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r113 r116 2 2 %\usepackage[english]{babel} 3 3 \usepackage[ansinew]{inputenc} 4 \usepackage{abstract}5 4 6 5 \usepackage{amsmath} … … 68 67 % - 3) permet de comparer 69 68 70 Experiments at high energy colliders are very complex systems, in several ways. First, in terms of the various detector subsystems, including tracking, central calorimetry, forward calorimetry, and muon chambers , with different principles, technologies, geometries and sensitivities. Then, due to the requirement of a highly effective online selection (i.e. a \textit{trigger}) which is subdivided into several levels for an optimal reduction factor, but based only on partial data. Finally, in terms of the experiment software with different data format(like \textit{raw} or \textit{reconstructed} data), many reconstruction algorithms and particle identification schemes.69 Experiments at high energy colliders are very complex systems, in several ways. First, in terms of the various detector subsystems, including tracking, central calorimetry, forward calorimetry, and muon chambers. These detectors differ with their principles, technologies, geometries and sensitivities. Then, due to the requirement of a highly effective online selection (i.e. a \textit{trigger}), subdivided into several levels for an optimal reduction factor, but based only on partially processed data. Finally, in terms of the experiment software, with different data formats (like \textit{raw} or \textit{reconstructed} data), many reconstruction algorithms and particle identification schemes. 71 70 72 71 This complexity is handled by large collaborations of thousands of people, which restrict the availability of the data, software and documentation to their members. Real data analyses require a full detector simulation, including the various detector inefficiencies, the dead material, the imperfections and the geometrical details. Moreover, detector calibration and alignment are crucial. Such simulation is very complicated, technical and slow. On the other hand, phenomenological studies, looking for the observability of given signals, may require only fast but realistic estimates of the observables. … … 80 79 \begin{figure}[!h] 81 80 \begin{center} 82 \includegraphics[width=\columnwidth]{FlowDelphes} 83 \caption{Flow chart describing the principles behind \textsc{Delphes}.} 81 \includegraphics[width=0.9\columnwidth]{FlowDelphes} 82 \caption{Flow chart describing the principles behind \textsc{Delphes}. Event files coming from external Monte Carlo generators are read by a convertor stage. 83 The kinematical variables of the final state particles are then smeared according to the subdetector resolutions. 84 Tracks are reconstructed in a simulated dipolar magnetic field and calorimetric towers sample the energy deposits. Based on these, dedicated algorithms are applied for particle identification, isolation and reconstruction. 85 The transport of very forward particle to the near-beam detectors is also simulated. 86 Finally, an output file is written, including generator level and analysis object data. If requested, a fully parametrisable trigger can be emulated. Optionnally, the geometry and visualisation files for the 3D event display can also be produced. 87 All user parameters are set in the \textit{Smearing Card} and the \textit{Trigger Card}. } 84 88 \label{fig:FlowChart} 85 89 \end{center} 86 90 \end{figure} 87 91 88 Although this kind of approach yields much realistic results than a simple ``parton-level" analysis, a fast simulation comes with some limitations. Detector geometry is idealised, being uniform, symmetric around the beam axis, and having no craks nor dead material. Secondary interactions, multiple scatterings, photon conversion and bremsstrahlung are also neglected. 