of the Tracker Inner Barrel TIB as well as the Rods of the
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Tracker Outer Barrel TOB were misaligned. Random shifts drawing from
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a flat distribution in the range $\pm 100 \rm\ \mu m$ were applied in
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$u$, $v$, $w$ (local coordinate system) for layers built from double
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sided modules, and in $u$ (precise coordinate) only for layers built
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from single sided modules. In addition, random rotations around all
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three local coordinate axes of size $\pm 10 \rm\ mrad$ were applied to
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the modules/rods of both single and double sided TIB and TOB layers.
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The pixel detector was kept fixed
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in order to define a reference system. In addition, the outermost TOB
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layer was also kept fixed in order to improve the convergence. This
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misalignment scenario was inserted as an alignment object into the
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offline database. In addition, another object corresponding to the
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ideal tracker geometry was inserted, to be used during prompt
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reconstruction.
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\begin{figure}
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\centering
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\includegraphics[width=0.8\linewidth]{figs/csa06_convergence}
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\caption{Alignment exercise: The convergence of the alignment
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algorithm in $\Delta u, \Delta v, \Delta w$ is shown for double sided
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TIB modules as a function of the iteration number (left), as well as
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projected for initial misalignment (labeled ``after 0 Iterations'')
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and after 4, 7 and 10 iterations (right). }
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\label{fig:alignment_convergence}
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\end{figure}
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The alignment was performed running the HIP alignment
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algorithm~\cite{hipnote} as implemented in CMSSW\_1\_0\_6 over approximately
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$1 \rm\ M$ AlCaReco $Z^0\rightarrow\mu^+\mu^-$ events produced during
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prompt reconstruction at the Tier-0, reading the above mentioned
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misalignment object from the offline database. The algorithm was run
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on 20 dedicated CPUs in parallel at CERN, iterating 10 times over the
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data sample. The result of the alignment was obtained in less than $5
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\rm\ h$, and the corresponding tracker alignment object
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was inserted into the database. Figure~\ref{fig:alignment_convergence}
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illustrates the convergence of the alignment for the double sided TIB
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sensors.
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|
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\begin{figure}
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\centering
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| 185 |
\includegraphics[width=0.8\linewidth]{figs/csa06_aliexercise}
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\caption{Invariant mass distribution from $Z^0\to \mu^+ \mu^-$ events,
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obtained from events produced by the prompt reconstruction at
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the Tier-0 (``ideal''), from events processed with misalignment
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as used as input for the alignment algorithm (``misaligned'') and
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from events re-reconstructed at a Tier-1 centre (PIC) using the alignment
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constants derived from the alignment algorithm (``realigned'').
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}
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\label{fig:aliexercise}
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\end{figure}
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|
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Once the alignment and calibration constants were inserted in the
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database, they were deployed to the Tier-1/2 centres via Frontier.
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Subsequently, re-reconstruction of some of the CSA06 datasets was
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launched at various Tier-1 centres as described in Section~\ref{sec:rereco}. For instance, the
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$Z^0\rightarrow\mu^+\mu^-$ data set was re-reconstructed at PIC
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(Barcelona) using the new alignment object. In order to demonstrate
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the final missing piece of the workflow, grid analysis jobs were
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submitted to PIC to process these re-reconstructed
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$Z^0\rightarrow\mu^+\mu^-$ events. The reconstructed invariant dimuon
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mass is presented in Figure~\ref{fig:aliexercise} for three cases:
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\begin{itemize}
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\item Using the ideal geometry, reading the RECO produced during prompt
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reconstruction;
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\item Using the misaligned geometry, reading the AlCaReco and the misalignment
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scenario database object;
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\item Using the realigned geometry, reading the events re-reconstructed
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with the alignment database object.
