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Timestamp:
Feb 27, 2009, 12:13:11 AM (16 years ago)
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Xavier Rouby
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including dde's comment

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    r208 r279  
    2828  \graphicspath{{all_png/}}
    2929  \pdfinfo{
    30    /Author (S. Ovyn, X. Rouby)
    31    /Title  (Delphes, a framework for fast simulation of a general purpose LHC detector)
     30   /Author (S. Ovyn, X. Rouby, V. Lemaitre)
     31   /Title  (Delphes, a framework for fast simulation of a general-purpose LHC detector)
    3232   /Subject ()
    3333   /Keywords (Delphes, Fast simulation, LHC, FROG, Hector, Smearing, FastJet)}
     
    3737\fi
    3838
    39 %\title{\textsc{Delphes}, a framework for fast simulation \\of a general purpose \textsc{lhc} detector}
    4039\title{\textsc{Delphes}, a framework for fast simulation \\of a generic collider experiment}
    41 \author{S. Ovyn and X. Rouby$^\textrm{a}$\\
     40\author{S. Ovyn, X. Rouby$^\textrm{a}$ and V. Lema\^itre\\
    4241        \small{Center for Particle Physics and Phenomenology (CP3)}\\
    4342        \small{Universit\'e catholique de Louvain}\\
    4443        \small{B-1348 Louvain-la-Neuve, Belgium}\\ \\
    4544        \texttt{severine.ovyn@uclouvain.be, xavier.rouby@cern.ch} \\
     45        \texttt{vincent.lemaitre@uclouvain.be} \\
    4646}
    4747\date{}
     
    5959
    6060\begin{abstract}
    61 It is always delicate to  know whether theoretical predictions are visible and measurable in a high energy experiment due to the complexity of the related detectors, data acquisition chain and software.
    62 %Knowing whether theoretical predictions are visible and measurable in a high energy experiment is always delicate due to the complexity of the related detectors, data acquisition chain and software.
    63 We introduce here a new framework, \textsc{Delphes}, for fast simulation of
    64 a general purpose experiment. The simulation includes a tracking system, embedded into a magnetic field, calorimetry and a muon
     61It 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.
     62We introduce here a new \texttt{C++}-basedframework, \textsc{Delphes}, for fast simulation of
     63a general-purpose experiment. The simulation includes a tracking system, embedded into a magnetic field, calorimetry and a muon
    6564system, and possible very forward detectors arranged along the beamline.
    6665The framework is interfaced to standard file formats (e.g. Les Houches Event File) and outputs observable objects for analysis, like missing transverse energy and collections of electrons or jets.
    67 The simulation of detector response takes into account the detector resolution, and usual reconstruction algorithms, like \textsc{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 \textsc{Hector} software. Finally, the \textsc{Frog} 2D/3D event display is used for visualisation of the collision final states.
    68 An overview of \textsc{Delphes} is given as well as a few use-cases for illustration.
     66The simulation of detector response takes into account the detector resolution, and usual reconstruction algorithms, such as \textsc{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 \textsc{Hector} software. Finally, the \textsc{Frog} 2D/3D event display is used for visualisation of the collision final states.
     67An overview of \textsc{Delphes} is given as well as a few \textsc{lhc} use-cases for illustration.
    6968\vspace{0.5cm}
    7069
     
