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trunk/paper/CommPhysComp/notes.tex
r540 r560 36 36 37 37 \author{X. Rouby} 38 %\author{X. Rouby\fnref{freiburg}}39 %\fntext[freiburg]{Now in Physikalisches Institut, Albert-Ludwigs-Universit\"at Freiburg}40 %\ead{xavier.rouby@cern.ch}41 42 38 \author{V. Lema\^itre} 43 39 … … 46 42 B-1348 Louvain-la-Neuve, Belgium} 47 43 48 %\author{X. Rouby}49 %\ead{xavier.rouby@cern.ch}50 51 %\address{Physikalisches Institut,52 % Albert-Ludwigs-Universit\"at Freiburg,53 % D-79104 Freiburg-im-Breisgau, Germany}54 55 44 \begin{abstract} 56 % It is always delicate to know whether theoretical predictions are visible and measurable in a high energy collider experiment due to the complexity of the related detectors, data acquisition chain and software. 57 % We introduce here a new \texttt{C++}-based framework, \textit{Delphes}, for fast simulation of 58 % a general-purpose experiment. The simulation includes a tracking system, embedded into a magnetic field, calorimetry and a muon 59 % system, and possible very forward detectors arranged along the beamline. 60 % The framework is interfaced to standard file formats (e.g.\ Les Houches Event File or \texttt{HepMC}) and outputs observable objects for analysis, like missing transverse energy and collections of electrons or jets. 61 % The simulation of detector response takes into account the detector resolution, and usual reconstruction algorithms, such as FastJet. A simplified preselection can also be applied on processed data for trigger emulation. Detection of very forward scattered particles relies on the transport in beamlines with the \textit{Hector} software. Finally, the \textsc{FROG} 2D/3D event display is used for visualisation of the collision final states. 62 % An overview of \textit{Delphes} is given as well as a few \textsc{LHC} use-cases for illustration.\\ \\ 63 64 It is sometimes difficult to know whether theoretical predictions can be observed in a high energy collider experiment, especially when expected experimental signature involve jets and missing transverse energy. 65 For this purpose, we have designed a new \texttt{C++}-based framework, \textit{Delphes}, performing a fast multipurpose detector response simulation. 66 The simulation includes a tracking system, embedded into a magnetic field, calorimeters and a muon system, and possible very forward detectors arranged along the beamline. 45 46 This paper presents a new \texttt{C++} framework, \textit{Delphes}, performing a 47 fast multipurpose detector response simulation. 48 The simulation includes a tracking system, embedded into a magnetic field, 49 calorimeters and a muon system, and possible very forward detectors arranged 50 along the beamline. 67 51 The framework is interfaced to standard file formats (e.g.\ Les Houches Event File or \texttt{HepMC}) and outputs observables such as isolated leptons, missing transverse energy and collection of jets which can be used for dedicated analyses. 68 52 The simulation of the detector response takes into account the effect of magnetic field, the granularity of the calorimeters and subdetector resolutions. … … 72 56 73 57 \textit{Preprint:} \texttt{CP3-09-01}, \texttt{arXiv:0903.2225 [hep-ph]}\\ \\ 74 %\includegraphics[scale=0.8]{DELPHESLogoSml}\\75 58 \includegraphics[scale=0.8]{fig0}\\ 76 59 {\bf PROGRAM SUMMARY}\\ … … 80 63 {\em Current version:} 1.8 \\ 81 64 {\em Journal Reference:} \\ 82 %Leave blank, supplied by Elsevier.83 65 {\em Catalogue identifier:} \\ 84 %Leave blank, supplied by Elsevier.85 %{\em Licensing provisions:} \\86 %enter "none" if CPC non-profit use license is sufficient.87 66 {\em Distribution format:} tar.gz \\ 88 67 {\em Programming language:} C++ \\ … … 128 107 \section{Introduction} 129 108 130 Multipurpose detectors at high energy colliders are very complex systems. Their simulation is in general performed by means of the GEANT~\citep{bib:geant} package and final observables used for analyses usually require sophisticated reconstruction algorithms. 131 132 133 This complexity is handled by large collaborations, and data and the expertise on reconstruction and simulation software are only available to their members. Precise data analyses require a full detector simulation, including transport of the primary and secondary particles through the detector material accounting for the various detector inefficiencies, the dead material, the imperfections and the geometrical details. 134 %\textcolor{blue}{Moreover, control of the detector calibration and alignment are crucial}. 135 Such simulation is very complicated, technical and requires a large \texttt{CPU} power. On the other hand, phenomenological studies, looking for the observability of given signals, may require only fast but realistic estimates of the expected signal signatures and their associated backgrounds. 136 137 A new framework, called \textit{Delphes}~\citep{bib:delphes}, is introduced here, for the fast simulation of a general-purpose collider experiment. 138 Using this framework, observables such as cross-sections and efficiencies after event selection can be estimated for specific reactions. 139 Starting from the output of event generators, the simulation of the detector response takes into account the subdetector resolutions, by smearing the kinematics of final-state particles (i.e. those considered as stable by the event generator 140 \footnote{In the current \textit{Delphes} version, particles other than electrons ($e^\pm$), photons ($\gamma$), muons ($\mu^\pm$), neutrinos ($\nu_e$, $\nu_\mu$ and $\nu_\tau$) and neutralinos are simulated as hadrons for their interactions with the calorimeters. The simulation of stable particles beyond the Standard Model should therefore be handled with care~\citep{qr:invisibleparticles}.}). 141 % Tracks of charged particles and deposits of energy in calorimetric cells (or \textit{calotowers}) are then created. These two types of quantities are used for the reconstruction of jets and the isolation of leptons. 142 143 \textit{Delphes} includes the most crucial experimental features, such as (Fig.~\ref{fig:FlowChart}): 109 Multipurpose detectors at high energy colliders are very complex systems. 110 Precise data analyses require a full detector simulation, including transport of 111 the primary and secondary particles through the detector material accounting for 112 the various detector inefficiencies, the dead material, the imperfections and 113 the geometrical details. Their simulation is in general performed by means of 114 the GEANT~\citep{bib:geant} package and final observables used for analyses 115 usually require sophisticated reconstruction algorithms. 116 117 118 This complexity can only be handled by large collaborations. Such simulation is 119 very complicated, technical and requires a large \texttt{CPU} power. 120 Phenomenological studies, looking for the observability of given signals, 121 require in general only fast but realistic estimates of the expected signal 122 signatures and their associated backgrounds. 123 124 In this context, a new framework, called \textit{Delphes}~\citep{bib:delphes}, 125 has been developped, for a fast simulation of a general-purpose collider 126 experiment. 127 Using this framework, observables such as cross-sections and efficiencies after 128 event selection can be estimated for specific reactions. 129 Starting from the output of event generators, the simulation of the detector 130 response takes into account the subdetector resolutions, by smearing the 131 kinematics of final-state particles (i.e. those considered as stable by the 132 event generator 133 \footnote{In the current \textit{Delphes} version, particles other than 134 electrons ($e^\pm$), photons ($\gamma$), muons ($\mu^\pm$), neutrinos ($\nu_e$, 135 $\nu_\mu$ and $\nu_\tau$) and neutralinos are simulated as hadrons for their 136 interactions with the calorimeters. The simulation of stable particles beyond 137 the Standard Model should therefore be handled with 138 care~\citep{qr:invisibleparticles}.}). 139 140 141 \textit{Delphes} includes the most crucial experimental features, such as 142 (Fig.~\ref{fig:FlowChart}): 144 143 \begin{enumerate} 145 144 \item the geometry of both central and forward detectors, 146 145 \item the effect of magnetic field on tracks, 147 \item the reconstruction of photons, leptons, jets, $b$-jets, $\tau$-jets and missing transverse energy, 146 \item the reconstruction of photons, leptons, jets, $b$-jets, $\tau$-jets and 147 missing transverse energy, 148 148 \item a lepton isolation, 149 149 \item a trigger emulation, … … 155 155 %\includegraphics[scale=0.78]{FlowDELPHES} 156 156 \includegraphics[scale=0.78]{fig1} 157 \caption{Flow chart describing the principles behind \textit{Delphes}. Event files coming from external Monte Carlo generators are read by a converter stage (top). 158 The kinematics variables of the final-state particles are then smeared according to the tunable subdetector resolutions. 159 Tracks are reconstructed in a simulated solenoidal magnetic field and calorimetric cells sample the energy deposits. Based on these low-level objects, dedicated algorithms are applied for particle identification, isolation and reconstruction. 160 The transport of very forward particles to the near-beam detectors is also simulated. 161 Finally, an output file is written, including generator-level and analysis-object data. 162 If requested, a fully parametrisable trigger can be emulated. Optionally, the geometry and visualisation files for the 3D event display can also be produced. 163 All user parameters are set in the \textit{Detector/Smearing Card} and the \textit{Trigger Card}. } 157 \caption{Flow chart describing the principles behind \textit{Delphes}. Event 158 files coming from external Monte Carlo generators are read by a converter stage 159 (top). 160 The kinematics variables of the final-state particles are then smeared 161 according to the tunable subdetector resolutions. 162 Tracks are reconstructed in a simulated solenoidal magnetic field and 163 calorimetric cells sample the energy deposits. Based on these low-level objects, 164 dedicated algorithms are applied for particle identification, isolation and 165 reconstruction. 166 The transport of very forward particles to the near-beam detectors is also 167 simulated. 168 Finally, an output file is written, including generator-level and 169 analysis-object data. 170 If requested, a fully parametrisable trigger can be emulated. Optionally, the 171 geometry and visualisation files for the 3D event display can also be produced. 