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\end{itemize}
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As can be seen, the invariant mass resolution is degraded in the case
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of misalignment. After the alignment algorithm has corrected the
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tracker geometry, the resolution is recovered close to the original
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value. This demonstrates that the work- and dataflow of the full
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alignment was successfully carried out.
|
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|
| 220 |
|
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\input{muonalignment.tex}
|
| 222 |
|
| 223 |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
| 224 |
|
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\subsection {Physics Analysis Exercises}
|
| 226 |
|
| 227 |
\subsubsection {Effect of tracker misalignment on track reconstruction performances}
|
| 228 |
|
| 229 |
The alignment uncertainties of the CMS Tracker detector, made of a huge amount of independent silicon sensors with an excellent position resolution, affect the performances of the track reconstruction and track parameters measurement.
|
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The purpose of the analysis exercise performed by the team at Bari
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| 231 |
during the CSA06 was to study the effect of the CMS tracker misalignment on
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the performance of the track reconstruction
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\cite{misalignment}. Realistic estimates for the expected
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displacements of the tracking systems were supplied in different
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scenarios as specified in the following:
|
| 236 |
|
| 237 |
\begin{itemize}
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\item the ideal scenario with a perfect tracker geometry;
|
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\item the short term misalignment scenario representing the
|
| 240 |
typical mis-alignment conditions during the first
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data-taking when the uncertainties on the position of the sub-structures of the CMS
|
| 242 |
tracker will be between $10 \, \mu$m for pixel detectors and $400 \, \mu$m for microstrip silicon detectors in
|
| 243 |
the endcaps. Detector position and errors are read
|
| 244 |
from the offline database at CERN by caching the needed information locally via frontier/squid
|
| 245 |
software.
|
| 246 |
|
| 247 |
\item the long term scenario when the alignment uncertainties are expected to be a factor 10 smaller because of the
|
| 248 |
improvement obtained by using alignment algorithms with a high statistics of tracks.
|
| 249 |
|
| 250 |
\item the CSA06 aligned scenario by using the tracker module position and errors as obtained by the output of the
|
| 251 |
alignment procedure (Section~\ref{sec:align}) that was run at the
|
| 252 |
CERN Tier-0 to verify the efficiency of the alignment procedure on
|
| 253 |
the track
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| 254 |
reconstruction. The refit of tracks is performed also in this case.
|
| 255 |
|
| 256 |
\end{itemize}
|
| 257 |
|
| 258 |
Track reconstruction is based on the Kalman Filter formalism \cite{Kalman} for trajectory building, cleaning and
|
| 259 |
smoothing steps and uses hits from pixel detector as seeds to provide initial trajectory candidates.
|
| 260 |
Because of the misalignment, the analysis requires to refit tracks with a misaligned tracker geometry.
|
| 261 |
Global efficiency of track reconstruction and track parameter resolutions for muons were
|
| 262 |
compared in all the cases. The association between simulated track and reconstructed tracks is performed
|
| 263 |
by comparing the corresponding track parameters at the closest approach point and choosing the pair which gives
|
| 264 |
the minimum $\chi^2$ from the best fit procedure.
|
| 265 |
|
| 266 |
Events from CSA06 $Z\rightarrow \mu \mu $ sample were firstly skimmed by selecting events with
|
| 267 |
Hep MC muons from Z decay with pseudorapidity, $\eta$, in the tracker acceptance, $|\eta| < 2.55$,
|
| 268 |
with a transverse momentum larger than $5 \, \mathrm{GeV}/c^2$ and a dimuon invariant mass in the following
|
| 269 |
range aroung the Z peak: $50 < m_{\mu\mu}(\mathrm{GeV}/c^2) < 130$. The efficiency of this selection is
|
| 270 |
between 50 and 60\% mainly due to the cut on the acceptance, for a
|
| 271 |
final sample of 1 million events.
|
| 272 |
The output files in RECOSIM format were needed for the subsequent analysis.
|
| 273 |
|
| 274 |
|
| 275 |
Jobs executing the misalignment analysis were submitted at Bari with CRAB\_1\_4\_0 in the LCG infrastructure.
|
| 276 |
A total of about 2.5 thousands jobs (45 at most in parallel) ran with a grid efficiency of 90\% and an
|
| 277 |
application efficiency of 80\%, by accessing detector position and errors from the offline database via
|
| 278 |
frontier.
|
| 279 |
|
| 280 |
|
| 281 |
Some results of the misalignment analysis are summarized below. The global efficiency of track reconstruction of muons coming from
|
| 282 |
Z decay is shown in Fig.~\ref{eff} as a function of the pseudorapidity, $\eta$, in the tracker acceptance.
