Changeset 540 in svn
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- Feb 6, 2010, 9:54:31 AM (15 years ago)
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- trunk/paper/CommPhysComp
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trunk/paper/CommPhysComp/notes.tex
r532 r540 118 118 119 119 \begin{keyword} 120 \textit{Delphes} \sep fast simulation \sep trigger \sep event display \sep \textsc{LHC} \sep FastJet \sep \textit{Hector} \sep \textsc{FROG} \sep Les Houches Event File \sep HepMC \sep \textsc{ROOT}120 \textit{Delphes} \sep detector simulation \sep event reconstruction \sep trigger \sep \textsc{LHC} 121 121 \PACS 29.85.-c \sep 07.05.Tp \sep 29.90.+r \sep 29.50.+v 122 122 \end{keyword} … … 128 128 \section{Introduction} 129 129 130 % Experiments at high energy colliders are very complex systems for several reasons. Firstly, in terms of the various detector subsystems, including tracking, central calorimetry, forward calorimetry, and muon chambers. Such apparatus differ in their detection principles, technologies, geometrical acceptances, resolutions and sensitivities. Secondly, due to the requirement of a highly effective online selection (i.e.\ a \textit{trigger}), subdivided into several levels for an optimal reduction factor of ``uninteresting'' events, 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 approaches.131 132 130 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. 133 131 … … 138 136 139 137 A new framework, called \textit{Delphes}~\citep{bib:delphes}, is introduced here, for the fast simulation of a general-purpose collider experiment. 140 Using the framework, observables can be estimated for specific signal and background channels, as well as their production and measurement rates. 141 Starting from the output of event generators, the simulation of the detector response takes into account the subdetector resolutions, by smearing the kinematic properties of the final-state particles (i.e. those considered as stable by the event generator 142 \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}.}). 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. 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. 143 142 144 143 \textit{Delphes} includes the most crucial experimental features, such as (Fig.~\ref{fig:FlowChart}): 145 144 \begin{enumerate} 146 145 \item the geometry of both central and forward detectors, 147 \item magnetic field for tracks and energy flow148 \item reconstruction of photons, leptons, jets, $b$-jets, $\tau$-jets and missing transverse energy,149 \item lepton isolation,150 \item trigger emulation,146 \item the effect of magnetic field on tracks, 147 \item the reconstruction of photons, leptons, jets, $b$-jets, $\tau$-jets and missing transverse energy, 148 \item a lepton isolation, 149 \item a trigger emulation, 151 150 \item an event display. 152 151 \end{enumerate} … … 167 166 \end{figure*} 168 167 169 Although this kind of approach yields much realistic results than a simple ``parton-level" analysis, a fast simulation comes withsome 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.170 171 Several datafile formats can be used as input in \textit{Delphes} \citep{qr:inputformat},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}, 172 171 %\footnote{\texttt{[code] }See the \texttt{HEPEVTConverter}, \texttt{HepMCConverter}, \texttt{LHEFConverter} and \texttt{STDHEPConverter} classes.}. 173 in order to process events from many different generators. 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}. 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}. 174 174 %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. 175 176 \textit{Delphes} uses the \texttt{ExRootAnalysis} utility~\citep{bib:ExRootAnalysis} to create output data in a \texttt{*.root} ntuple. 177 This output contains a copy of the generator-level data (\texttt{GEN} tree), the analysis data objects after reconstruction (\texttt{Analysis} tree), and possibly the results of the trigger emulation (\texttt{Trigger} tree). 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}. 178 177 In option 179 178 %\footnote{\texttt{[code]} See the \texttt{FLAG\_LHCO} variable in the detector datacard. This text file format is shortly described in the user manual.}, … … 185 184 186 185 The overall layout of the multipurpose detector simulated by \textit{Delphes} is shown in Fig.~\ref{fig:GenDet3}. 