172 All user parameters are set in the \textit{Detector/Smearing Card} and the 173 \textit{Trigger Card}. } 164 174 \label{fig:FlowChart} 165 175 \end{center} 166 176 \end{figure*} 167 177 168 Although \textit{Delphes} yields much realistic results than a simple ``parton-level" analysis, it has 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. 169 170 Several common datafile formats can be used as input in \textit{Delphes} \citep{qr:inputformat}, 171 %\footnote{\texttt{[code] }See the \texttt{HEPEVTConverter}, \texttt{HepMCConverter}, \texttt{LHEFConverter} and \texttt{STDHEPConverter} classes.}. 172 in order to process events from many different generators. 173 % The standard Monte Carlo event structures \texttt{StdHEP}~\citep{bib:stdhep} and \texttt{HepMC}~\citep{bib:hepmc} can be used as an input. Besides, \textit{Delphes} can also provide detector response for events read in ``Les Houches Event Format'' (\textsc{LHEF}~\citep{bib:lhe}) and \texttt{*.root} files obtained from \texttt{*.hbook} using the \texttt{h2root} utility from the \textsc{ROOT} framework~\citep{bib:Root}. 174 %Afterwards, \textit{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. 175 \textit{Delphes} creates output data in a ROOT ntuple \citep{bib:Root}. 176 This output contains a copy of the generator-level data, the analysis data objects after reconstruction, and possibly the results of the trigger emulation \citep{qr:outputformat}. 177 In option 178 %\footnote{\texttt{[code]} See the \texttt{FLAG\_LHCO} variable in the detector datacard. This text file format is shortly described in the user manual.}, 179 \textit{Delphes} can produce a reduced output file in \texttt{*.lhco} text format, which is limited to the list of the reconstructed high-level objects in the final states~\citep{qr:lhco}. 178 Although \textit{Delphes} yields much realistic results than a simple 179 ``parton-level" analysis, it has some limitations. Detector geometry is 180 idealised, being uniform, symmetric around the beam axis, and having no cracks 181 nor dead material. Secondary interactions, multiple scatterings, photon 182 conversion and bremsstrahlung are also neglected. 183 184 Several common datafile formats can be used as input in \textit{Delphes} 185 \citep{qr:inputformat}, in order to process events from many different 186 generators. \textit{Delphes} creates output data in a ROOT ntuple 187 \citep{bib:Root}. This output contains a copy of the generator-level data, the 188 analysis data objects after reconstruction, and possibly the results of the 189 trigger emulation \citep{qr:outputformat}. 190 In option \textit{Delphes} can produce a reduced output file in \texttt{*.lhco} 191 text format, which is limited to the list of the reconstructed high-level 192 objects in the final states~\citep{qr:lhco}. 180 193 181 194 … … 183 196 \section{Simulation of the detector response} 184 197 185 The overall layout of the multipurpose detector simulated by \textit{Delphes} is shown in Fig.~\ref{fig:GenDet3}. 186 It consists in a central tracking system (\textsc{TRACKER}) surrounded by an electromagnetic and a hadron calorimeters (\textsc{ECAL} and \textsc{HCAL}, each with a central region and two endcaps) and two forward calorimeters (\textsc{FCAL}). 187 % ensure a larger geometric coverage for the measurement of the missing transverse energy. 188 Finally, a muon system (\textsc{MUON}) encloses the central detector volume. 189 190 A detector card \citep{qr:detectorcard} allows a large spectrum of running conditions by modifying basic detector parameters, including calorimeter and tracking coverage and resolution, thresholds or jet algorithm parameters. 191 Even if \textit{Delphes} has been developped for the simulation of general-purpose detectors at the \textsc{LHC} (namely, \textsc{CMS} and \textsc{ATLAS}), this input parameter file interfaces a flexible parametrisation for other cases, e.g.\ at future linear colliders~\citep{qr:datacards}. 192 If no detector card is provided, predefined values based on ``typical'' \textsc{CMS} acceptances and resolutions are used. 193 %\footnote{\texttt{[code] }Detector and trigger cards for the \textsc{ATLAS} and \textsc{CMS} experiments are also provided in \texttt{data/} directory.}. 194 The geometrical coverage of the various subsystems used in the default configuration are summarised in Tab.~\ref{tab:defEta}. 195 The detector is assumed to be strictly symmetric around the beam axis. 198 The overall layout of the multipurpose detector simulated by \textit{Delphes} 199 is shown in Fig.~\ref{fig:GenDet3}. It consists in a central tracking system 200 (\textsc{TRACKER}) surrounded by an electromagnetic and a hadron calorimeters 201 (\textsc{ECAL} and \textsc{HCAL}, each with a central region and two endcaps) 202 and two forward calorimeters (\textsc{FCAL}). Finally, a muon system 203 (\textsc{MUON}) encloses the central detector volume. 204 205 A detector card \citep{qr:detectorcard} allows a large spectrum of running 206 conditions by modifying basic detector parameters, including calorimeter and 207 tracking coverage and resolution, thresholds or jet algorithm parameters. 208 Even if \textit{Delphes} has been developped for the simulation of 209 general-purpose detectors at the \textsc{LHC} (namely, \textsc{CMS} and 210 \textsc{ATLAS}), this input parameter file interfaces a flexible parametrisation 211 for other cases, e.g.\ at future linear colliders~\citep{qr:datacards}. 212 If no detector card is provided, predefined values based on ``typical'' 213 \textsc{CMS} acceptances and resolutions are used. The geometrical coverage of 214 the various subsystems used in the default configuration are summarised in 215 Tab.~\ref{tab:defEta}. The detector is assumed to be strictly symmetric around 216 the beam axis. 196 217 197 218 \begin{table}[t] 198 % \begin{table*}[t]199 219 \begin{center} 200 220 \caption{Default extension in pseudorapidity $\eta$ of the different subdetectors. 201 221 Full azimuthal ($\phi$) acceptance is assumed. 202 222 \vspace{0.5cm}} 203 % \begin{tabular}{llcc}204 % \hline205 % Subdetector & & $\eta$ & $\phi$ \\206 % \textsc{TRACKER} & {\verb CEN_max_tracker } & $[-2.5; 2.5]$ & $[-\pi ; \pi]$\\207 % \textsc{ECAL}, \textsc{HCAL} & {\verb CEN_max_calo_cen }& $[-1.7 ; 1.7]$ & $[-\pi ; \pi]$\\208 % \textsc{ECAL}, \textsc{HCAL} endcaps & {\verb CEN_max_calo_ec }& $[-3 ; -1.7] \& [1.7 ; 3]$ & $[-\pi ; \pi]$\\209 % \textsc{FCAL} & {\verb CEN_max_calo_fwd } & $[-5 ; -3]$ \& $[3 ;5]$ & $[-\pi ; \pi]$\\210 % \textsc{MUON} & {\verb CEN_max_mu } & $[-2.4 ; 2.4]$ & $[-\pi ; \pi]$\\ \hline211 % \end{tabular}212 223 \begin{tabular}{lcc} 213 224 \hline … … 221 232 \label{tab:defEta} 222 233 \end{center} 223 % \end{table*}224 234 \end{table} 225 235 … … 229 239 \includegraphics[width=\columnwidth]{fig2} 230 240 \caption{ 231 Profile of layout of the generic detector geometry assumed in \textit{Delphes}. The innermost layer, close to the interaction point, is a central tracking system (pink). 232 It is surrounded by a central calorimeter volume (green) with both electromagnetic and hadronic sections. 233 The outer layer of the central system (red) is muon system. In addition, two end-cap calorimeters (blue) extend the pseudorapidity coverage of the central detector. 234 % The detector parameters are defined in the user-configuration card. The extension of the various subdetectors, as defined in Tab.~\ref{tab:defEta}, are clearly visible. The detector is assumed to be strictly symmetric around the beam axis (black line). 241 Profile of layout of the generic detector geometry assumed in \textit{Delphes}. 242 The innermost layer, close to the interaction point, is a central tracking 243 system (pink). It is surrounded by a central calorimeter volume (green) with 244 both electromagnetic and hadronic sections. The outer layer of the central 245 system (red) is muon system. In addition, two end-cap calorimeters (blue) extend 246 the pseudorapidity coverage of the central detector. 235 247 Additional forward detectors are not depicted. 236 248 } … … 241 253 242 254 \subsection{Magnetic field} 243 In addition to the subdetectors, the effects of a solenoidal magnetic field are simulated for the charged particles~\citep{qr:magneticfield} 244 %\footnote{\texttt{[code] }See the \texttt{TrackPropagation} class.} 245 . This affects the position at which charged particles enter the calorimeters and their corresponding tracks. The field extension is limited to the tracker volume and is in particular not applied for muon chambers. Howerver, this is not a limiting factor as the resolution applied for muon reconstruction is the one expected by the experiment, which consequently includes the effects of the magnetic field within the muon system. 255 In addition to the subdetectors, the effects of a solenoidal magnetic field are 256 simulated for the charged particles~\citep{qr:magneticfield}. This affects the 257 position at which charged particles enter the calorimeters and their 258 corresponding tracks. The field extension is limited to the tracker volume and 259 is in particular not applied for muon chambers. Howerver, this is not a limiting 260 factor as the resolution applied for muon reconstruction is the one expected by 261 the experiment, which consequently includes the effects of the magnetic field 262 within the muon system. 246 263 247 264 248 265 \subsection{Tracks reconstruction} 249 266 Every stable charged particle with a transverse momentum above some threshold and lying inside the detector volume covered by the tracker provides a track. 250 By default, a track is assumed to be reconstructed with $90\%$ probability 251 %\footnote{\texttt{[code]} The reconstruction efficiency is defined in the detector datacard by the \texttt{TRACKING\_EFF} term.} 252 if its transverse momentum $p_T$ is higher than $0.9~\textrm{GeV}/c$ and if its pseudorapidity 253 $|\eta| \leq 2.5$~\citep{qr:tracks}. No smearing is currentlyapplied on tracks.267 By default, a track is assumed to be reconstructed with $90\%$ probability if 268 its transverse momentum $p_T$ is higher than $0.9~\textrm{GeV}/c$ and if its 269 pseudorapidity $|\eta| \leq 2.5$~\citep{qr:tracks}. No smearing is currently 270 applied on tracks. 254 271 255 272 256 273 \subsection{Calorimetric cells} 257 274 258 The response of the calorimeters to energy deposits of incoming particles depends on their segmentation and resolution, as well as on the nature of the particles themselves. In CMS and ATLAS detectors, for instance, the calorimeter characteristics are not identical in every direction, with typically finer resolution and granularity in the central regions~\citep{bib:cmsjetresolution,bib:ATLASresolution}. It is thus very important to compute the exact coordinates of the entry point of the particles into the calorimeters, via the magnetic field calculations. 