    8685% - 3) permet de comparer
    8786
    88 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. These detectors differ with their principles, technologies, geometries 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, but based only on partially processed data. Finally, in terms of the experiment software, with different data formats (like \textit{raw} or \textit{reconstructed} data), many reconstruction algorithms and particle identification schemes.
    89 
    90 This complexity is handled by large collaborations of thousands of people, but the data and the expertise are only available to their members. Real data analyses require a full detector simulation, including the various detector inefficiencies, the dead material, the imperfections and the geometrical details. Moreover, detector calibration and alignment are crucial. Such simulation is very complicated, technical and 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 observables.
    91 
    92 A new framework, called \textsc{Delphes}~\cite{bib:Delphes}, is introduced here, for the fast simulation of a general purpose collider experiment.
     87Experiments 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.
     88
     89This complexity is handled by large collaborations of thousands of people, but the data and the expertise are only available to their members. Real 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. Moreover, control of the detector calibration and alignment are crucial. 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 signals and associated backgrounds.
     90
     91A new framework, called \textsc{Delphes}~\cite{bib:Delphes}, is introduced here, for the fast simulation of a general-purpose collider experiment.
    9392Using the framework, observables can be estimated for specific signal and background channels, as well as their production and measurement rates.
    94 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\footnote{throughout the paper, final state particles refer as particles considered as stable by the event generator.}. Tracks of charged particles and deposits of energy in calorimetric cells (or \textit{calotowers}) are then created.
    95 
    96 \textsc{Delphes} includes the most crucial experimental features, like
     93Starting 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\footnote{throughout the paper, final-state particles refer as particles considered as stable by the event generator.}. Tracks of charged particles and deposits of energy in calorimetric cells (or \textit{calotowers}) are then created.
     94
     95\textsc{Delphes} includes the most crucial experimental features, such as (Fig.~\ref{fig:FlowChart}):
    9796\begin{enumerate}
    98 \item the geometry of both central or forward detectors,
     97\item the geometry of both central and forward detectors,
     98\item magnetic field for tracks
    9999\item reconstruction of photons, leptons, jets, $b$-jets, $\tau$-jets and missing transverse energy,
    100100\item lepton isolation,
    101101\item trigger emulation,
    102 \item an event display (Fig.~\ref{fig:FlowChart}, at the end).
     102\item an event display.
    103103\end{enumerate}
    104104
    105 \begin{figure*}[t]
    106 \begin{center}
    107 %\includegraphics[width=0.9\textwidth]{FlowDelphes}
     105\begin{figure*}[!ht]
     106\begin{center}
    108107\includegraphics[scale=0.78]{FlowDelphes}
    109 \caption{Flow chart describing the principles behind \textsc{Delphes}. Event files coming from external Monte Carlo generators are read by a converter stage.
    110 The kinematics variables of the final state particles are then smeared according to the subdetector resolutions.
    111 Tracks are reconstructed in a simulated dipolar magnetic field and calorimetric towers sample the energy deposits. Based on these, dedicated algorithms are applied for particle identification, isolation and reconstruction.
    112 The transport of very forward particle to the near-beam detectors is also simulated.
    113 Finally, an output file is written, including generator level and analysis object data. If requested, a fully parametrisable trigger can be emulated. Optionally, the geometry and visualisation files for the 3D event display can also be produced.
     108\caption{Flow chart describing the principles behind \textsc{Delphes}. Event files coming from external Monte Carlo generators are read by a converter stage (top).
     109The kinematics variables of the final-state particles are then smeared according to the tunable subdetector resolutions.
     110Tracks are reconstructed in a simulated dipolar magnetic field and calorimetric towers sample the energy deposits. Based on these low-level objects, dedicated algorithms are applied for particle identification, isolation and reconstruction.
     111The transport of very forward particles to the near-beam detectors is also simulated.
     112Finally, an output file is written, including generator-level and analysis-object data. If requested, a fully parametrisable trigger can be emulated. Optionally, the geometry and visualisation files for the 3D event display can also be produced.
    114113All user parameters are set in the \textit{Smearing Card} and the \textit{Trigger Card}. }
    115114\label{fig:FlowChart}
     