187 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). Two forward calorimeters (\textsc{FCAL}) ensure a larger geometric coverage for the measurement of the missing transverse energy. Finally, a muon system (\textsc{MUON}) encloses the central detector volume. 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. 189 188 190 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. 189 191 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}. … … 191 193 %\footnote{\texttt{[code] }Detector and trigger cards for the \textsc{ATLAS} and \textsc{CMS} experiments are also provided in \texttt{data/} directory.}. 192 194 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. 193 196 194 197 \begin{table}[t] … … 228 231 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). 229 232 It is surrounded by a central calorimeter volume (green) with both electromagnetic and hadronic sections. 230 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. 231 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). Additional forward detectors are not depicted. 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). 235 Additional forward detectors are not depicted. 232 236 } 233 237 \label{fig:GenDet3} … … 252 256 \subsection{Calorimetric cells} 253 257 254 The response of the calorimeters to energy deposits of incoming particles depends on their segmentation and resolution. 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. 255 256 The response of each sub-calorimeter is parametrised through a Gaussian smearing of the particle energy with a variance $\sigma$: 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. 262 263 \begin{figure}[!ht] 264 \begin{center} 265 %\includegraphics[width=\columnwidth]{calosegmentation} 266 \includegraphics[width=\columnwidth]{fig3} 267 \caption{Default segmentation of the calorimeters in the $(\eta,\phi)$ plane. Only the central detectors (\textsc{ECAL}, \textsc{HCAL}) and \textsc{FCAL} are considered. $\phi$ angles are expressed in radians.} 268 \label{fig:calosegmentation} 269 \end{center} 270 \end{figure} 271 272 273 The calorimeter response is parametrised through a Gaussian smearing of the accumulated cell energy with a variance $\sigma$: 257 274 \begin{equation} 258 275 \frac{\sigma}{E} = \frac{S}{\sqrt{E}} \oplus \frac{N}{E} \oplus C, … … 261 278 where $S$, $N$ and $C$ are the \textit{stochastic}, \textit{noise} and \textit{constant} terms, respectively, and $\oplus$ stands for quadratic additions~\citep{qr:energysmearing}.\\ 262 279 263 %\footnote{\texttt{[code] } The response of the detector is applied to the electromagnetic and the hadronic particles through the \texttt{SmearElectron} and \texttt{SmearHadron} functions.} 264 In the default parametrisation, the calorimeter is assumed to cover the pseudorapidity range $|\eta|<3$ and consists in an electromagnetic and hadronic parts. Coverage between pseudorapidities of $3.0$ and $5.0$ is provided by forward calorimeters, with different response to electromagnetic objects ($e^\pm, \gamma$) or hadrons. 280 In the default parametrisation, ECAL and HCAL are assumed to cover the pseudorapidity range $|\eta|<3$, and FCAL between $3.0$ and $5.0$, with different response to electromagnetic objects ($e^\pm, \gamma$) or hadrons. 265 281 Muons and neutrinos are assumed not to interact with the calorimeters~\citep{qr:invisibleparticles}. 266 %\footnote{In the current \textit{Delphes} version, particles other than electrons ($e^\pm$), photons ($\gamma$), muons ($\mu^\pm$) and neutrinos ($\nu_e$, $\nu_\mu$ and $\nu_\tau$) 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.}.267 282 The default values of the stochastic, noise and constant terms are given in Tab.~\ref{tab:defResol}.\\ 268 283 … … 294 309 \end{table} 295 310 296 % \begin{table}[!h] 297 % \begin{center} 298 % \caption{Default values for the resolution of the central and forward calorimeters. Resolution is parametrised by the \textit{stochastic} ($S$), \textit{noise} ($N$) and \textit{constant} ($C$) terms (Eq.~\ref{eq:caloresolution}). 