|
| 283 |
In the case of a perfect geometry the global track reconstruction is not fully efficient over all the $\eta$
|
| 284 |
range because of the track associator algorithm itself, which discards tracks with $\chi^2$ of the fit larger
|
| 285 |
than 25. The effect of misalignment is relevant observed ib the short term scenario and causes a partial inefficiency of the
|
| 286 |
track reconstruction that can be recovered if the intrinsic position resolution of the tracker
|
| 287 |
detector is combined with the alignment uncertainties to make larger the error on the position of the
|
| 288 |
reconstructed hit (called the alignment position error, or APE) so improving the track fit at the
|
| 289 |
expense of a larger rate of fake tracks.
|
| 290 |
|
| 291 |
|
| 292 |
The transverse momentum resolution as a function of the transverse momentum is reported in Fig.~\ref{respt};
|
| 293 |
the degradation of the transverse momentum resolution at large $p_{T}$ because of the misalignment is in a factor
|
| 294 |
between 2 and 3 with respect to the perfect geometry case. At low transverse momentum (less than few $\mathrm{GeV}/c$
|
| 295 |
the multiple scattering is the
|
| 296 |
most important contribution to the resolution so the effect of
|
| 297 |
misalignment is negligible.
|
| 298 |
|
| 299 |
The residual of the Z mass obtained as the invariant mass of muons coming from Z decays for the case of perfect
|
| 300 |
tracker geometry and for the short-term and long term misalignment scenarios is shown in Fig.~\ref{mz}; the $\sigma$ of
|
| 301 |
the Gaussian fit of the residual distribution can be quoted as the Z mass resolution which is degraded by a factor 2
|
| 302 |
because of the tracker misalignment in the short term scenario.
|
| 303 |
|
| 304 |
\begin{2figures}{hbt}
|
| 305 |
\resizebox{\linewidth}{!}{\includegraphics{figs/Eff_eta}} &
|
| 306 |
\resizebox{\linewidth}{!}{\includegraphics{figs/SigmapT_pT}} \\
|
| 307 |
\caption{Global track reconstruction efficiency vs pseudorapidity for muons coming from Z decay in the case of perfect
|
| 308 |
tracker geometry and in short-term and long term misalignment scenarios when the APE is not used.}
|
| 309 |
\label{eff} &
|
| 310 |
\caption{$p_{T}$ resolution vs $p_{T}$ in the case of perfect
|
| 311 |
tracker geometry and in short-term and long term misalignment scenarios.}
|
| 312 |
\label{respt} \\
|
| 313 |
\end{2figures}
|
| 314 |
|
| 315 |
|
| 316 |
\begin{figure}[htb]
|
| 317 |
\begin{center}
|
| 318 |
\resizebox{0.7\linewidth}{!}{\includegraphics{figs/Residual_mZ_mu}}
|
| 319 |
\end{center}
|
| 320 |
\caption{Residual of Z mass obtained as the invariant mass of muons coming from Z decayd for the case of perfect
|
| 321 |
tracker geometry and for the short-term and long term misalignment scenarios.}
|
| 322 |
\label{mz}
|
| 323 |
\end{figure}
|
| 324 |
|
| 325 |
% muon analyses
|
| 326 |
|
| 327 |
\input{wmunu.tex}
|
| 328 |
|
| 329 |
\input{dimuon.tex}
|
| 330 |
|
| 331 |
% electron analyses
|
| 332 |
\input{zee.tex}
|
| 333 |
|
| 334 |
\input{wmass.tex}
|
| 335 |
|
| 336 |
|
| 337 |
% tau analyses:
|
| 338 |
|
| 339 |
\input{z_2tau.tex}
|
| 340 |
|
| 341 |
\input{taumisid.tex}
|
| 342 |
|
| 343 |
\input{tau_validation.tex}
|
| 344 |
|
| 345 |
% Higgs
|
| 346 |
\input{hww_2l.tex}
|
| 347 |
|
| 348 |
\input{qqh_inv_zbkg.tex}
|
| 349 |
|
| 350 |
% min bias studies
|
| 351 |
\input{mbue.tex}
|
| 352 |
|
| 353 |
\input{ttbar_ana.tex}
|
| 354 |
|
| 355 |
% SUSY
|
| 356 |
\input{susybsm.tex}
|
| 357 |
|
| 358 |
%BSM analyses
|
| 359 |
%input{heep-analysis.tex}
|