259 260 The smallest unit for geometrical sampling of the calorimeters is a \textit{cell}; it segments the $(\eta,\phi)$ plane for the energy measurement. No longitudinal segmentation is available in the simulated calorimeters. \textit{Delphes} assumes that ECAL and HCAL have the same segmentations and that the detector is symmetric in $\phi$ and with respect to the $\eta=0$ plane~\citep{qr:calorimetriccells}. 261 Fig.~\ref{fig:calosegmentation} illustrates the default calorimeter segmentation. 275 The response of the calorimeters to energy deposits of incoming particles 276 depends on their segmentation and resolution, as well as on the nature of the 277 particles themselves. In CMS and ATLAS detectors, for instance, the calorimeter 278 characteristics are not identical in every direction, with typically finer 279 resolution and granularity in the central 280 regions~\citep{bib:cmsjetresolution,bib:ATLASresolution}. It is thus very 281 important to compute the exact coordinates of the entry point of the particles 282 into the calorimeters, via the magnetic field calculations. 283 284 The smallest unit for geometrical sampling of the calorimeters is a 285 \textit{cell}; it segments the $(\eta,\phi)$ plane for the energy measurement. 286 No longitudinal segmentation is available in the simulated 287 calorimeters. \textit{Delphes} assumes that ECAL and HCAL have the same 288 segmentations and that the detector is symmetric in $\phi$ and with respect to 289 the $\eta=0$ plane~\citep{qr:calorimetriccells}. 290 Fig.~\ref{fig:calosegmentation} illustrates the default calorimeter 291 segmentation. 262 292 263 293 \begin{figure}[!ht] … … 284 314 \begin{table}[!h] 285 315 \begin{center} 286 \caption{Default values for the resolution of the central and forward calorimeters (for both electromagnetic and hadronic parts). Resolution is parametrised by the \textit{stochastic} ($S$), \textit{noise} ($N$) and \textit{constant} ($C$) terms (Eq.~\ref{eq:caloresolution})~\citep{qr:resolutionterms}. 287 %The corresponding parameter name, in the detector card, is given. 316 \caption{Default values for the resolution of the central and forward 317 calorimeters (for both electromagnetic and hadronic parts). Resolution is 318 parametrised by the \textit{stochastic} ($S$), \textit{noise} ($N$) and 319 \textit{constant} ($C$) terms 320 (Eq.~\ref{eq:caloresolution})~\citep{qr:resolutionterms}. 288 321 \vspace{0.5cm}} 289 322 \begin{tabular}[!h]{lccc} 290 323 \hline 291 %\multicolumn{2}{c}{Resolution Term} & Value\\\hline292 324 & $S$ (GeV$^{1/2}$) & $N$ (GeV) & $C$ \\\hline 293 %\multicolumn{4}{l}{\textsc{ECAL}} \\294 325 ECAL & $0.05$ & $0.25$ & $0.0055$ \\ 295 %\multicolumn{4}{l}{\textsc{ECAL}, end caps} \\296 326 ECAL, end caps & $0.05$ & $0.25$ & $0.0055$ \\ 297 %\multicolumn{4}{l}{\textsc{FCAL}, electromagnetic part} \\298 327 FCAL, e.m. part & $2.084$ & $0$ & $0.107$ \\ 299 %\multicolumn{4}{l}{\textsc{HCAL}} \\300 328 HCAL & $1.5$ & $0$ & $0.05$\\ 301 %\multicolumn{4}{l}{\textsc{HCAL}, end caps} \\302 329 HCAL, end caps & $1.5$ & $0$ & $0.05$\\ 303 %\multicolumn{4}{l}{\textsc{FCAL}, hadronic part} \\304 330 FCAL, had. part & $2.7$ & $0$ & $0.13$\\ 305 331 \hline … … 310 336 311 337 312 Electrons and photons leave their energy in the electromagnetic parts of the calorimeters (\textsc{ECAL} and \textsc{FCAL}, e.m.), while charged and neutral final-state hadrons interact with the hadronic parts (\textsc{HCAL} and \textsc{FCAL}, had.). 313 Some long-living particles, such as the $K^0_s$ and $\Lambda$'s, with lifetime $c\tau$ smaller than $10~\textrm{mm}$ are considered as stable particles by the generators although they may decay before the calorimeters. The energy smearing of such particles is therefore performed using the expected fraction of the energy, determined according to their decay products, that would be deposited into the \textsc{ECAL} ($E_{\textsc{ECAL}}$) and into the \textsc{HCAL} ($E_{\textsc{HCAL}}$). Defining $F$ as the fraction of the energy leading to a \textsc{HCAL} deposit, the two energy values are given by 338 Electrons and photons leave their energy in the electromagnetic parts of the 339 calorimeters (\textsc{ECAL} and \textsc{FCAL}, e.m.), while charged and neutral 340 final-state hadrons interact with the hadronic parts (\textsc{HCAL} and 341 \textsc{FCAL}, had.). 342 Some long-living particles, such as the $K^0_s$ and $\Lambda$'s, with lifetime 343 $c\tau$ smaller than $10~\textrm{mm}$ are considered as stable particles by the 344 generators although they may decay before the calorimeters. The energy smearing 345 of such particles is therefore performed using the expected fraction of the 346 energy, determined according to their decay products, that would be deposited 347 into the \textsc{ECAL} ($E_{\textsc{ECAL}}$) and into the \textsc{HCAL} 348 ($E_{\textsc{HCAL}}$). Defining $F$ as the fraction of the energy leading to a 349 \textsc{HCAL} deposit, the two energy values are given by 314 350 \begin{equation} 315 351 \left\{ … … 320 356 \right. 321 357 \end{equation} 322 where $0 \leq F \leq 1$. The electromagnetic part is handled similarly as for electrons and photons. 323 The resulting calorimetry energy measurement given after the application of the smearing is then $E = E_{\textsc{HCAL}} + E_{\textsc{ECAL}}$. For $K_S^0$ and $\Lambda$ hadrons, the energy fraction is $F$ is assumed to be $0.7$~\citep{qr:emhadratios}.\\ 324 325 326 No sharing between neighbouring cells is implemented when particles enter a cell very close to its geometrical edge. Due to the finite segmentation, the smearing, as defined in Eq.~\ref{eq:caloresolution}, is applied directly on the accumulated electromagnetic and hadronic energies of each calorimetric cell. The calorimetric cells enter in the calculation of the missing transverse energy (\textsc{MET}), and are used as input for the jet reconstruction algorithms. 358 where $0 \leq F \leq 1$. The electromagnetic part is handled similarly as for 359 electrons and photons. The resulting calorimetry energy measurement given after 360 the application of the smearing is then $E = E_{\textsc{HCAL}} + 361 E_{\textsc{ECAL}}$. For $K_S^0$ and $\Lambda$ hadrons, the energy fraction is 362 $F$ is assumed to be $0.7$~\citep{qr:emhadratios}.\\ 363 364 365 No sharing between neighbouring cells is implemented when particles enter a 366 cell very close to its geometrical edge. Due to the finite segmentation, the 367 smearing, as defined in Eq.~\ref{eq:caloresolution}, is applied directly on the 368 accumulated electromagnetic and hadronic energies of each calorimetric cell. The 369 calorimetric cells enter in the calculation of the missing transverse energy 370 (\textsc{MET}), and are used as input for the jet reconstruction algorithms. 327 371 328 372 … … 331 375 \section{High-level object reconstruction} 332 376 333 The output file created by \textit{Delphes}~\citep{qr:analysistree} stores the final collections of particles ($e^\pm$, $\mu^\pm$, $\gamma$) and objects (light jets, $b$-jets, $\tau$-jets, $E_T^\textrm{miss}$). In addition, some detector data are added, such as tracks, calorimetric cells and hits in the very forward detectors (\textsc{ZDC}, \textsc{RP220} and \textsc{FP420}, see Sec.~\ref{sec:vfd}). While electrons, muons and photons are easily identified, other quantities are more difficult to evaluate as they rely on sophisticated algorithms (e.g. jets or missing energy). 334 335 For most of these objects, their four-momentum and related quantities are directly accessible in \textit{Delphes} output ($E$, $\vec{p}$, $p_T$, $\eta$ and $\phi$). Additional properties are available for specific objects (like the charge and the isolation status for $e^\pm$ and $\mu^\pm$, the result of application of $b$-tag for jets and time-of-flight for some detector hits). 377 The output file created by \textit{Delphes}~\citep{qr:analysistree} stores the 378 final collections of particles ($e^\pm$, $\mu^\pm$, $\gamma$) and objects (light 379 jets, $b$-jets, $\tau$-jets, $E_T^\textrm{miss}$). In addition, some detector 380 data are added, such as tracks, calorimetric cells and hits in the very forward 381 detectors (\textsc{ZDC}, \textsc{RP220} and \textsc{FP420}, see 382 Sec.~\ref{sec:vfd}). While electrons, muons and photons are easily identified, 383 other quantities are more difficult to evaluate as they rely on sophisticated 384 algorithms (e.g. jets or missing energy). 385 386 For most of these objects, their four-momentum and related quantities are 387 directly accessible in \textit{Delphes} output ($E$, $\vec{p}$, $p_T$, $\eta$ 388 and $\phi$). Additional properties are available for specific objects (like the 389 charge and the isolation status for $e^\pm$ and $\mu^\pm$, the result of 390 application of $b$-tag for jets and time-of-flight for some detector hits). 336 391 337 392 \subsection{Photon and charged lepton} 338 From here onwards, \textit{electrons} refer to both positrons ($e^+$) and electrons ($e^-$), and $\textit{charged leptons}$ refer to electrons and muons ($\mu^\pm$), leaving out the $\tau^\pm$ leptons as they decay before being detected. 339 340 The electron, muon and photon collections contains only the true final-state particles identified via the generator-data. 341 In addition, these particles must pass fiducial cuts taking into account the magnetic field effects and some additional reconstruction cuts. 342 343 Consequently, no fake candidates enter these collections. However, when needed, fake candidates can be added into the collections at the analysis level, when processing \textit{Delphes} output data. As effects like bremsstrahlung are not taken into account along the lepton propagation in the tracker, no clustering is needed for the electron reconstruction in \textit{Delphes}. 393 From here onwards, \textit{electrons} refer to both positrons ($e^+$) and 394 electrons ($e^-$), and $\textit{charged leptons}$ refer to electrons and muons 395 ($\mu^\pm$), leaving out the $\tau^\pm$ leptons as they decay before being 396 detected. 