299 % The corresponding parameter name, in the detector card, is given. \vspace{0.5cm}} 300 % \begin{tabular}[!h]{lllc} 301 % \hline 302 % \multicolumn{2}{c}{Resolution Term} & Card flag & Value\\\hline 303 % \multicolumn{4}{l}{\textsc{ECAL}} \\ 304 % & $S$ (GeV$^{1/2}$) & {\verb ELG_Scen } & $0.05$ \\ 305 % & $N$ (GeV)& {\verb ELG_Ncen } & $0.25$ \\ 306 % & $C$ & {\verb ELG_Ccen } & $0.0055$ \\ 307 % \multicolumn{4}{l}{\textsc{ECAL}, end caps} \\ 308 % & $S$ (GeV$^{1/2}$) & {\verb ELG_Sec } & $0.05$ \\ 309 % & $N$ (GeV)& {\verb ELG_Nec } & $0.25$ \\ 310 % & $C$ & {\verb ELG_Cec } & $0.0055$ \\ 311 % \multicolumn{4}{l}{\textsc{FCAL}, electromagnetic part} \\ 312 % & $S$ (GeV$^{1/2}$)& {\verb ELG_Sfwd } & $2.084$ \\ 313 % & $N$ (GeV)& {\verb ELG_Nfwd } & $0$ \\ 314 % & $C$ & {\verb ELG_Cfwd } & $0.107$ \\ 315 % \multicolumn{4}{l}{\textsc{HCAL}} \\ 316 % & $S$ (GeV$^{1/2}$)& {\verb HAD_Scen } & $1.5$ \\ 317 % & $N$ (GeV)& {\verb HAD_Ncen } & $0$\\ 318 % & $C$ & {\verb HAD_Ccen } & $0.05$\\ 319 % \multicolumn{4}{l}{\textsc{HCAL}, end caps} \\ 320 % & $S$ (GeV$^{1/2}$)& {\verb HAD_Sec } & $1.5$ \\ 321 % & $N$ (GeV)& {\verb HAD_Nec } & $0$\\ 322 % & $C$ & {\verb HAD_Cec } & $0.05$\\ 323 % \multicolumn{4}{l}{\textsc{FCAL}, hadronic part} \\ 324 % & $S$ (GeV$^{1/2}$)& {\verb HAD_Sfwd } & $2.7$\\ 325 % & $N$ (GeV)& {\verb HAD_Nfwd } & $0$ \\ 326 % & $C$ & {\verb HAD_Cfwd } & $0.13$\\ 327 % \hline 328 % \end{tabular} 329 % \label{tab:defResol} 330 % \end{center} 331 % \end{table} 332 333 334 The energy of electrons and photons found in the particle list are smeared using only the \textsc{ECAL} resolution terms, while charged and neutral final-state hadrons interact with all calorimeters. 335 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 decay before the calorimeters. The energy smearing of such particles is 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 311 312 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 336 314 \begin{equation} 337 315 \left\{ … … 342 320 \right. 343 321 \end{equation} 344 where $0 \leq F \leq 1$. The electromagnetic part is handled the same way for the electrons and photons. 345 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 346 %\footnote{\texttt{[code]} To implement different ratios for other particles, see the \texttt{BlockClasses} class.} 347 , the energy fraction is $F$ is assumed to be $0.7$~\citep{qr:emhadratios}.\\ 348 349 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}. 350 Fig.~\ref{fig:calosegmentation} illustrates the default calorimeter segmentation. 351 352 \begin{figure}[!ht] 353 \begin{center} 354 %\includegraphics[width=\columnwidth]{calosegmentation} 355 \includegraphics[width=\columnwidth]{fig3} 356 \caption{Default segmentation of the calorimeters in the $(\eta,\phi)$ plane. Only the central detectors (\textsc{ECAL}, \textsc{HCAL}) and \textsc{FCAL} are considered. $\phi$ angles are expressed in radians.} 357 \label{fig:calosegmentation} 358 \end{center} 359 \end{figure} 360 361 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 directly enter in the calculation of the missing transverse energy (\textsc{MET}), and as input for the jet reconstruction algorithms. 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. 362 327 363 328 … … 366 331 \section{High-level object reconstruction} 367 332 368 Analysis object data contain the final collections of particles ($e^\pm$, $\mu^\pm$, $\gamma$) or objects (light jets, $b$-jets, $\tau$-jets, $E_T^\textrm{miss}$) and are stored 369 %\footnote{\texttt{[code] }All these processed data are located under the \texttt{Analysis} tree.} 370 in the output file created by \textit{Delphes}~\citep{qr:analysistree}. 371 In addition, some detector data are added: tracks, calorimetric cells and hits in the very forward detectors (\textsc{ZDC}, \textsc{RP220} and \textsc{FP420}, Sec.~\ref{sec:vfd}). While electrons, muons and photons are easily identified, some other objects are more difficult to measure, like jets or missing energy due to invisible particles. 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). 372 334 373 335 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). 374 336 375 \subsection{Photon and charged lepton reconstruction} 376 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. The collections of electrons, photons and muons are filled in with candidates observing some fiducial and reconstruction cuts, and are based on the true particle ID provided by the generator. 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}. 337 \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}. 377 344 378 345 \subsubsection*{Electrons and photons} 379 Real electron ($e^\pm$) and photon candidates are identified if they fall into the acceptance of the tracking system and have a transverse momentum above a threshold (default $p_T > 10~\textrm{GeV}/c$). A calorimetric cell will be activated in the detector and electrons will leave in addition a track. Subsequently, electrons and photons create a candidate in the jet collection. 