89 % 90 91 92 The simulation package proceeds in two stages. The first part is executed on the generated events. ``Particle-level" informations are read from input files and stored in a {\it \textsc{gen}} \textsc{root} tree. Three varieties of input files can currently be used as input in \textsc{Delphes}. In order to process events from many different generators, the standard Monte Carlo event structure StdHep can be used as an input. Besides, \textsc{Delphes} can also provide detector response for events read in "Les Houches Event Format" (\textsc{lhef}) and \textsc{root} files obtained using the {\bf h2root} converter program. This first stage is performed using three C++ classes: {\verb HEPEVTConverter }, {\verb LHEFConverter } and {\verb STDHEPConverter }. 93 Afterwards, \textsc{Delphes} performs a simple trigger simulation and reconstruct "high-level objects". These informations are organised in classes and each objects are ordered with respect to the transverse momentum. The output of the various C++ classes is stored in the {\it Analysis} tree. The program is driven by a datacard (data/DataCardDet.dat) which allow a large spectrum of running conditions by modifying basic detector parameters, including calorimeter and tracking coverage and resolution, thresholds or jet algorithm parameters.\\ 94 95 Usual algorithms are applied for the reconstruction of complex objects, like the missing transverse energy or the jets originating from $b$ quarks or $\tau$ leptons. 96 97 A simplified preselection can also be applied on processed data for trigger emulation. 98 All detectors are assumed to be symmetric with respect to the beam axis 92 Although this kind of approach yields much realistic results than a simple ``parton-level" analysis, a fast simulation comes with some limitations. Detector geometry is idealised, being uniform, symmetric around the beam axis, and having no cracks nor dead material. Secondary interactions, multiple scatterings, photon conversion and bremsstrahlung are also neglected. 93 94 %The simulation package proceeds in two stages. The first part is executed on the generated events. ``Particle-level" informations are read from input files and stored in a {\it \textsc{gen}} \textsc{root} tree. 95 96 Three formats of input files can currently be used as input in \textsc{Delphes}\footnote{The corresponding code can be found in the \texttt{HEPEVTConverter}, \texttt{LHEFConverter } and \texttt{STDHEPConverter} classes.}. In order to process events from many different generators, the standard Monte Carlo event structure \mbox{\textsc{s}td\textsc{hep}} can be used as an input. Besides, \textsc{Delphes} can also provide detector response for events read in ``Les Houches Event Format'' (\textsc{lhef}) and \textsc{root} files obtained using the \textbf{h2root} utility from the \textsc{root} framework~\cite{bib:root}. 97 %Afterwards, \textsc{Delphes} performs a simple trigger simulation and reconstruct "high-level objects". These informations are organised in classes and each objects are ordered with respect to the transverse momentum. 98 99 The output of \textsc{Delphes} contains a copy of the generator level data (\textsc{gen} tree), the analysis data objects after reconstruction (\mbox{\textsc{A}nalysis} tree), and possibly the results of the trigger emulation (\mbox{\textsc{T}rigger} tree). The program is driven by input cards. The detector card (\texttt{data/DataCardDet.dat}) allows a large spectrum of running conditions by modifying basic detector parameters, including calorimeter and tracking coverage and resolution, thresholds or jet algorithm parameters. The trigger card (\texttt{data/trigger.dat}) lists the user algorithms for the simplified online preselection.\\ 100 101 99 102 \section{Central detector simulation} 100 103 … … 102 105 \begin{center} 103 106 \includegraphics[width=\columnwidth]{Detector_Delphes_1} 104 \caption{Layout of the generic detector geometry assumed in \textsc{Delphes}. The innermost layer, close to the interaction point, is a ce 105 ntral tracking system (pink). It is surrounded by a central calorimeter volume (green) with both electromagnetic and hadronic sections. Th 106 e outer layer of the central system (red) consist of a muon system. In addition, two end-cap calorimeters (blue) extend the pseudorapidity 107 coverage of the central detector. The actual detector granularity and extension is defined in the user-configuration card. The detector i 108 s assumed to be strictly symmetric around the beam axis (black line). Additional forward detectors are not depicted.