397 398 The electron, muon and photon collections contains only the true final-state 399 particles identified via the generator-data. In addition, these particles must 400 pass fiducial cuts taking into account the magnetic field effects and some 401 additional reconstruction cuts. 402 403 Consequently, no fake candidates enter these collections. However, when needed, 404 fake candidates can be added into the collections at the analysis level, when 405 processing \textit{Delphes} output data. As effects like bremsstrahlung are not 406 taken into account along the lepton propagation in the tracker, no clustering is 407 needed for the electron reconstruction in \textit{Delphes}. 344 408 345 409 \subsubsection*{Electrons and photons} 346 Real electron ($e^\pm$) and photon candidates are associated to the final-state collections if they fall into the acceptance of the tracking system and have a transverse momentum above some threshold (default: $p_T > 10~\textrm{GeV}/c$). 347 Assuming a good measurement of the track parameters in the real experiment, the electron energy can be reasonably recovered. 348 \textit{Delphes} assumes a perfect algorithm for clustering and Brehmstrahlung recovery. Electron energy is smeared according to the resolution of the calorimetric cell where it points to, but independently from any other deposited energy is this cell. 410 Real electron ($e^\pm$) and photon candidates are associated to the final-state 411 collections if they fall into the acceptance of the tracking system and have a 412 transverse momentum above some threshold (default: $p_T > 10~\textrm{GeV}/c$). 413 Assuming a good measurement of the track parameters in the real experiment, the 414 electron energy can be reasonably recovered. \textit{Delphes} assumes a perfect 415 algorithm for clustering and Brehmstrahlung recovery. Electron energy is smeared 416 according to the resolution of the calorimetric cell where it points to, but 417 independently from any other deposited energy is this cell. 349 418 Electrons and photons may create a candidate in the jet collection. 350 419 351 420 \subsubsection*{Muons} 352 Generator-level muons entering the muon detector acceptance (default: $-2.4 \leq \eta \leq 2.4$) and overpassing some threshold (default : $p_T > 10~\textrm{GeV}/c$) are considered as good candidates for analyses. 353 The application of the detector resolution on the muon momentum depends on a Gaussian smearing of the $p_T$~\citep{qr:muonsmearing}. 354 %\footnote{\texttt{[code]} See the \texttt{SmearMuon} method.}. 355 Neither $\eta$ nor $\phi$ variables are modified beyond the calorimeters: no additional magnetic field is applied. Multiple scattering is neglected. This implies that low energy muons have in \textit{Delphes} a better resolution than in a real detector. At last, the particles which might leak out of the calorimeters into the muon systems (\textit{punch-through}) are not considered as muon candidates in \textit{Delphes}. 421 Generator-level muons entering the muon detector acceptance (default: $-2.4 422 \leq \eta \leq 2.4$) and overpassing some threshold (default : $p_T > 423 10~\textrm{GeV}/c$) are considered as good candidates for analyses. 424 The application of the detector resolution on the muon momentum depends on a 425 Gaussian smearing of the $p_T$~\citep{qr:muonsmearing}. 426 Neither $\eta$ nor $\phi$ variables are modified beyond the calorimeters: no 427 additional magnetic field is applied. Multiple scattering is neglected. This 428 implies that low energy muons have in \textit{Delphes} a better resolution than 429 in a real detector. At last, the particles which might leak out of the 430 calorimeters into the muon systems (\textit{punch-through}) are not considered 431 as muon candidates in \textit{Delphes}. 356 432 357 433 \subsubsection*{Charged lepton isolation} 358 434 \label{sec:isolation} 359 435 360 To improve the quality of the contents of the charged lepton collections, isolation criteria can be applied. This requires that electron or muon candidates are isolated in the detector from any other particle, within a small cone. In \textit{Delphes}, charged lepton isolation demands that there is no other charged particle with $p_T>2~\textrm{GeV}/c$ within a cone of $\Delta R = \sqrt{\Delta \eta^2 + \Delta \phi^2} <0.5$ centered on the cell associated to the charged lepton $\ell$, obviously taking the magnetic field into account. 436 To improve the quality of the contents of the charged lepton collections, 437 isolation criteria can be applied. This requires that electron or muon 438 candidates are isolated in the detector from any other particle, within a small 439 cone. In \textit{Delphes}, charged lepton isolation demands that there is no 440 other charged particle with $p_T>2~\textrm{GeV}/c$ within a cone of $\Delta R = 441 \sqrt{\Delta \eta^2 + \Delta \phi^2} <0.5$ centered on the cell associated to 442 the charged lepton $\ell$, obviously taking the magnetic field into account. 361 443 362 444 The result (i.e.\ \textit{isolated} or \textit{not}) is added to the charged lepton measured properties. 363 445 In addition, the sum $P_T$ of the transverse momenta of all tracks but the lepton one within the isolation cone is 364 446 provided~\citep{qr:isolflag}: 365 %\footnote{\texttt{[code] }See the \texttt{IsolFlag} and \texttt{IsolPt} values in the \texttt{Electron} or \texttt{Muon} collections in the \texttt{Analysis} tree, as well as the \texttt{ISOL\_PT} and \texttt{ISOL\_Cone} variables in the detector card.}366 447 $$ P_T = \sum_{i \neq \ell}^\textrm{tracks} p_T(i)$$ 367 448 368 No calorimetric isolation is applied, but the charged lepton collections contain also the ratio $\rho_\ell$ between (1) the sum of the transverse energies in all calorimetric cells in a $N \times N$ grid around the lepton, and (2) the lepton transverse momentum~\citep{qr:caloisolation}: 369 %\footnote{\texttt{[code] }Calorimetric isolation parameters in the detector card are \texttt{ISOL\_Calo\_ET} and \texttt{ISOL\_Calo\_Grid}.}: 370 $$ \rho_\ell = \frac{\Sigma_i E_T(i)}{p_T(\ell)}~,~ i\textrm{ in }N \times N \textrm { grid centred on }\ell.$$ 371 372 373 % \subsubsection*{Forward neutrals} 374 % 375 % The zero degree calorimeter hits correspond to neutral particles with a lifetime long enough to reach these detectors (default: $c \tau \geq 140~\textrm{m}$) and very large pseudorapidities (default: $|\eta|>8.3$). In current versions of \textit{Delphes}, only photons and neutrons are considered. Photons are identified thanks to the electromagnetic section of the calorimeter, and if their energy overpasses a given threshold (def. $20$~GeV). Similarly, neutrons are reconstructed according to the resolution of the hadronic section, if their energy exceeds a threshold (def. $50$~GeV)~\citep{qr:fwdneutrals}. 376 % %\footnote{\texttt{[code]} These thresholds are defined by the \texttt{ZDC\_gamma\_E} and \texttt{ZDC\_n\_E} variables in the detector card.} (def. $50$~GeV). 377 449 No calorimetric isolation is applied, but the charged lepton collections 450 contain also the ratio $\rho_\ell$ between (1) the sum of the transverse 451 energies in all calorimetric cells in a $N \times N$ grid around the lepton, and 452 (2) the lepton transverse momentum~\citep{qr:caloisolation}: 453 $$ \rho_\ell = \frac{\Sigma_i E_T(i)}{p_T(\ell)}~,~ i\textrm{ in }N \times N 454 \textrm { grid centred on }\ell.$$ 378 455 379 456 380 457 \subsection{Jet reconstruction} 381 458 382 A realistic analysis requires a correct treatment of partons which have hadronised. Therefore, the most widely currently used jet algorithms have been integrated into the \textit{Delphes} framework using the FastJet tools\footnote{A more detailed description of the jet algorithms is given in the User Manual, in appendix.}. 383 Six different jet reconstruction schemes are available~\citep{bib:FASTJET,qr:jetalgo}. 384 %\footnote{\texttt{[code] }The choice is done by allocating the \texttt{JET\_jetalgo } input parameter in the detector card.}. 385 % The first three belong to the cone algorithm class while the last three are using a sequential recombination scheme. 386 For all of them, the calorimetric cells are used as inputs. Jet algorithms differ in their sensitivity to soft particles or collinear splittings, and in their computing speed performances. 459 A realistic analysis requires a correct treatment of partons which have 460 hadronised. Therefore, the most widely currently used jet algorithms have been 461 integrated into the \textit{Delphes} framework using the FastJet 462 tools\footnote{A more detailed description of the jet algorithms is given in the 463 User Manual, in appendix.}. Six different jet reconstruction schemes are 464 available~\citep{bib:FASTJET,qr:jetalgo}. For all of them, the calorimetric 465 cells are used as inputs. Jet algorithms differ in their sensitivity to soft 466 particles or collinear splittings, and in their computing speed performances. 387 467 388 468 \subsubsection*{Cone algorithms} … … 390 470 \begin{enumerate} 391 471 392 \item {\it CDF Jet Clusters}~\citep{bib:jetclu}: Cone algorithm forming jets by combining cells lying within a circle (default radius $\Delta R=0.7$) in the $(\eta$, $\phi)$ space. Jets are seeded by all cells with 393 transverse energy $E_T$ above a given threshold (default: $E_T > 1~\textrm{GeV}$)~\citep{qr:jetparams}. 394 395 \item {\it CDF MidPoint}~\citep{bib:midpoint}: Cone algorithm with additional ``midpoints'' (energy barycentres) in the list of seeds. 396 397 \item {\it Seedless Infrared Safe Cone}~\citep{bib:SIScone}: The \textsc{SISC}one algorithm is simultaneously insensitive to additional soft particles and collinear splittings. 472 \item {\it CDF Jet Clusters}~\citep{bib:jetclu}: Cone algorithm forming jets by 473 combining cells lying within a circle (default radius $\Delta R=0.7$) in the 474 $(\eta$, $\phi)$ space. Jets are seeded by all cells with transverse energy 475 $E_T$ above a given threshold (default: $E_T > 476 1~\textrm{GeV}$)~\citep{qr:jetparams}. 477 478 \item {\it CDF MidPoint}~\citep{bib:midpoint}: Cone algorithm with additional 479 ``midpoints'' (energy barycentres) in the list of seeds. 480 481 \item {\it Seedless Infrared Safe Cone}~\citep{bib:SIScone}: The 482 \textsc{SISC}one algorithm is simultaneously insensitive to additional soft 483 particles and collinear splittings. 398 484 \end{enumerate} 399 485 400 486 \subsubsection*{Recombination algorithms} 401 487 402 The next three jet algorithms rely on recombination schemes where calorimeter cell pairs are successively merged: 403 404 % Two such variables are defined: the distance $d_{ij}$ between each pair of cells $(i,j)$, and a variable $d_{iB}$ (\textit{beam distance}) depending on the transverse momentum of the cell $i$. 