380 Assuming a good measurement of the track parameters in the real experiment, the electron energy can be reasonably recovered. In \textit{Delphes}, 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. This approach is still conservative as the calorimeter resolution is worse than the tracker one. 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. 349 Electrons and photons may create a candidate in the jet collection. 381 350 382 351 \subsubsection*{Muons} 383 Generator-level muons entering the detector acceptance are considered as candidates for the analysis level. 384 The acceptance is defined in terms of a transverse momentum threshold to be overpassed that should be computed using the chosen geometry of the detector and the magnetic field considered (default : $p_T > 10~\textrm{GeV}/c$) and of the pseudorapidity coverage of the muon system (default: $-2.4 \leq \eta \leq 2.4$). 385 The application of the detector resolution on the muon momentum depends on a Gaussian smearing of the $p_T$ variable~\citep{qr:muonsmearing}. 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}. 386 354 %\footnote{\texttt{[code]} See the \texttt{SmearMuon} method.}. 387 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. Furthermore, muons leave no deposit in calorimeters. At last, the particles which might leak out of the calorimeters into the muon systems (\textit{punch-through}) will not be seenas muon candidates in \textit{Delphes}.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}. 388 356 389 357 \subsubsection*{Charged lepton isolation} 390 358 \label{sec:isolation} 391 359 392 To improve the quality of the contents of the charged lepton collections, additional criteria can be applied such as isolation. 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 $\Delta R = \sqrt{\Delta \eta^2 + \Delta \phi^2} <0.5$ around the lepton. 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. 361 393 362 The result (i.e.\ \textit{isolated} or \textit{not}) is added to the charged lepton measured properties. 394 363 In addition, the sum $P_T$ of the transverse momenta of all tracks but the lepton one within the isolation cone is 395 364 provided~\citep{qr:isolflag}: 396 365 %\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.} 397 $$ P_T = \sum_{i \neq \ mu}^\textrm{tracks} p_T(i)$$398 399 No calorimetric isolation is applied, but the muon collection contains also the ratio $\rho_\mu$ between (1) the sum of the transverse energies in all calorimetric cells in a $N \times N$ grid around the muon, and (2) the muon transverse momentum~\citep{qr:caloisolation}:366 $$ P_T = \sum_{i \neq \ell}^\textrm{tracks} p_T(i)$$ 367 368 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}: 400 369 %\footnote{\texttt{[code] }Calorimetric isolation parameters in the detector card are \texttt{ISOL\_Calo\_ET} and \texttt{ISOL\_Calo\_Grid}.}: 401 $$ \rho_\ mu = \frac{\Sigma_i E_T(i)}{p_T(\mu)}~,~ i\textrm{ in }N \times N \textrm { grid centred on }\mu.$$370 $$ \rho_\ell = \frac{\Sigma_i E_T(i)}{p_T(\ell)}~,~ i\textrm{ in }N \times N \textrm { grid centred on }\ell.$$ 402 371 403 372 … … 411 380 \subsection{Jet reconstruction} 412 381 413 A realistic analysis requires a correct treatment of part icles 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.}.414 Six different jet reconstruction schemes are available , with three cone algorithms and three recombination algorithms~\citep{bib:FASTJET,qr:jetalgo}.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}. 415 384 %\footnote{\texttt{[code] }The choice is done by allocating the \texttt{JET\_jetalgo } input parameter in the detector card.}. 416 385 % The first three belong to the cone algorithm class while the last three are using a sequential recombination scheme. 417 For all of them, the calorimetric cells are used as inputs for the jet clustering. Jet algorithms differ in their sensitivity to soft particles or collinear splittings, and in their computing speed performances. 418 By default, reconstruction uses a cone algorithm with $\Delta R=0.7$. 419 Jets are stored if their transverse energy is higher 420 %\footnote{\texttt{[code] PTCUT\_jet }variable in the detector card.} 421 than $20~\textrm{GeV}$~\citep{qr:ptcutjet}. 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. 422 387 423 388 \subsubsection*{Cone algorithms} … … 426 391 427 392 \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 428 transverse energy $E_T$ overpassinga given threshold (default: $E_T > 1~\textrm{GeV}$)~\citep{qr:jetparams}.429 430 \item {\it CDF MidPoint}~\citep{bib:midpoint}: Cone algorithm with additional ``midpoints'' (energy barycentres) in the list of seeds ; this algorithm has reduced infrared and collinear sensitivities.431 432 \item {\it Seedless Infrared Safe Cone}~\citep{bib:SIScone}: The \textsc{SISC}one algorithm is simultaneously insensitive to additional soft particles and collinear splittings , and fast enough to be used in experimental analysis.