} 107 \caption{Layout of the generic detector geometry assumed in \textsc{Delphes}. The innermost layer, close to the interaction point, is a central tracking system (pink). 108 It is surrounded by a central calorimeter volume (green) with both electromagnetic and hadronic sections. 109 The outer layer of the central system (red) consist of a muon system. In addition, two end-cap calorimeters (blue) extend the pseudorapidity coverage of the central detector. 110 The actual detector granularity and extension is defined in the user-configuration card. The detector is assumed to be strictly symmetric around the beam axis (black line). Additional forward detectors are not depicted.} 109 111 \label{fig:GenDet} 110 112 \end{center} … … 114 116 \begin{center} 115 117 \includegraphics[width=0.5\columnwidth]{Detector_Delphes_3} 116 \caption{Profile of the layout assumed in \textsc{Delphes}. The extension of the various subdetectors, as defined in Tab.~\ref{tab:defEta} 117 , are clearly visible.Same colour codes as for Fig.~\ref{fig:GenDet} are applied. Additional forward detectors are not depicted.}118 \caption{Profile of the layout assumed in \textsc{Delphes}. The extension of the various subdetectors, as defined in Tab.~\ref{tab:defEta}, are clearly visible. 119 Same colour codes as for Fig.~\ref{fig:GenDet} are applied. Additional forward detectors are not depicted.} 118 120 \label{fig:GenDet3} 119 121 \end{center} … … 129 131 130 132 131 The overall layout of the general purpose detector simulated by \textsc{Delphes} is shown in figure \ref{fig:GenDet}. A central tracking system surrounded by an electromagnetic and a hadron calorimeters. A forward calorimeter ensures a larger geometric coverage for the measurement of the missing transverse energy. The fast simulation of the detector response takes into account geometrical acceptance of sub-detectors and their finite resolution. 133 The overall layout of the general purpose detector simulated by \textsc{Delphes} is shown in figure \ref{fig:GenDet}. A central tracking system is surrounded by an electromagnetic and a hadron calorimeters (\textsc{ecal} and \textsc{hcal}, resp.). A forward calorimeter ensures a larger geometric coverage for the measurement of the missing transverse energy. The fast simulation of the detector response takes into account geometrical acceptance of sub-detectors and their finite resolution, as defined in the smearing data card\footnote{See the \texttt{RESOLution} class.}. 134 If no such file is provided, predifined values are used. The coverage of the various subsystems used in the default configuration are summarized in table \ref{tab:defEta}. 132 135 133 136 \textcolor{red}{No smearing is applied on particle direction. (???)}\\ 134 137 135 Before starting to loop over events, the {\verb RESOLution } class loads all sub-detector resolutions and coverage from the detector parameter file. If no such file is provided, predifined values are used. The coverage of the various sub-systems used in the default configuration are summarized in table \ref{tab:defEta}.136 137 138 \begin{table}[!h] 138 139 \begin{center} 140 \caption{Default extension in pseudorapidity $\eta$ of the different subdetectors.} 139 141 \begin{tabular}[!h]{lll} 140 142 \hline 141 Tracking & {\verb CEN_max_tracker } & 2.5\\142 Calorimeters & {\verb CEN_max_calo_cen } & 3.0\\143 & {\verb CEN_max_calo_fwd } & 5.0\\144 Muon & {\verb CEN_max_mu } & 2.4\\\hline143 Tracking & {\verb CEN_max_tracker } & $0.0 \leq |\eta| \leq 2.5$\\ 144 Calorimeters & {\verb CEN_max_calo_cen } & $0.0 \leq |\eta| \leq 3.0$\\ 145 & {\verb CEN_max_calo_fwd } & $3.0 \leq |\eta| \leq5.0$\\ 146 Muon & {\verb CEN_max_mu } & $0.0 \leq |\eta| \leq 2.4$\\\hline 145 147 \end{tabular} 146 148 \label{tab:defEta} … … 154 156 \frac{\sigma}{E} = \frac{S}{\sqrt{E}} \oplus \frac{N}{E} \oplus C, 155 157 \end{equation} 156 where S is the stochastic term, N the noise and C the constant term.