405 406 % The jet reconstruction algorithm browses the calorimetric cell list. It starts by finding the minimum value $d_\textrm{min}$ of all the distances $d_{ij}$ and $d_{iB}$. If $d_\textrm{min}$ is a $d_{ij}$, the cells $i$ and $j$ are merged into a single cell with a four-momentum $p^\mu = p^\mu (i) + p^\mu (j)$ (\textit{E-scheme recombination}). If $d_\textrm{min}$ is a $d_{iB}$, the cell is declared as a final jet and is removed from the input list. This procedure is repeated until no cells are left in the input list. Further information on these jet algorithms is given here below, using $k_{ti}$, $y_{i}$ and $\phi_i$ as the transverse momentum, rapidity and azimuth of calorimetric cell $i$ and $\Delta R_{ij}= \sqrt{(y_i-y_j)^2+(\phi_i-\phi_j)^2}$ as the jet-radius parameter: 488 The next three jet algorithms rely on recombination schemes where calorimeter 489 cell pairs are successively merged: 407 490 408 491 \begin{enumerate}[start=4] 409 410 492 \item {\it Longitudinally invariant $k_t$ jet}~\citep{bib:ktjet}, 411 % \begin{equation}412 % \begin{array}{l}413 % d_{ij} = \min(k_{ti}^2,k_{tj}^2)\Delta R_{ij}^2/R^2 \\414 % d_{iB}=k_{ti}^2 \\415 % \end{array}416 % \end{equation}417 418 493 \item {\it Cambridge/Aachen jet}~\citep{bib:aachen}, 419 % \begin{equation} 420 % \begin{array}{l} 421 % d_{ij} = \Delta R_{ij}^2/R^2\\ 422 % d_{iB}=1 \\ 423 % \end{array} 424 % \end{equation} 425 426 \item {\it Anti $k_t$ jet}~\citep{bib:antikt}, where hard jets are exactly circular in the $(y,\phi)$ plane. 427 % \begin{equation} 428 % \begin{array}{l} 429 % d_{ij} = \min(1/k_{ti}^2,1/k_{tj}^2)\Delta R_{ij}^2/R^2 \\ 430 % d_{iB}=1/k_{ti}^2 \\ 431 % \end{array} 432 % \end{equation} 494 \item {\it Anti $k_t$ jet}~\citep{bib:antikt}, where hard jets are exactly 495 circular in the $(y,\phi)$ plane. 433 496 \end{enumerate} 434 497 435 The recombination algorithms are safe with respect to soft radiations (\textit{infrared}) and collinear splittings. Their implementations are similar except for the definition of the \textit{distances} used during the merging procedure. 436 437 By default, reconstruction uses the CDF cone algorithm. 438 Jets are stored if their transverse energy is higher than $20~\textrm{GeV}$~\citep{qr:ptcutjet}. 498 The recombination algorithms are safe with respect to soft radiations 499 (\textit{infrared}) and collinear splittings. Their implementations are similar 500 except for the definition of the \textit{distances} used during the merging 501 procedure. 502 503 By default, reconstruction uses the CDF cone algorithm. Jets are stored if their 504 transverse energy is higher than $20~\textrm{GeV}$~\citep{qr:ptcutjet}. 439 505 440 506 441 507 \subsubsection*{Energy flow} 442 508 443 In jets, several particle can leave their energy into a given calorimetric cell, which broadens the jet energy resolution. However, the energy of charged particles associated to jets can be deduced from their reconstructed track, thus providing a way to identify some of the components of cells with multiple hits. When the \textit{energy flow} is switched on in \textit{Delphes} 444 %\footnote{\texttt{[code]} Set \texttt{JET\_Eflow} to $1$ or $0$ in the detector card in order to switch on or off the energy flow for jet reconstruction.} 445 , the energy of tracks pointing to calorimetric cells is subtracted and smeared separately, before running the chosen jet reconstruction algorithm. This option allows a better jet $E$ reconstruction~\citep{qr:energyflow}. 509 In jets, several particle can leave their energy into a given calorimetric cell, 510 which broadens the jet energy resolution. However, the energy of charged 511 particles associated to jets can be deduced from their reconstructed track, thus 512 providing a way to identify some of the components of cells with multiple hits. 513 When the \textit{energy flow} is switched on in \textit{Delphes}, the energy of 514 tracks pointing to calorimetric cells is subtracted and smeared separately, 515 before running the chosen jet reconstruction algorithm. This option allows a 516 better jet $E$ reconstruction~\citep{qr:energyflow}. 446 517 447 518 \subsection{$b$-tagging} 448 519 \label{btagging} 449 520 450 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. By default, a $b$-tagging efficiency of $40\%$ is assumed if the jet has a parent $b$ quark. For $c$-jets and light jets (i.e.\ originating in $u$, $d$, $s$ quarks or in gluons), a fake $b$-tagging efficiency of $10 \%$ and $1 \%$ respectively is assumed~\citep{qr:btag}. 451 %\footnote{\texttt{[code] }Corresponding to the \texttt{BTAG\_b}, \texttt{BTAG\_mistag\_c} and \texttt{BTAG\_mistag\_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 mistagging a light jet ($u$,$d$,$s$,$g$) as a $b$-jet.}. 452 The (mis)tagging relies on the true parton identity of the most energetic parton within a cone around the $(\eta,\phi)$ region, with a radius equal to the one used to reconstruct the jet (default: $\Delta R$ of $0.7$). In current version of \textit{Delphes}, the displacement of secondary vertices is not simulated. 521 A jet is tagged as $b$-jets if its direction lies in the acceptance of the 522 tracker and if it is associated to a parent $b$-quark. By default, a $b$-tagging 523 efficiency of $40\%$ is assumed if the jet has a parent $b$ quark. For $c$-jets 524 and light jets (i.e.\ originating in $u$, $d$, $s$ quarks or in gluons), a fake 525 $b$-tagging efficiency of $10 \%$ and $1 \%$ respectively is 526 assumed~\citep{qr:btag}. The (mis)tagging relies on the identity of 527 the most energetic parton within a cone around the jet axis, with a 528 radius equal to the one used to reconstruct the jet (default: $\Delta R$ of 529 $0.7$). In current version of \textit{Delphes}, the displacement of secondary 530 vertices is not simulated. 453 531 454 532 \subsection{\texorpdfstring{$\tau$}{\texttau} identification} 455 533 456 Jets originating from $\tau$-decays are identified using a procedure consistent with the one applied in a full detector simulation~\citep{bib:cmsjetresolution}. 457 The tagging relies on two properties of the $\tau$ lepton. First, $77\%$ of the $\tau$ hadronic decays contain only one charged hadron associated to a few neutrals (Tab.~\ref{tab:taudecay}). Secondly, the particles arisen from the $\tau$ lepton produce narrow jets in the calorimeter (this is defined as the jet \textit{collimation}). 534 Jets originating from $\tau$-decays are identified using a procedure consistent 535 with the one applied in a full detector simulation~\citep{bib:cmsjetresolution}. 536 The tagging relies on two properties of the $\tau$ lepton. First, $77\%$ of the 537 $\tau$ hadronic decays contain only one charged hadron associated to a few 538 neutrals (Tab.~\ref{tab:taudecay}). Secondly, the particles arisen from the 539 $\tau$ lepton produce narrow jets in the calorimeter (this is defined as the jet 540 \textit{collimation}). 458 541 459 542 460 543 \begin{table}[!h] 461 544 \begin{center} 462 \caption{ Branching ratios for $\tau^-$ lepton~\citep{bib:pdg}. $h^\pm$ and $h^0$ refer to charged and neutral hadrons, respectively. $n \geq 0$ and $m \geq 0$ are integers. 545 \caption{ Branching ratios for $\tau^-$ lepton~\citep{bib:pdg}. $h^\pm$ and 546 $h^0$ refer to charged and neutral hadrons, respectively. $n \geq 0$ and $m \geq 547 0$ are integers. 463 548 \vspace{0.5cm} } 464 549 \begin{tabular}[!h]{lll} … … 491 576 \caption{Default values for parameters used in $\tau$-jet reconstruction algorithm. Electromagnetic collimation requirements involve the inner \textit{small} cone radius $R^\textrm{em}$, the minimum transverse energy for calorimetric cells $E_T^\textrm{cell}$ and the collimation factor $C_\tau$. Tracking isolation constrains the number of tracks with a significant transverse momentum $p_T^\textrm{tracks}$ in a cone of radius $R^\textrm{tracks}$. Finally, the $\tau$-jet collection is purified by the application of a cut on the $p_T$ of $\tau$-jet candidates~\citep{qr:taujets}. 492 577 \vspace{0.5cm} } 493 % \begin{tabular}[!h]{lll}494 % \hline495 % Parameter & Card flag & Value\\\hline496 % \multicolumn{3}{l}{\textbf{Electromagnetic collimation}} \\497 % $R^\textrm{em}$ & \texttt{TAU\_energy\_scone } & $0.15$\\498 % min $E_{T}^\textrm{tower}$ & {\verb JET_M_seed } & $1.0$~GeV\\499 % $C_{\tau}$ & \texttt{TAU\_energy\_frac} & $0.95$\\500 % \multicolumn{3}{l}{\textbf{Tracking isolation}} \\501 % $R^\textrm{tracks}$ & \texttt{TAU\_track\_scone} & $0.4$\\502 % min $p_T^\textrm{tracks}$ & \texttt{PTAU\_track\_pt } & $2$ GeV$/c$\\503 % \multicolumn{3}{l}{\textbf{$\tau$-jet candidate}} \\504 % $\min p_T$ & \texttt{TAUJET\_pt} & $10$ GeV$/c$\\505 % \hline506 % \end{tabular}507 578 \begin{tabular}[!h]{lll} 508 579 \hline … … 525 596 \subsubsection*{Electromagnetic collimation} 526 597 527 To use the narrowness of the $\tau$-jet, the \textit{electromagnetic collimation} $C_{\tau}$ is defined as the sum of the energy of cells in a small cone of radius $R^\textrm{em}$ around the jet axis, divided by the energy of the reconstructed jet. 528 To be taken into account, a calorimeter cell should have a transverse energy $E_T^\textrm{cell}$ above a given threshold. 529 A large fraction of the jet energy is expected in this small cone. This fraction, or \textit{collimation factor}, is represented in Fig.~\ref{fig:tau2} for the default values (see Tab.~\ref{tab:tauRef}). 598 To use the narrowness of the $\tau$-jet, the \textit{electromagnetic 599 collimation} $C_{\tau}$ is defined as the sum of the energy of cells in a small 600 cone of radius $R^\textrm{em}$ around the jet axis, divided by the energy of the 601 reconstructed jet. To be taken into account, a calorimeter cell should have a 602 transverse energy $E_T^\textrm{cell}$ above a given threshold. A large fraction 603 of the jet energy is expected in this small cone. This fraction, or 604 \textit{collimation factor}, is represented in Fig.~\ref{fig:tau2} for the 605 default values (see Tab.~\ref{tab:tauRef}). 530 606 531 607 \begin{figure}[!ht] … … 543 619 \subsubsection*{Tracking isolation} 544 620 545 The tracking isolation for the $\tau$ identification requires that the number of tracks associated to particles with significant transverse momenta is one and only one in a cone of radius $R^\textrm{tracks}$ ($3-$prong $\tau$-jets are dropped). 546 This cone should be entirely incorporated into the tracker to be taken into account. Default values of these parameters are given in Tab.~\ref{tab:tauRef}. 