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. 433 398 \end{enumerate} 434 399 435 400 \subsubsection*{Recombination algorithms} 436 401 437 The next three jet algorithms rely on recombination schemes where calorimeter cell pairs are successively merged (\textit{E-scheme recombination}):402 The next three jet algorithms rely on recombination schemes where calorimeter cell pairs are successively merged: 438 403 439 404 % 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 $i$. … … 470 435 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. 471 436 472 437 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}. 439 440 473 441 \subsubsection*{Energy flow} 474 442 475 443 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} 476 444 %\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.} 477 , the energy of tracks pointing to calorimetric cells is extracted and smeared separately, before running the chosen jet reconstruction algorithm. This option allows a better jet $E$ reconstruction~\citep{qr:energyflow}.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}. 478 446 479 447 \subsection{$b$-tagging} … … 482 450 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}. 483 451 %\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.}. 484 The (mis)tagging relies on the true part icle identity (\textsc{PID}) of the most energetic particle within a cone around the observed$(\eta,\phi)$ 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.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. 485 453 486 454 \subsection{\texorpdfstring{$\tau$}{\texttau} identification} 487 455 488 456 Jets originating from $\tau$-decays are identified using a procedure consistent with the one applied in a full detector simulation~\citep{bib:cmsjetresolution}. 489 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}). Tracks are useful for this criterion.Secondly, the particles arisen from the $\tau$ lepton produce narrow jets in the calorimeter (this is defined as the jet \textit{collimation}).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}). 490 458 491 459 … … 521 489 \begin{table}[!h] 522 490 \begin{center} 523 \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 $E_T^\textrm{ tower}$ 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}.491 \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}. 524 492 \vspace{0.5cm} } 525 493 % \begin{tabular}[!h]{lll} … … 541 509 \multicolumn{3}{l}{\textbf{Electromagnetic collimation}} \\ 542 510 & $R^\textrm{em}$ & $0.15$\\ 543 & min $E_{T}^\textrm{ tower}$ & $1.0$~GeV\\511 & min $E_{T}^\textrm{cell}$ & $1.0$~GeV\\ 544 512 & $C_{\tau}$ & $0.95$\\ 545 513 \multicolumn{3}{l}{\textbf{Tracking isolation}} \\ … … 558 526 559 527 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. 560 To be taken into account, a calorimeter cell should have a transverse energy $E_T^\textrm{ tower}$ above a given threshold.528 To be taken into account, a calorimeter cell should have a transverse energy $E_T^\textrm{cell}$ above a given threshold. 561 529 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}). 562 530 … … 612 580 \end{equation} 613 581 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. 614 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 this document, \textsc{MET} is based on the calorimetric cells and only muons and neutrinos are not taken into account for its evaluation: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: 615 583 \begin{equation} 616 \overrightarrow{E_T}^\textrm{miss} = - \sum^\textrm{ towers}_i \overrightarrow{E_T}(i)584 \overrightarrow{E_T}^\textrm{miss} = - \sum^\textrm{cells}_i \overrightarrow{E_T}(i) 617 585 \end{equation} 618 586 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. … … 620 588 \section{Trigger emulation} 621 589 622 New physics in collider experiment are often characterised in phenomenology by low cross-section values, compared to the Standard Model (\textsc{SM}) processes. %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 $2 \times 10^{-3}~\textrm{nb}$ ($pp \rightarrow WH$, $m_H=115~\textrm{GeV}/c^2$). 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 $2 \times 10^{-3}~\textrm{nb}$ ($pp \rightarrow WH$, $m_H=115~\textrm{GeV}/c^2$). 