\\ 157 158 The response of the detector is applied to the electromagnetic and the hadronic particles through the {\verb SmearElectron }and {\verb SmearHadron } functions. The 4-momentum $p^\mu$ are smeared with a parametrisation directly derived from the detector techinal designs. In the default parametrisation, the calorimeter is assumed to cover the pseudorapidity range $|\eta|<3$ and consists in an electromagnetic and an hadronic part. Coverage between pseudorapidities of 3.0 and 5.0 is provided by a forward calorimeter. The response of this calorimeter can be different for electrons and hadrons. The default values of the stochastic, noisy and constant terms as well as the ``Card flag" names used in the configuration file are given in table \ref{tab:defResol}.\\ 158 where $S$ is the stochastic term, $N$ the noise and $C$ the constant term.\\ 159 160 161 The 4-momentum $p^\mu$ are smeared with a parametrisation directly derived from the detector techinal designs\footnote{The response of the detector is applied to the electromagnetic and the hadronic particles through the \texttt{SmearElectron} and \texttt{SmearHadron} functions.}. 162 In the default parametrisation, the calorimeter is assumed to cover the pseudorapidity range $|\eta|<3$ and consists in an electromagnetic and an hadronic part. Coverage between pseudorapidities of $3.0$ and $5.0$ is provided by a forward calorimeter. The response of this calorimeter can be different for electrons and hadrons. The default values of the stochastic, noisy and constant terms are given in table \ref{tab:defResol}.\\ 159 163 160 164 \begin{table}[!h] 161 165 \begin{center} 166 \caption{Default values for the resolution of the central and forward calorimeter. The corresponding parameter name, in the smearing card, is given.} 162 167 \begin{tabular}[!h]{lclc} 163 168 \hline 164 169 \multicolumn{2}{c}{Resolution Term} & Card flag & Value\\\hline 165 Central \textsc{ecal} & S & {\verb ELG_Scen } & 0.05 \\ 166 & N & {\verb ELG_Ncen } & 0.25 \\ 167 & C & {\verb ELG_Ccen } & 0.0055 \\ 168 Forward \textsc{ecal} & S & {\verb ELG_Sfwd } & 2.084 \\ 169 & N & {\verb ELG_Nfwd } & 0.0 \\ 170 & C & {\verb ELG_Cfwd } & 0.107 \\ 171 Central \textsc{hcal} & S & {\verb HAD_Shcal } & 1.5 \\ 172 & N & {\verb HAD_Nhcal } & 0.\\ 173 & C & {\verb HAD_Chcal } & 0.05\\ 174 Forward \textsc{hcal} & S & {\verb HAD_Shf } & 2.7\\ 175 & N & {\verb HAD_Nhf } & 0. \\ 176 & C & {\verb HAD_Chf } & 0.13\\ 170 \multicolumn{4}{l}{Central \textsc{ecal}} \\ 171 & $S$ & {\verb ELG_Scen } & $0.05$ \\ 172 & $N$ & {\verb ELG_Ncen } & $0.25$ \\ 173 & $C$ & {\verb ELG_Ccen } & $0.0055$ \\ 174 \multicolumn{4}{l}{Forward \textsc{ecal}} \\ 175 & $S$ & {\verb ELG_Sfwd } & $2.084$ \\ 176 & $N$ & {\verb ELG_Nfwd } & $0.0$ \\ 177 & $C$ & {\verb ELG_Cfwd } & $0.107$ \\ 178 \multicolumn{4}{l}{Central \textsc{hcal}} \\ 179 & $S$ & {\verb HAD_Shcal } & $1.5$ \\ 180 & $N$ & {\verb HAD_Nhcal } & $0.$\\ 181 & $C$ & {\verb HAD_Chcal } & $0.05$\\ 182 \multicolumn{4}{l}{Forward \textsc{hcal}} \\ 183 & $S$ & {\verb HAD_Shf } & $2.7$\\ 184 & $N$ & {\verb HAD_Nhf } & $0$. \\ 185 & $C$ & {\verb HAD_Chf } & $0.13$\\ 177 186 \hline 178 187 \end{tabular} … … 187 196 where $0 \leq F \leq 1$. The electromagnetic part is handled as the electrons, while the resolution terms used for the hadronic part are {\verb HAD_Shcal }, {\verb HAD_Nhcal } and {\verb HAD_Chcal }. The resulting final energy given after the application of the smearing is then $E = E_{hcal} + E_{ecal}$.\\ 188 197 198 \subsection{Calorimetric towers} 199 200 All undecayed particles, except muons and neutrinos are producing a calorimetric tower. 201 A calorimetric tower are just the smallest unit in $\eta \times \phi$ for the segmentation of the energy measurement. As the detector is assumed to be symmetric in $\phi$ and with respect to the $(x,y)$ plane, the smearing card stores the number of calorimetric towers with $\phi=0$ and $\eta>0$ (default: $40$ towers). For a given $\eta$, the size of the $\phi$ segmentation is also specified. 202 The calorimeters are then segmented into towers, that directly enter in the calculation of the missing transverse energy. 203 No longitudinal segmentation is available in the simulated calorimeters. 