621 The tracking isolation for the $\tau$ identification requires that the number 622 of tracks associated to particles with significant transverse momenta is one and 623 only one in a cone of radius $R^\textrm{tracks}$ ($3-$prong $\tau$-jets are 624 dropped). This cone should be entirely incorporated into the tracker to be taken 625 into account. Default values of these parameters are given in 626 Tab.~\ref{tab:tauRef}. 547 627 548 628 … … 560 640 561 641 \subsubsection*{Purity} 562 Once both electromagnetic collimation and tracking isolation are applied, a threshold on the $p_T$ of the $\tau$-jet candidate is requested to purify the collection. This procedure selects $\tau$ leptons decaying hadronically with a typical efficiency of $66\%$. 642 Once both electromagnetic collimation and tracking isolation are applied, a 643 threshold on the $p_T$ of the $\tau$-jet candidate is requested to purify the 644 collection. This procedure selects $\tau$ leptons decaying hadronically with a 645 typical efficiency of $66\%$. 563 646 564 647 \subsection{Missing transverse energy} 565 In an ideal detector, momentum conservation imposes the transverse momentum of the observed final state $\overrightarrow{p_T}^\textrm{obs}$ to be equal to the $\overrightarrow{p_T}$ vector sum of the invisible particles, written $\overrightarrow{p_T}^\textrm{miss}$. 566 \begin{equation} 567 \overrightarrow{p_T} = \left( 568 \begin{array}{c} 569 p_x\\ 570 p_y\\ 571 \end{array} 572 \right) 573 ~ \textrm{and} ~ 574 \left\{ 575 \begin{array}{l} 576 p_x^\textrm{miss} = - p_x^\textrm{obs} \\ 577 p_y^\textrm{miss} = - p_y^\textrm{obs} \\ 578 \end{array} 579 \right. 580 \end{equation} 581 The \textit{true} missing transverse energy, i.e.\ at generator-level, is calculated as the opposite of the vector sum of the transverse momenta of all visible particles -- or equivalently, to the vector sum of invisible particle transverse momenta. 582 In a real experiment, calorimeters measure energy and not momentum. Any problem affecting the detector (dead channels, misalignment, noisy cells, cracks) worsens directly the measured missing transverse energy $\overrightarrow {E_T}^\textrm{miss}$. In \textit{Delphes}, \textsc{MET} is based on the calorimetric cells only. Muons and neutrinos are therefore not taken into account for its evaluation: 648 In an ideal detector, momentum conservation imposes the transverse momentum of 649 the observed final state $\overrightarrow{p_T}^\textrm{obs}$ to be equal and 650 in opposite direction to the $\overrightarrow{p_T}$ vector sum of the 651 invisible particles, written $\overrightarrow{p_T}^\textrm{miss}$. 652 The \textit{true} missing transverse energy, i.e.\ at generator-level, is 653 calculated as the opposite of the vector sum of the transverse momenta of all 654 visible particles -- or equivalently, to the vector sum of invisible particle 655 transverse momenta. 656 In a real experiment, calorimeters measure energy and not momentum. Any problem 657 affecting the detector (dead channels, misalignment, noisy cells, cracks) 658 worsens directly the measured missing transverse energy $\overrightarrow 659 {E_T}^\textrm{miss}$. In \textit{Delphes}, \textsc{MET} is based on the 660 calorimetric cells only. Muons and neutrinos are therefore not taken into 661 account for its evaluation: 583 662 \begin{equation} 584 663 \overrightarrow{E_T}^\textrm{miss} = - \sum^\textrm{cells}_i \overrightarrow{E_T}(i) 585 664 \end{equation} 586 However, as muon candidates, tracks and calorimetric cells are available in the output file, the missing transverse energy can always be reprocessed a posteriori with more specialised algorithms. 665 However, as muon candidates, tracks and calorimetric cells are available in the 666 output file, the missing transverse energy can always be reprocessed a 667 posteriori with more specialised algorithms. 587 668 588 669 \section{Trigger emulation} 589 670 590 % New physics in collider experiment are often characterised in phenomenology by low cross-section values, compared to the Standard Model (\textsc{SM}) processes. 591 %For instance at the \textsc{LHC} ($\sqrt{s}=14~\textrm{TeV}$), the cross-section of inclusive production of $b \bar b$ pairs is expected to be $10^7~\textrm{nb}$, or inclusive jets at $100~\textrm{nb}$ ($p_T > 200~\textrm{GeV}/c$), while Higgs boson cross-section within the \textsc{SM} can be as small as $2 \times 10^{-3}~\textrm{nb}$ ($pp \rightarrow WH$, $m_H=115~\textrm{GeV}/c^2$). 592 593 %High statistics are required for data analyses, consequently imposing high luminosity, i.e.\ a high collision rate. 594 % As only a tiny fraction of the observed events can be stored for subsequent \textit{offline} analyses, a very large data rejection factor should be applied directly as the events are produced. 595 % This data selection is supposed to reject only well-known \textsc{SM} events\footnote{In real experiments, some bandwidth is allocated to minimum-bias and/or zero-bias (``random'') triggers that stores a small fraction of random events without any selection criteria.}. 596 % Dedicated algorithms of this \textit{online} selection, or \textit{trigger}, should be fast and very efficient for data rejection, in order to preserve the experiment output bandwidth. They must also be as inclusive as possible to avoid loosing interesting events. 597 598 Most of the usual trigger algorithms select events containing leptons, jets, and \textsc{MET} with an energy scale above some threshold. 599 This is often expressed in terms of a cut on the transverse momentum of one or several objects of the measured event. 600 Logical combinations of several conditions are also possible. For instance, a trigger path could select events containing at least one jet and one electron such as $p_T^\textrm{jet} > 100~\textrm{GeV}/c$ and $p_T^e > 50~\textrm{GeV}/c$. 601 602 A trigger emulation is included in \textit{Delphes}, using a fully parametrisable \textit{trigger table} \citep{qr:triggercard}. When enabled, this trigger is applied on analysis-object data. 603 In a real experiment, the online selection is often divided into several steps (or \textit{levels}). 604 % This splits the overall reduction factor into a product of smaller factors, corresponding to the different trigger levels. 605 % This is related to the architecture of the experiment data acquisition chain, with limited electronic buffers requiring a quick decision for the first trigger level. 606 First-level triggers are fast and simple but based only on partial data as not all detector front-ends are readable within the decision latency. 607 Higher level triggers are more complex, of finer-but-not-final quality and based on full detector data. 608 609 Real triggers are thus intrinsically based on reconstructed data with a worse resolution than final analysis data. 610 On the contrary, same data are used in \textit{Delphes} for trigger emulation and for final analyses. 671 Most of the usual trigger algorithms select events containing leptons, jets, and 672 \textsc{MET} with an energy scale above some threshold. This is often expressed 673 in terms of a cut on the transverse momentum of one or several objects of the 674 measured event. Logical combinations of several conditions are also possible. 675 For instance, a trigger path could select events containing at least one jet and 676 one electron such as $p_T^\textrm{jet} > 100~\textrm{GeV}/c$ and $p_T^e > 677 50~\textrm{GeV}/c$. 678 679 A trigger emulation is included in \textit{Delphes}, using a fully 680 parametrisable \textit{trigger table} \citep{qr:triggercard}. When enabled, this 681 trigger is applied on analysis-object data. In a real experiment, the online 682 selection is often divided into several steps (or \textit{levels}). 683 corresponding to the different trigger levels. 684 First-level triggers are fast and simple but based only on partial data as not 685 all detector front-ends are readable within the decision latency. 686 Higher level triggers are more complex, of finer-but-not-final quality and 687 based on full detector data. 688 689 Real triggers are thus intrinsically based on reconstructed data with a worse 690 resolution than final analysis information. On the contrary, the same 691 information is used in \textit{Delphes} for the trigger emulation and for final 692 analyses. 611 693 612 694 \section{\label{sec:vfd}Very forward detector simulation} 613 695 614 Most of the recent experiments in beam colliders have additional instrumentation along the beamline. These extend the $\eta$ coverage to higher values, for the detection of very forward final-state particles. In \textit{Delphes}, Zero Degree Calorimeters, roman pots and forward taggers have been implemented (Fig.~\ref{fig:fdets}), similarly to the plans for CMS and ATLAS collaborations~\citep{bib:cmsjetresolution, bib:ATLASresolution}. 696 Most of the recent experiments in beam colliders have additional 697 instrumentation along the beamline. These extend the $\eta$ coverage to higher 698 values, for the detection of very forward final-state particles. In 699 \textit{Delphes}, Zero Degree Calorimeters, roman pots and forward taggers have 700 been implemented (Fig.~\ref{fig:fdets}), similarly as for CMS and 701 ATLAS collaborations~\citep{bib:cmsjetresolution, bib:ATLASresolution}. 615 702 616 703 \begin{figure}[!ht] … … 618 705 %\includegraphics[width=\columnwidth]{fdets} 619 706 \includegraphics[width=\columnwidth]{fig4} 620 \caption{Default location of the very forward detectors, including \textsc{ZDC}, \textsc{RP220} and \textsc{FP420} in the \textsc{LHC} beamline. 621 Incoming (beam 1, red) and outgoing (beam 2, black) beams on one side of the fifth interaction point (\textsc{IP5}, $s=0~\textrm{m}$ on the plot). 622 The Zero Degree Calorimeter is located in perfect alignment with the beamline axis at the interaction point, at $140~\textrm{m}$, the beam paths are separated. The forward taggers are near-beam detectors located at $220~\textrm{m}$ and $420~\textrm{m}$. Beamline simulation with \textit{Hector}~\citep{bib:hector}. All very forward detectors are located symmetrically around the interaction point. } 707 \caption{Default location of the very forward detectors, including 708 \textsc{ZDC}, \textsc{RP220} and \textsc{FP420} in the \textsc{LHC} beamline. 709 Incoming (beam 1, red) and outgoing (beam 2, black) beams on one side of the 710 fifth interaction point (\textsc{IP5}, $s=0~\textrm{m}$ on the plot). 