623 592 624 593 %High statistics are required for data analyses, consequently imposing high luminosity, i.e.\ a high collision rate. 625 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.626 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.}.627 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.628 629 Most of the usual trigger algorithms select events containing objects (i.e.\ jets, particles, \textsc{MET}) with an energy scale above some threshold. This is often expressed in terms of a cut on the transverse momentum of one or several objects of the measured event. 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 $p_T^e > 50~\textrm{GeV}/c$.630 631 A trigger emulation is included in \textit{Delphes}, using a fully parametrisable \textit{trigger table} \citep{qr:triggercard} 632 %\footnote{\texttt{[code] }The trigger card is the \texttt{data/TriggerCard.dat} file.} 633 . When enabled, this trigger is applied on analysis-object data.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. 634 603 In a real experiment, the online selection is often divided into several steps (or \textit{levels}). 635 This splits the overall reduction factor into a product of smaller factors, corresponding to the different trigger levels.636 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.637 First-level triggers are thenfast and simple but based only on partial data as not all detector front-ends are readable within the decision latency.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. 638 607 Higher level triggers are more complex, of finer-but-not-final quality and based on full detector data. 639 608 … … 660 629 \begin{center} 661 630 \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. 662 The tagger acceptance is fully determined by the distance in the transverse plane of the detector to the real beam position~\citep{bib:hector}. It is expressed in terms of the particle energy ($E$). 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}. 632 It is expressed in terms of the particle energy ($E$). 663 633 All detectors are located on both sides of the interaction point. 664 634 \vspace{0.5cm}} … … 1004 974 1005 975 \bibitem{bib:delphes} \textit{Delphes}, \href{http://www.fynu.ucl.ac.be/delphes.html}{www.fynu.ucl.ac.be/delphes.html} 1006 \bibitem{bib:stdhep} L.A. Garren, M. Fischler, \href{http://cepa.fnal.gov/psm/stdhep/c++}{cepa.fnal.gov/psm/stdhep/c++}1007 \bibitem{bib:hepmc} M. Dobbs and J.B. Hansen, \textbf{Comput. Phys. Commun.} \href{http://dx.doi.org/10.1016/S0010-4655(00)00189-2}{134 (2001) 41}.1008 \bibitem{bib:lhe} J. Alwall, et al., \textbf{Comput. Phys. Commun.} \href{http://dx.doi.org/10.1016/j.cpc.2006.11.010}{176:300-304,2007}.1009 976 \bibitem{bib:Root} %\textsc{ROOT}, \textit{An Object Oriented Data Analysis Framework}, 1010 977 R. Brun, F. Rademakers, Nucl. Inst. \& Meth. in \textbf{Phys. Res. A} \href{http://dx.doi.org/10.1016/S0168-9002(97)00048-X}{389 (1997) 81-86}. … … 1044 1011 1045 1012 \bibitem{bib:mcfio} P. Lebrun, L. Garren, Copyright (c) 1994-1995 Universities Research Association, Inc. 1013 \bibitem{bib:stdhep} L.A. Garren, M. Fischler, \href{http://cepa.fnal.gov/psm/stdhep/c++}{cepa.fnal.gov/psm/stdhep/c++} 1014 \bibitem{bib:hepmc} M. Dobbs and J.B. Hansen, \textbf{Comput. Phys. Commun.} \href{http://dx.doi.org/10.1016/S0010-4655(00)00189-2}{134 (2001) 41}. 1015 \bibitem{bib:lhe} J. Alwall, et al., \textbf{Comput. Phys. Commun.} \href{http://dx.doi.org/10.1016/j.cpc.2006.11.010}{176:300-304,2007}. 1016 1046 1017 \end{thebibliography} 1047 1018 … … 1053 1024 \addcontentsline{toc}{section}{Internal code references} 1054 1025 1055 \bibitem[a]{qr:inputformat} See the following classes: \texttt{HEPEVTConverter}, \texttt{HepMCConverter}, \texttt{LHEFConverter}, \texttt{STDHEPConverter} and \texttt{DelphesRootConverter}. 1056 1057 \bibitem[b]{qr:invisibleparticles} The list of particles considered as invisible is accessible in the \texttt{PdgParticle} class. This list currently contains the PIDs 12, 14, 16, 1000022, 1000023, 1000025, 1000035 and 1000045, in absolute values. 1026 \bibitem[a]{qr:inputformat} 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'' (LHEF~\citep{bib:lhe}) and \texttt{*.root} files obtained from \texttt{*.hbook} using the \texttt{h2root} utility from the ROOT framework~\citep{bib:Root}. 1027 See the following classes: \texttt{HEPEVTConverter}, \texttt{HepMCConverter}, \texttt{LHEFConverter}, \texttt{STDHEPConverter} and \texttt{DelphesRootConverter}. 