204 189 205 190 206 \subsection{Muon smearing} 191 207 192 208 Muons candidates are searched 193 The smearing ot the muon 4-momentum $p^\mu$ is given by a Gaussian smearing of the $p_T$ function \texttt{SmearMuon}. Only the $p_T$ is smeared, but neither $\eta$ nor $\phi$. 209 The smearing ot the muon 4-momentum $p^\mu$ is given by a Gaussian smearing of the $p_T$ function \texttt{SmearMuon}. Only the $p_T$ is smeared, but neither $\eta$ nor $\phi$. Multiple scattering is thus neglected, while low energy muons have a worst resolution in a real detector. 194 210 195 211 \subsection{Tracks reconstruction} 196 197 All stable charged particles lying inside the fiducial volume of the tracking coverage provide a track. The reconstructio efficiency is manageable in the input datacard through the {\verb TRACKING_EFF } term. By default, a track is assumed to be reconstructed with $90\%$ probability. 198 199 \subsection{Calorimetric towers} 200 201 All undecayed particles, except muons and neutrinos are producing a calorimetric tower. The same particles enter in the calculation of the missing transverse energy. \textit{what is used is the particle smeared momentum, not the calorimetric towers!} 212 Every stable charged particle with a transverse momentum above some threshold and lying inside the fiducial volume of the tracker provides a track. The reconstructio efficiency is defined in the smearing datacard by the {\verb TRACKING_EFF } term. By default, a track is assumed to be reconstructed with $90\%$ probability if its transverse momentum $p_T$ is higher than $0.9~\textrm{GeV}$ and if its pseudorapidity $|\eta| \leq 2.5$. 213 202 214 203 215 \subsection{Isolated lepton reconstruction} 204 216 205 Photon and electron candidates are reconstructed if they fall into the acceptance of the tracking system and have a transverse momentum above the {\verb ELEC_pt } value ( 10~GeV by default). Muons candidates are searched206 217 Photon and electron candidates are reconstructed if they fall into the acceptance of the tracking system and have a transverse momentum above the {\verb ELEC_pt } value ($10~\textrm{GeV}$ by default). 218 %Muons candidates are searched 207 219 Lepton isolation demands that there is no other charged particles with $p_T>2$~GeV within a cone of $\Delta R<0.5$ around the lepton.\\ 208 220 209 221 \subsection{Very forward detectors simulation} 210 222 211 Some subdetectors have the ability to measure the time of flight of the particle. This correspond to the delay after which the particle is observed in the detector, after the bunch crossing. The time of flight measurement of ZDC and FP420 detector is implemented here. For the ZDC, the formula is simply223 Some subdetectors have the ability to measure the time of flight of the particle. This correspond to the delay after which the particle is observed in the detector, after the bunch crossing. The time of flight measurement of \textsc{zdc} and \textsc{fp420} detector is implemented here. For the \textsc{zdc}, the formula is simply 212 224 \begin{equation} 213 225 t_2 = t_1 + \frac{1}{v} \times \big( \frac{s-z}{\cos \theta}\big), 214 226 \end{equation} 215 where $t_2$ is the time of flight, $t_1$ is the true time coordinate of the vertex from which the particle originates, $v$ the particle velocity, $s$ is the ZDC distance to the interaction point, $z$ is the longitudinal coordinate of the vertex from which the particle comes from, $theta$ is the particle emission angle. This assumes that the neutral particle observed in the ZDCis highly relativistic, i.e. travelling at the speed of light $c$. We also assume that $\cos \theta = 1$, i.e. $\theta \approx 0$ or equivalently $\eta$ is large. As an example, $\eta = 5$ leads to $\theta = 0.013$ and $1 - \cos \theta < 10^{-4}$.227 where $t_2$ is the time of flight, $t_1$ is the true time coordinate of the vertex from which the particle originates, $v$ the particle velocity, $s$ is the \textsc{zdc} distance to the interaction point, $z$ is the longitudinal coordinate of the vertex from which the particle comes from, $\theta$ is the particle emission angle. This assumes that the neutral particle observed in the \textsc{zdc} is highly relativistic, i.e. travelling at the speed of light $c$. We also assume that $\cos \theta = 1$, i.e. $\theta \approx 0$ or equivalently $\eta$ is large. As an example, $\eta = 5$ leads to $\theta = 0.013$ and $1 - \cos \theta < 10^{-4}$. 