711 The Zero Degree Calorimeter is located in perfect alignment with the beamline 712 axis at the interaction point, at $140~\textrm{m}$, where the beam paths are 713 well separated. The forward taggers are near-beam detectors located at 714 $220~\textrm{m}$ and $420~\textrm{m}$. Beamline simulation with 715 \textit{Hector}~\citep{bib:hector}. All very forward detectors are located 716 symmetrically around the interaction point. } 623 717 \label{fig:fdets} 624 718 \end{center} 625 719 \end{figure} 626 720 627 %\begin{table*}[t] % the star (*) allows to arrange the table over the two columns628 721 \begin{table}[t] 629 722 \begin{center} 630 \caption{Default parameters for the forward detectors: distance from the interaction point and detector acceptance. The \textsc{LHC} beamline is assumed around the fifth \textsc{LHC} interaction point (\textsc{IP}). For the \textsc{ZDC}, the acceptance depends only on the pseudorapidity $\eta$ of the particle, which should be neutral and stable. 631 % The tagger acceptance is fully determined by the distance in the transverse plane of the detector to the real beam position~\citep{bib:hector}. 723 \caption{Default parameters for the forward detectors: distance from the 724 interaction point and detector acceptance. The \textsc{LHC} beamline is assumed 725 around the fifth \textsc{LHC} interaction point (\textsc{IP}). For the 726 \textsc{ZDC}, the acceptance depends only on the pseudorapidity $\eta$ of the 727 particle, which should be neutral and stable. 632 728 It is expressed in terms of the particle energy ($E$). 633 729 All detectors are located on both sides of the interaction point. … … 635 731 \begin{tabular}{llcl} 636 732 \hline 637 %Detector & Distance from \textsc{IP}& Acceptance & \\ \hline638 733 Detector & Distance & Acceptance & \\ \hline 639 734 \textsc{ZDC} & $\pm 140$ m & $|\eta|> 8.3$ & for $n$ and $\gamma$\\ … … 649 744 \subsection{Zero Degree Calorimeters} 650 745 651 In direct sight of the interaction point, on both sides of the central detector, the Zero Degree Calorimeters (\textsc{ZDC}s) are located at zero angle, i.e.\ are aligned with the beamline axis at the interaction point. They are placed beyond the point where the paths of incoming and outgoing beams separate. These allow the measurement of stable neutral particles ($\gamma$ and $n$) coming from the interaction point, with large pseudorapidities (e.g.\ $|\eta_{\textrm{n,}\gamma}| > 8.3$ in \textsc{ATLAS} and \textsc{CMS}). 652 653 The trajectory of the neutrals observed in the \textsc{ZDC}s is a straight line, while charged particles are deflected away from their acceptance window by the powerful magnets located in front of them. The fact that additional charged particles may enter the \textsc{ZDC} acceptance is neglected in the current versions of \textit{Delphes}. 746 In direct sight of the interaction point, on both sides of the central 747 detector, the Zero Degree Calorimeters (\textsc{ZDC}s) are located at zero 748 angle, i.e.\ are aligned with the beamline axis at the interaction point. They 749 are placed beyond the point where the paths of incoming and outgoing beams 750 separate. These allow the measurement of stable neutral particles ($\gamma$ and 751 $n$) coming from the interaction point, with large pseudorapidities (e.g.\ 752 $|\eta_{\textrm{n,}\gamma}| > 8.3$ in \textsc{ATLAS} and \textsc{CMS}). 753 754 The trajectory of the neutrals observed in the \textsc{ZDC}s is a straight 755 line, while charged particles are deflected away from their acceptance window by 756 the powerful magnets located in front of them. The fact that additional charged 757 particles may enter the \textsc{ZDC} acceptance is neglected in the current 758 versions of \textit{Delphes}. 654 759 655 760 The \textsc{ZDC}s have the ability to measure the time-of-flight of the particle. 656 This corresponds to the delay $t$ after which the particle is observed in the detector, with respect to the bunch crossing reference time at the interaction point ($t_0$): 761 This corresponds to the delay $t$ after which the particle is observed in the 762 detector, with respect to the bunch crossing reference time at the interaction 763 point ($t_0$): 657 764 \begin{equation} 658 765 t = t_0 + \frac{1}{v} \times \Big( \frac{s-z}{\cos \theta}\Big) \approx \frac{1}{c} \times (s-z), 659 766 \end{equation} 660 where $t_0$ is thus 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, $\theta$ is the particle emission angle. It is assumed that the neutral particle observed in the \textsc{ZDC} is highly relativistic and very forward. 661 % 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 $1 - \cos \theta < 10^{-4}$. 662 % The formula then reduces to 663 % \begin{equation} 664 % t = \frac{1}{c} \times (s-z). 665 % \end{equation} 666 % For example, a photon takes $0.47~\mu\textrm{s}$ to reach a \textsc{ZDC} located at $s=140~\textrm{m}$, neglecting $z$ and $\theta$. 667 For the time-of-flight measurement, a Gaussian smearing can be applied according to the detector resolution (Tab.~\ref{tab:defResolZdc})~\citep{qr:resolutionterms}. 668 %In the current version of \textit{Delphes}, only neutrons, antineutrons and photons are assumed to be able to reach the \textsc{ZDC}s, all other particles being neglected. 669 670 The \textsc{ZDC}s are composed of an electromagnetic and a hadronic sections, for the measurement of photons and neutrons, respectively. The energy of the observed neutral is smeared according to Eq.~\ref{eq:caloresolution} and the corresponding section resolutions (Tab.~\ref{tab:defResolZdc}). The \textsc{ZDC} hits do not enter in the calorimeter cell list used for reconstruction of jets and missing transverse energy. 767 where $t_0$ is thus the true time coordinate of the vertex from which the 768 particle originates, $v$ the particle velocity, $s$ is the \textsc{ZDC} distance 769 to the interaction point, $z$ is the longitudinal coordinate of the vertex, 770 $\theta$ is the particle emission angle. It is assumed that the neutral particle 771 observed in the \textsc{ZDC} is highly relativistic and very forward. 772 For the time-of-flight measurement, a Gaussian smearing can be applied according 773 to the detector resolution 774 (Tab.~\ref{tab:defResolZdc})~\citep{qr:resolutionterms}. 775 776 777 The \textsc{ZDC}s are composed of an electromagnetic and a hadronic sections, 778 for the measurement of photons and neutrons, respectively. The energy of the 779 observed neutral is smeared according to Eq.~\ref{eq:caloresolution} and the 780 corresponding section resolutions (Tab.~\ref{tab:defResolZdc}). The \textsc{ZDC} 781 hits do not enter in the calorimeter cell list used for reconstruction of jets 782 and missing transverse energy. 671 783 672 784 \begin{table}[!h] 673 785 \begin{center} 674 \caption{Default values for the resolution of the zero degree calorimeters. Resolution on energy measurement is parametrised by the \textit{stochastic} ($S$), \textit{noise} ($N$) and \textit{constant} ($C$) terms (Eq.~\ref{eq:caloresolution})~\citep{qr:resolutionterms}. The time-of-flight is smeared according to a Gaussian function. 786 \caption{Default values for the resolution of the zero degree calorimeters. 787 Resolution on energy measurement is parametrised by the \textit{stochastic} 788 ($S$), \textit{noise} ($N$) and \textit{constant} ($C$) terms 789 (Eq.~\ref{eq:caloresolution})~\citep{qr:resolutionterms}. The time-of-flight is 790 smeared according to a Gaussian function. 675 791 \vspace{0.5cm}} 676 % \begin{tabular}[!h]{lllc}677 % \hline678 % \multicolumn{2}{c}{Resolution Term} & Card flag & Value\\\hline679 % \multicolumn{4}{l}{\textsc{ZDC}, electromagnetic part} \\680 % & $S$ (GeV$^{1/2}$)& \texttt{ELG\_Szdc} & $0.7$ \\681 % & $N$ (GeV)& \texttt{ELG\_Nzdc} & $0.0$ \\682 % & $C$ & \texttt{ELG\_Czdc} & $0.08$ \\683 % \multicolumn{4}{l}{\textsc{ZDC}, hadronic part} \\684 % & $S$ (GeV$^{1/2}$)& \texttt{HAD\_Szdc} & $1.38$\\685 % & $N$ (GeV)& \texttt{HAD\_Nzdc} & $0$ \\686 % & $C$ & \texttt{HAD\_Czdc} & $0.13$\\687 % \multicolumn{4}{l}{\textsc{ZDC}, timing resolution} \\688 % & $\sigma_t$ (s) & \texttt{ZDC\_T\_resolution} & $0$ \\689 % \hline690 % \end{tabular}691 792 \begin{tabular}[!h]{llcc} 692 793 \hline … … 703 804 \end{table} 704 805 705 % \subsubsection*{Forward neutrals} 706 707 The reconstructed ZDC hits correspond to neutral particles with a lifetime long enough to reach these detectors (default: $c \tau \geq 140~\textrm{m}$) and verylarge pseudorapidities (default: $|\eta|>8.3$).708 %In current versions of \textit{Delphes}, only photons and neutrons are considered. 709 Photons are identified thanks to the electromagnetic section of the calorimeter, and if their energy overpasses a given threshold (def. $20$~GeV). Similarly, neutrons are reconstructed according to the resolution of the hadronic section, if their energy exceeds a threshold (def. $50$~GeV)~\citep{qr:fwdneutrals}.710 %\footnote{\texttt{[code]} These thresholds are defined by the \texttt{ZDC\_gamma\_E} and \texttt{ZDC\_n\_E} variables in the detector card.} (def. $50$~GeV). 806 The reconstructed ZDC hits correspond to neutral particles with a lifetime long 807 enough to reach these detectors (default: $c \tau \geq 140~\textrm{m}$) and very 808 large pseudorapidities (default: $|\eta|>8.3$). 809 Photons and neutrons are identified if their energy overpasses a given threshold 810 (def. $E_\gamma \leq 20$~GeV and $E_n \leq 50$~GeV)~\citep{qr:fwdneutrals}. 811 711 812 712 813 713 814 \subsection{Forward taggers} 714 815 715 Forward taggers (called here \textsc{RP220}, for ``roman pots at $220~\textrm{m}$'' and \textsc{FP420} for ``forward proton taggers at $420~\textrm{m}$'', as at the \textsc{LHC}) are meant for the measurement of particles following very closely the beam path. Such devices, also used at \textsc{HERA} and Tevatron, are located very far away from the interaction point (further than $150$~m in the \textsc{LHC} case). 716 717 To be able to reach these detectors, particles must have a charge identical to the beam particles, and a momentum very close to the nominal value of the beam. These taggers are near-beam detectors located a few millimetres from the true beam trajectory and this distance defines their acceptance (Tab.~\ref{tab:fdetacceptance}). 718 For instance, roman pots at $220~\textrm{m}$ from the \textsc{IP} and $2~\textrm{mm}$ from the beam will detect all forward protons with an energy between $120$ and $900~\textrm{GeV}$~\citep{bib:hector}. 719 In practice, in the \textsc{LHC}, only positively charged muons ($\mu^+$) and protons can reach the forward taggers as other particles with a single positive charge coming from the interaction points will decay before their possible tagging. In \textit{Delphes}, extra hits coming from the beam-gas events or secondary particles hitting the beampipe in front of the detectors are not taken into account. 