1028 1029 \bibitem[b]{qr:outputformat} The ROOT output files are created using the \texttt{ExRootAnalysis} utility~\citep{bib:ExRootAnalysis}. Generator-level data are located under the \texttt{GEN} tree, the analysis data objects after reconstruction under the \texttt{Analysis} tree, and the results of the trigger emulation under the \texttt{Trigger} tree. 1058 1030 1059 1031 \bibitem[c]{qr:lhco} Set the \texttt{FLAG\_LHCO} variable to $1$ or $0$ in the detector card to switch on/off the creation of \texttt{*.lhco} output file. 1060 1032 1061 \bibitem[d]{qr:detectorcard}The detector card is the \texttt{data/DetectorCard.dat} file. This file is parsed by the \texttt{SmearUtil} class. 1062 1063 \bibitem[e]{qr:datacards} Detector and trigger cards for the \textsc{ATLAS} and \textsc{CMS} experiments are also provided in \texttt{data/} directory. 1064 1065 \bibitem[f]{qr:resolutionterms}The resolution terms in the detector card are named \texttt{ELG\_Xyyy} or \texttt{HAD\_Xyyy}, refering to electromagnetic and hadronic terms (resp.); \texttt{X} is replaced by \texttt{S}, \texttt{N}, \texttt{C} for the stochastic, noise and constant terms; and finally \texttt{yyy} is \texttt{cen} for central part, \texttt{ec} for end-caps, \texttt{fwd} for the forward calorimeters and \texttt{zdc} for the zero-degree calorimeters. 1066 1067 \bibitem[g]{qr:magneticfield} See the \texttt{TrackPropagation} class. 1068 1069 \bibitem[h]{qr:tracks} See the \texttt{TRACK\_eff} and \texttt{TRACK\_ptmin} terms in the detector card. 1070 1071 \bibitem[i]{qr:energysmearing} The response of the detector is applied to the electromagnetic and the hadronic particles through the \texttt{SmearElectron} and \texttt{SmearHadron} methods in the \texttt{SmearUtil} class. 1072 1073 \bibitem[j]{qr:emhadratios} To implement different ratios for other particles, see the \texttt{BlockClasses} class. 1074 1075 \bibitem[k]{qr:calorimetriccells} As the detector is assumed to be cylindrical (e.g.\ symmetric in $\phi$ and with respect to the $\eta=0$ plane), the detector card stores the number of calorimetric cells with $\phi=0$ and $\eta>0$ (default: $40$ cells). For a given $\eta$, the size of the $\phi$ segmentation is also specified. See the \texttt{TOWER\_number}, \texttt{TOWER\_eta\_edges} and \texttt{TOWER\_dphi} variables in the detector card. 1076 1077 \bibitem[l]{qr:analysistree} All these processed data are located under the \texttt{Analysis} tree. 1078 1079 \bibitem[m]{qr:muonsmearing} See the \texttt{SmearMuon} method in the \texttt{SmearUtil} class. 1080 1081 \bibitem[n]{qr:isolflag} 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. 1082 1083 \bibitem[o]{qr:caloisolation} Calorimetric isolation parameters in the detector card are \texttt{ISOL\_Calo\_ET} and \texttt{ISOL\_Calo\_Grid} in the detector card. 1084 1085 \bibitem[p]{qr:fwdneutrals} These thresholds are defined by the \texttt{ZDC\_gamma\_E} and \texttt{ZDC\_n\_E} variables in the detector card. 1086 1087 \bibitem[q]{qr:jetalgo} The choice is done by allocating the \texttt{JET\_jetalgo } input parameter in the detector card. 1088 1089 \bibitem[r]{qr:ptcutjet} See the \texttt{PTCUT\_jet }variable in the detector card. 1090 1091 \bibitem[s]{qr:jetparams} See the \texttt{JET\_coneradius} and \texttt{JET\_seed} variables in the detector card. The existing FastJet code has been modified to allow easy modification of the cell pattern in $(\eta, \phi)$ space. 1033 \bibitem[d]{qr:invisibleparticles} The list of particles considered as invisible is accessible in the \texttt{PdgParticle} class. This list currently contains the PIDs 12, 14, 16, 1000022, 1000023, 1000025, 1000035 and 1000045, in absolute values. 1034 1035 \bibitem[e]{qr:detectorcard}The detector card is the \texttt{data/DetectorCard.dat} file. This file is parsed by the \texttt{SmearUtil} class. 1036 1037 \bibitem[f]{qr:datacards} Detector and trigger cards for the \textsc{ATLAS} and \textsc{CMS} experiments are also provided in \texttt{data/} directory. 1038 1039 \bibitem[g]{qr:resolutionterms}The resolution terms in the detector card are named \texttt{ELG\_Xyyy} or \texttt{HAD\_Xyyy}, refering to electromagnetic and hadronic terms (resp.); \texttt{X} is replaced by \texttt{S}, \texttt{N}, \texttt{C} for the stochastic, noise and constant terms; and finally \texttt{yyy} is \texttt{cen} for central part, \texttt{ec} for end-caps, \texttt{fwd} for the forward calorimeters and \texttt{zdc} for the zero-degree calorimeters. 1040 1041 \bibitem[h]{qr:magneticfield} See the \texttt{TrackPropagation} class. 