216 228 The formula then reduces to 217 229 \begin{equation} 218 230 t_2 = \frac{1}{c} \times (s-z) 219 231 \end{equation} 220 NB : for the moment, only neutrons and photons are assumed to be able to reach the ZDC. All other particles are neglected 221 222 To fix the ideas, if the ZDC is located at $s=140~\textrm{m}$, neglecting $z$ and $\theta$, and assuming that $v=c$, one gets $t=0.47~\mu\textrm{s}$. 223 224 \section{``High-level" objects reconstruction} 232 Only neutrons and photons are currently assumed to be able to reach the \textsc{zdc}. All other particles are neglected 233 To fix the ideas, if the \textsc{zdc} is located at $s=140~\textrm{m}$, neglecting $z$ and $\theta$, and assuming that $v=c$, one gets $t=0.47~\mu\textrm{s}$. 234 235 \section{High-level object reconstruction} 236 237 Hadronising final state particles or invisible ones are more difficult to measure. For instance, light jets or jets originating from $b$ quarks or $\tau$ leptons require dedicated algorithms for their measurement. 238 The \textsc{FastJet} tools have been integrated into the \textsc{Delphes} framework for a fast jet reconstruction, using several algorithms, like Cone or $k_T$ ones. 239 240 \textcolor{red}{More on jet algorithms?} 225 241 226 242 \subsection{Jet reconstruction} 227 243 228 Jets are reconstructed using a cone algorithm with $R=0.7$ and make only use of the smeared particle momenta. The reconstructed jets are required to have a transverse momentum above 20~GeV and $|\eta|<3.0$. A jet is tagged as $b$-jets if its direction lies in the acceptance of the tracker, $|\eta|<0.5$, and if it is associated to a parent $b$-quark. A $b$-tagging efficiency of $40\%$ is assumed if the jet has a parent $b$ quark. For $c$-jets and light/gluon jets, a fake $b$-tagging efficiency of $10 \%$ and $1 \%$ respectively is assumed.\\ 244 By default, jets are reconstructed using a cone algorithm with $R=0.7$ and use the calorimetric towers. The reconstructed jets are required to have a transverse momentum above $20~\textrm{GeV}$ and $|\eta|<3.0$. 229 245 230 246 \subsection{$b$-tagging} 231 247 232 The simulation of the $b$-tagging is based on the detector efficiencies assumed (1) for the tagging of a $b$-jet and (2) for the mis-identification of other jets as $b$-jets. This relies on the TAGGING\_B, MISTAGGING\_C and MISTAGGING\_L constants, for (respectively) the efficiency of tagging of a $b$-jet, the efficiency of mistagging a c-jet as a $b$-jet, and the efficiency of mistatting a light jet (u,d,s,g) as a $b$-jet. The (mis)tagging relies on the particle ID of the most energetic particle within a cone around the observed (eta,phi) region, with a radius CONERADIUS.248 A jet is tagged as $b$-jets if its direction lies in the acceptance of the tracker and if it is associated to a parent $b$-quark. A $b$-tagging efficiency of $40\%$ is assumed if the jet has a parent $b$ quark. For $c$-jets and light/gluon jets, a fake $b$-tagging efficiency of $10 \%$ and $1 \%$ respectively is assumed\footnote{Corresponding tot the TAGGING\_B, MISTAGGING\_C and MISTAGGING\_L constants, for (respectively) the efficiency of tagging of a $b$-jet, the efficiency of mistagging a c-jet as a $b$-jet, and the efficiency of mistatting a light jet (u,d,s,g) as a $b$-jet.}. The (mis)tagging relies on the particle ID of the most energetic particle within a cone around the observed (eta,phi) region, with a radius CONERADIUS. 233 249 234 250 \subsection{Tau identification} 235 251 236 252 \begin{wrapfigure}{l}{0.3\columnwidth} 237 \includegraphics[width=0.3\columnwidth]{Tau .eps}238 \caption{ \small{detectorAng.eps}}253 \includegraphics[width=0.3\columnwidth]{Tau} 254 \caption{Illustration of the identification of $\tau$ jets.