720 721 While neutral particles propagate along a straight line to the \textsc{ZDC}, a dedicated simulation of the transport of charged particles is needed for \textsc{RP220} and \textsc{FP420}. This fast simulation uses the \textit{Hector} software~\citep{bib:hector}, which includes the chromaticity effects and the geometrical aperture of the beamline elements of any arbitrary collider. 722 723 Forward taggers are able to measure the hit positions ($x,y$) and angles ($\theta_x,\theta_y$) in the transverse plane at the location of the detector ($s$ meters away from the \textsc{IP}), as well as the time-of-flight\footnote{It is worth noting that for both \textsc{CMS} and \textsc{ATLAS} experiments, the taggers located at $220$~m are not able to measure the time-of-flight, contrary to \textsc{FP420} detectors.} ($t$). Out of these the particle energy ($E$) and the momentum transfer it underwent during the interaction ($q^2$) can be reconstructed at the analysis level (it is not implemented in the current versions of \textit{Delphes}. The time-of-flight measurement can be smeared with a Gaussian distribution (default value 724 %\footnote{\texttt{[code] } The resolution is defined by the \texttt{RP220\_T\_resolution} and \texttt{RP420\_T\_resolution} parameters in the detector card.} 816 Forward taggers (called here \textsc{RP220}, for ``roman pots at 817 $220~\textrm{m}$'' and \textsc{FP420} for ``forward proton taggers at 818 $420~\textrm{m}$'', as at the \textsc{LHC}) are meant for the measurement of 819 particles following very closely the beam path. Such devices, also used at 820 \textsc{HERA} and Tevatron, are located very far away from the interaction point 821 (further than $150$~m in the \textsc{LHC} case). 822 823 To be able to reach these detectors, particles must have a charge identical to 824 the beam particles, and a momentum very close to the nominal value of the beam. 825 These taggers are near-beam detectors located a few millimetres from the true 826 beam trajectory and this distance defines their acceptance 827 (Tab.~\ref{tab:fdetacceptance}). For instance, roman pots at $220~\textrm{m}$ 828 from the \textsc{IP} and $2~\textrm{mm}$ from the beam will detect all forward 829 protons with an energy between $120$ and $900~\textrm{GeV}$~\citep{bib:hector}. 830 In practice, in the \textsc{LHC}, only positively charged muons ($\mu^+$) and 831 protons can reach the forward taggers as other particles with a single positive 832 charge coming from the interaction points will decay before their possible 833 tagging. In \textit{Delphes}, extra hits coming from the beam-gas events or 834 secondary particles hitting the beampipe in front of the detectors are not taken 835 into account. 836 837 While neutral particles propagate along a straight line to the \textsc{ZDC}, a 838 dedicated simulation of the transport of charged particles is needed for 839 \textsc{RP220} and \textsc{FP420}. This fast simulation uses the \textit{Hector} 840 software~\citep{bib:hector}, which includes the chromaticity effects and the 841 geometrical aperture of the beamline elements of any arbitrary collider. 842 843 Forward taggers are able to measure the hit positions ($x,y$) and angles 844 ($\theta_x,\theta_y$) in the transverse plane at the location of the detector 845 ($s$ meters away from the \textsc{IP}), as well as the 846 time-of-flight\footnote{It is worth noting that for both \textsc{CMS} and 847 \textsc{ATLAS} experiments, the taggers located at $220$~m are not able to 848 measure the time-of-flight, contrary to \textsc{FP420} detectors.} ($t$). Out of 849 these the particle energy ($E$) and the momentum transfer it underwent during 850 the interaction ($q^2$) can be reconstructed at the analysis level (it is not 851 implemented in the current versions of \textit{Delphes}. The time-of-flight 852 measurement can be smeared with a Gaussian distribution (default value 725 853 $\sigma_t = 0~\textrm{s}$)~\citep{qr:protontaggers}. 726 854 … … 730 858 731 859 \textit{Delphes} performs a fast simulation of a collider experiment. 732 Its performances in terms of computing time and data size are directly proportional to the number of simulated events and on the considered physics process. As an example, $10,000$ $pp \rightarrow t \bar t X$ events are processed in $110~\textrm{s}$ on a regular laptop and use less than $250~\textrm{MB}$ of disk space. 733 The quality and validity of the output are assessed by comparing the resolutions on the reconstructed data to the expectations of both \textsc{CMS}~\citep{bib:cmsjetresolution} and \textsc{ATLAS}~\citep{bib:ATLASresolution} detectors. 734 735 Electrons and muons are by construction equal to the experiment designs, as the Gaussian smearing of their kinematics properties is defined according to the detector specifications. 736 Similarly, the $b$-tagging efficiency (for real $b$-jets) and misidentification rates (for fake $b$-jets) are taken directly from the expected values of the experiment. 737 Unlike these simple objects, jets and missing transverse energy should be carefully cross-checked. 860 Its performances in terms of computing time and data size are directly 861 proportional to the number of simulated events and on the considered physics 862 process. As an example, $10,000$ $pp \rightarrow t \bar t X$ events are 863 processed in $110~\textrm{s}$ on a regular laptop and use less than 864 $250~\textrm{MB}$ of disk space. 865 The quality and validity of the output are assessed by comparing the 866 resolutions on the reconstructed data to the expectations of both 867 \textsc{CMS}~\citep{bib:cmsjetresolution} and 868 \textsc{ATLAS}~\citep{bib:ATLASresolution} detectors. 869 870 Electrons and muons are by construction equal to the experiment designs, as the 871 Gaussian smearing of their kinematics properties is defined according to the 872 detector specifications. Similarly, the $b$-tagging efficiency (for real 873 $b$-jets) and misidentification rates (for fake $b$-jets) are taken directly 874 from the expected values of the experiment. Unlike these simple objects, jets 875 and missing transverse energy should be carefully cross-checked. 738 876 739 877 \subsection{Jet resolution} 740 878 741 The majority of interesting processes at the \textsc{LHC} contain jets in the final state. The jet resolution obtained using \textit{Delphes} is therefore a crucial point for its validation, both for \textsc{CMS}- and \textsc{ATLAS}-like detectors. 742 This validation is based on $pp \rightarrow gg$ events produced with MadGraph/MadEvent and hadronised using \textit{Pythia}~\citep{bib:mgme,bib:pythia}. 743 744 For a \textsc{CMS}-like detector, a similar procedure as the one explained in published results is applied here. 745 The events were arranged in $14$ bins of gluon transverse momentum $\hat{p}_T$. In each $\hat{p}_T$ bin, every jet in \textit{Delphes} is matched to the closest jet of generator-level particles, using the spatial separation between the two jet axes 879 The majority of interesting processes at the \textsc{LHC} contain jets in the 880 final state. The jet resolution obtained using \textit{Delphes} is therefore a 881 crucial point for its validation, both for \textsc{CMS}- and \textsc{ATLAS}-like 882 detectors. This validation is based on $pp \rightarrow gg$ events produced with 883 MadGraph/MadEvent and hadronised 884 using \textit{Pythia}~\citep{bib:mgme,bib:pythia}. 885 886 For a \textsc{CMS}-like detector, a similar procedure as the one explained in 887 published results is applied here. The events were arranged in $14$ bins of 888 gluon transverse momentum $\hat{p}_T$. In each $\hat{p}_T$ bin, every jet in 889 \textit{Delphes} is matched to the closest jet of generator-level particles, 890 using the spatial separation between the two jet axes 746 891 \begin{equation} 747 \Delta R = \sqrt{ \big(\eta^\textrm{rec} - \eta^\textrm{MC} \big)^2 + \big(\phi^\textrm{rec} - \phi^\textrm{MC} \big)^2}<0.25. 892 \Delta R = \sqrt{ \big(\eta^\textrm{rec} - \eta^\textrm{MC} \big)^2 + 893 \big(\phi^\textrm{rec} - \phi^\textrm{MC} \big)^2}<0.25. 748 894 \end{equation} 749 The jets made of generator-level particles, here referred as \textit{MC jets}, are obtained by applying the algorithm to all particles considered as stable after hadronisation (i.e.\ including muons). 750 Jets produced by \textit{Delphes} and satisfying the matching criterion are called hereafter \textit{reconstructed jets}. 751 All jets are computed with the clustering algorithm (JetCLU) with a cone radius $R$ of $0.7$. 752 753 The ratio of the transverse energies of every reconstructed jet $E_T^\textrm{rec}$ to its corresponding \textsc{MC} jet $E_T^\textrm{MC}$ is calculated in each $\hat{p}_T$ bin. 754 The $E_T^\textrm{rec}/E_T^\textrm{MC}$ histogram is fitted with a Gaussian distribution in the interval \mbox{$\pm 2$~\textsc{RMS}} centred around the mean value. 755 The resolution in each $\hat{p}_T$ bin is obtained by the fit mean $\langle x \rangle$ and variance $\sigma^2(x)$: 895 The jets made of generator-level particles, here referred as \textit{MC jets}, 896 are obtained by applying the algorithm to all particles considered as stable 897 after hadronisation (i.e.\ including muons). Jets produced by \textit{Delphes} 898 and satisfying the matching criterion are called hereafter \textit{reconstructed 899 jets}. All jets are computed with the clustering algorithm (JetCLU) with a cone 900 radius $R$ of $0.7$. 901 902 The ratio of the transverse energies of every reconstructed jet 903 $E_T^\textrm{rec}$ to its corresponding \textsc{MC} jet $E_T^\textrm{MC}$ is 904 calculated in each $\hat{p}_T$ bin. The $E_T^\textrm{rec}/E_T^\textrm{MC}$ 905 histogram is fitted with a Gaussian distribution in the interval \mbox{$\pm 906 2$~\textsc{RMS}} centred around the mean value. The resolution in each 907 $\hat{p}_T$ bin is obtained by the fit mean $\langle x \rangle$ and variance 908 $\sigma^2(x)$: 756 909 \begin{equation} 757 %\frac{\sigma(R_{jet})}{\langle R_{jet} \rangle }= 758 \frac{\sigma \Big (\frac{E_T^\textrm{rec}}{E_T^\textrm{MC}} \Big)_\textrm{fit}}{ \Big \langle \frac{E_T^\textrm{rec}}{E_T^\textrm{MC}} \Big \rangle_\textrm{fit}}~ 910 \frac{\sigma \Big (\frac{E_T^\textrm{rec}}{E_T^\textrm{MC}} \Big)_\textrm{fit}}{ 911 \Big \langle \frac{E_T^\textrm{rec}}{E_T^\textrm{MC}} \Big 912 \rangle_\textrm{fit}}~ 759 913 \Big( \hat{p}_T(i) \Big)\textrm{, for all }i. 760 914 \end{equation}
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