1042 1043 \bibitem[i]{qr:tracks} See the \texttt{TRACK\_eff} and \texttt{TRACK\_ptmin} terms in the detector card. 1044 1045 \bibitem[j]{qr:energysmearing} The response of the detector is applied to the electromagnetic and the hadronic particles through the \texttt{SmearElectron} and \texttt{SmearHadron} methods in the \texttt{SmearUtil} class. 1046 1047 \bibitem[k]{qr:emhadratios} To implement different ratios for other particles, see the \texttt{BlockClasses} class. 1048 1049 \bibitem[l]{qr:calorimetriccells} As the detector is assumed to be cylindrical (e.g.\ symmetric in $\phi$ and with respect to the $\eta=0$ plane), the detector card stores the number of calorimetric cells with $\phi=0$ and $\eta>0$ (default: $40$ cells). For a given $\eta$, the size of the $\phi$ segmentation is also specified. See the \texttt{TOWER\_number}, \texttt{TOWER\_eta\_edges} and \texttt{TOWER\_dphi} variables in the detector card. 1050 1051 \bibitem[m]{qr:analysistree} All these processed data are located under the \texttt{Analysis} tree. 1052 1053 \bibitem[n]{qr:muonsmearing} See the \texttt{SmearMuon} method in the \texttt{SmearUtil} class. 1054 1055 \bibitem[o]{qr:isolflag} 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. 1056 1057 \bibitem[p]{qr:caloisolation} Calorimetric isolation parameters in the detector card are \texttt{ISOL\_Calo\_ET} and \texttt{ISOL\_Calo\_Grid} in the detector card. 1058 1059 \bibitem[q]{qr:fwdneutrals} These thresholds are defined by the \texttt{ZDC\_gamma\_E} and \texttt{ZDC\_n\_E} variables in the detector card. 1060 1061 \bibitem[r]{qr:jetalgo} The choice is done by allocating the \texttt{JET\_jetalgo } input parameter in the detector card. 1062 1063 \bibitem[s]{qr:ptcutjet} See the \texttt{PTCUT\_jet }variable in the detector card. 1064 1065 \bibitem[t]{qr:jetparams} See the \texttt{JET\_coneradius} and \texttt{JET\_seed} variables in the detector card. The existing FastJet code has been modified to allow easy modification of the cell pattern in $(\eta, \phi)$ space. 1092 1066 In following versions of \textit{Delphes}, a new dedicated plug-in will be created on this purpose. 1093 1067 1094 \bibitem[ t]{qr:energyflow} 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.1095 1096 \bibitem[ u]{qr:btag} Corresponding to the \texttt{BTAG\_b}, \texttt{BTAG\_mistag\_c} and \texttt{BTAG\_mistag\_l} constants, for the efficiency of tagging of a $b$-jet, the efficiency of mistagging a $c$-jet as a $b$-jet, and the1068 \bibitem[u]{qr:energyflow} 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. 1069 1070 \bibitem[v]{qr:btag} Corresponding to the \texttt{BTAG\_b}, \texttt{BTAG\_mistag\_c} and \texttt{BTAG\_mistag\_l} constants, for the efficiency of tagging of a $b$-jet, the efficiency of mistagging a $c$-jet as a $b$-jet, and the 1097 1071 efficiency of mistagging a light jet ($u$,$d$,$s$,$g$) as a $b$-jet. 1098 1072 1099 \bibitem[ v]{qr:taujets} See the following parameters in the detector card:\\1100 \texttt{TAU\_energy\_scone } for $R^\textrm{em}$; \texttt{JET\_M\_seed } for min $E_{T}^\textrm{ tower}$;1073 \bibitem[w]{qr:taujets} See the following parameters in the detector card:\\ 1074 \texttt{TAU\_energy\_scone } for $R^\textrm{em}$; \texttt{JET\_M\_seed } for min $E_{T}^\textrm{cell}$; 1101 1075 \texttt{TAU\_energy\_frac} for $C_{\tau}$; \texttt{TAU\_track\_scone} for $R^\textrm{tracks}$; 1102 1076 \texttt{PTAU\_track\_pt } for min $p_T^\textrm{tracks}$ and \texttt{TAUJET\_pt} for $\min p_T$. 1103 1077 1104 1078 1105 \bibitem[ w]{qr:triggercard} The trigger card is the \texttt{data/TriggerCard.dat} file. Default trigger files are also available for CMS-like and ATLAS-like detectors1106 1107 \bibitem[ x]{qr:protontaggers} The resolution is defined by the \texttt{RP220\_T\_resolution} and \texttt{RP420\_T\_resolution} parameters in the detector card.1108 1109 \bibitem[ y]{qr:frog} To prepare the visualisation, the \texttt{FLAG\_FROG} parameter should be equal to $1$.1079 \bibitem[x]{qr:triggercard} The trigger card is the \texttt{data/TriggerCard.dat} file. Default trigger files are also available for CMS-like and ATLAS-like detectors 1080 1081 \bibitem[y]{qr:protontaggers} The resolution is defined by the \texttt{RP220\_T\_resolution} and \texttt{RP420\_T\_resolution} parameters in the detector card. 1082 1083 \bibitem[z]{qr:frog} To prepare the visualisation, the \texttt{FLAG\_FROG} parameter should be equal to $1$. 1110 1084 1111 1085 \end{thebibliography}
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