} 239 255 \label{h_WW_ss_cut1} 240 256 \end{wrapfigure} 241 257 242 Jets originating from $\tau$-decay are identified using an identification procedure consistent with the one applied in a full detector simulation. The tagging rely on two tau properties. First, in roughly 75$\%$ of the time, the hadronic $\tau$-decay products contain only one charged hadron and a number of $\pi^0$. Second, the particles arisen from the $\tau$-lepton produce narrow jets in the calorimeter.258 Jets originating from $\tau$-decay are identified using an identification procedure consistent with the one applied in a full detector simulation. The tagging rely on two properties of the $\tau$ lepton. First, in roughly $75 \%$ of the time, the hadronic $\tau$-decay products contain only one charged hadron and a number of $\pi^0$. Second, the particles arisen from the $\tau$-lepton produce narrow jets in the calorimeter. 243 259 244 260 \subsubsection*{Electromagnetic collimation} … … 248 264 \begin{figure}[!h] 249 265 \begin{center} 250 %\includegraphics[width=0.8\columnwidth]{figures/Taujets1.eps}251 \caption{\ small{}}266 \includegraphics[width=0.8\columnwidth]{figures/Tau2} 267 \caption{\textcolor{red}{Distribution of the $\tau \bar \tau$ events} with respect to the electromagnetic collimation factor $C_\tau$. } 252 268 \label{fig:tau1} 253 269 \end{center} … … 258 274 \begin{figure}[!h] 259 275 \begin{center} 260 %\includegraphics[width=0.8\columnwidth]{figures/Taujets2.eps}261 \caption{\ small{}}276 \includegraphics[width=0.8\columnwidth]{figures/Tau1} 277 \caption{\textcolor{red}{Distribution of the...}} 262 278 \label{h_WW_ss_cut1} 263 279 \end{center} 264 280 \end{figure} 265 281 266 The tracking isolation for the $\tau$ identification requires that the number of tracks associated to a particle with $p_T >$ {\verb TAU_track_pt } is one and only one in a cone with $\Delta R =$ {\verb TAU_track_scone }. This cone should be entirely included in the tracker to be taken into account. This procedure selects taus decaying hadronically with a typical efficiency of $60\%$. Moreover, the minimal $p_T$ of the $\tau$-jet is required to be {\verb TAUJET_pt } (default value: 10~GeV).\\282 The tracking isolation for the $\tau$ identification requires that the number of tracks associated to a particle with $p_T >$ {\verb TAU_track_pt } is one and only one in a cone with $\Delta R =$ {\verb TAU_track_scone }. This cone should be entirely included in the tracker to be taken into account. This procedure selects taus decaying hadronically with a typical efficiency of $60\%$. Moreover, the minimal $p_T$ of the $\tau$-jet is required to be {\verb TAUJET_pt } (default value: $10~\textrm{GeV}$).\\ 267 283 268 284 \begin{table}[!h] … … 282 298 283 299 \subsection{Transverse missing energy} 300 In an ideal detector, the transverse missing energy is simply computed as the missing term which would balance the transverse momentum in the observed event. Its value is then computed as the opposite of the sum of the momentum of all observed particles. In a real experiment, any problem affecting the detector (dead channels, misalignment, noisy towers, cracks) is directly worsening the measured missing transverse energy. In this document, the missing transverse energy (\textcolor{red}{symbol???}) is based on the calorimetric towers and only muons and neutrinos are not taken into account for its evaluation. 284 301 285 302 \section{Trigger emulation} 303 304 New physics in collider experiment are often characterised by the phenomenology by low cross-section values. High statistics are required for their studies, which in turn imposes high luminosity collisions. 305 306 On the other hand, due to the very high collision rate in recent collider ($40~\textrm{MHz}$ at the \textsc{lhc}) and the large total cross-section ($\mathcal{O}(110~\textrm{mb})$ at the \textsc{lhc}), the need for an online event selection is crucial in order to reject most of the event and keep 286 307 287 308 \section{Validation} … … 407 428 \bibitem{bib:FastJet} \textsc{Fast-Jet}, 408 429 \bibitem{bib:Frog} \textsc{Frog}, 430 \bibitem{bib:CMSresolution} CMS IN 2007/053 431 \bibitem{bib:root} \textsc{Root} - An Object Oriented Data Analysis Framework, R. Brun and F. Rademakers, Nucl. Inst. \& Meth. in Phys. Res. A 389 (1997) 81-86, \url{http://root.cern.ch} 409 432 \end{thebibliography} 410 433
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