    119118Although this kind of approach yields much realistic results than a simple ``parton-level" analysis, a fast simulation comes with some limitations. Detector geometry is idealised, being uniform, symmetric around the beam axis, and having no cracks nor dead material. Secondary interactions, multiple scatterings, photon conversion and bremsstrahlung are also neglected.
    120119
    121 %The simulation package proceeds in two stages. The first part is executed on the generated events. ``Particle-level" informations are read from input files and stored in a {\it \textsc{gen}} \textsc{root} tree.
    122 
    123 Three formats of input files can be used as input in \textsc{Delphes}\footnote{\texttt{[code] }See the \texttt{HEPEVTConverter}, \texttt{LHEFConverter} and \texttt{STDHEPConverter} classes.}. In order to process events from many different generators, the standard Monte Carlo event structure \texttt{StdHEP}~\cite{bib:stdhep} can be used as an input. Besides, \textsc{Delphes} can also provide detector response for events read in ``Les Houches Event Format'' (\textsc{lhef}~\cite{bib:lhe}) and \textsc{root} files obtained using the \texttt{h2root} utility from the \textsc{root} framework~\cite{bib:Root}.
     120Three dataformat files can be used as input in \textsc{Delphes}\footnote{\texttt{[code] }See the \texttt{HEPEVTConverter}, \texttt{LHEFConverter} and \texttt{STDHEPConverter} classes.}. In order to process events from many different generators, the standard Monte Carlo event structure \texttt{StdHEP}~\cite{bib:stdhep} can be used as an input. Besides, \textsc{Delphes} can also provide detector response for events read in ``Les Houches Event Format'' (\textsc{lhef}~\cite{bib:lhe}) and \textsc{root} files obtained from \textsc{.hbook} using the \texttt{h2root} utility from the \textsc{root} framework~\cite{bib:Root}.
    124121%Afterwards, \textsc{Delphes} performs a simple trigger simulation and reconstruct "high-level objects". These informations are organised in classes and each objects are ordered with respect to the transverse momentum.
    125122
    126123\textsc{Delphes} uses the \texttt{ExRootAnalysis} utility~\cite{bib:ExRootAnalysis} to create output data in a \texttt{*.root} ntuple.
    127 This output contains a copy of the generator level data (\textsc{gen} tree), the analysis data objects after reconstruction (\mbox{\textsc{A}nalysis} tree), and possibly the results of the trigger emulation (\mbox{\textsc{T}rigger} tree). The program is driven by input cards. The detector card (\texttt{data/DataCardDet.dat}) allows a large spectrum of running conditions by modifying basic detector parameters, including calorimeter and tracking coverage and resolution, thresholds or jet algorithm parameters. The trigger card (\texttt{data/trigger.dat}) lists the user algorithms for the simplified online preselection.\\
     124This output contains a copy of the generator-level data (\textsc{gen} tree), the analysis data objects after reconstruction (\mbox{\textsc{A}nalysis} tree), and possibly the results of the trigger emulation (\mbox{\textsc{T}rigger} tree). The program is driven by input cards. The detector card (\texttt{data/DataCardDet.dat}) allows a large spectrum of running conditions by modifying basic detector parameters, including calorimeter and tracking coverage and resolution, thresholds or jet algorithm parameters. The trigger card (\texttt{data/trigger.dat}) lists the user algorithms for the simplified online preselection.\\
    128125
    129126
    130127\section{Detector simulation}
    131128
    132 The overall layout of the general purpose detector simulated by \textsc{Delphes} is shown in Fig.~\ref{fig:GenDet3}.
     129The overall layout of the general-purpose detector simulated by \textsc{Delphes} is shown in Fig.~\ref{fig:GenDet3}.
    133130A central tracking system (\textsc{tracker}) is surrounded by an electromagnetic and a hadron calorimeters (\textsc{ecal} and \textsc{hcal}, resp.). 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
    134131The fast simulation of the detector response takes into account geometrical acceptance of sub-detectors and their finite resolution, as defined in the smearing data card\footnote{\texttt{[code] }See the \texttt{RESOLution} class.}.
    135 If no such file is provided, predefined values are used. The coverage of the various subsystems used in the default configuration are summarised in Tab.~\ref{tab:defEta}.
     132If no such file is provided, predefined values based on ``typical'' \textsc{cms} acceptances and resolutions are used. The geometrical coverage of the various subsystems used in the default configuration are summarised in Tab.~\ref{tab:defEta}.
    136133
    137134\begin{table*}[t]
    138135\begin{center}
    139 \caption{Default extension in pseudorapidity $\eta$ of the different subdetectors.
     136\caption{Default extension in pseudorapidity $\eta$ of the different subdetectors.
     137Full azimuthal ($\phi$) acceptance is assumed.
    140138The corresponding parameter name, in the smearing card, is given. \vspace{0.5cm}}
    141 \begin{tabular}{lll}
     139\begin{tabular}{llcc}
    142140\hline
    143 \textsc{tracker} & {\verb CEN_max_tracker } & $0.0 \leq |\eta| \leq 2.5$\\
    144 \textsc{ecal}, \textsc{hcal} & {\verb CEN_max_calo_cen } & $0.0 \leq |\eta| \leq 3.0$\\
    145 \textsc{fcal} & {\verb CEN_max_calo_fwd } & $3.0 \leq |\eta| \leq5.0$\\
    146 \textsc{muon} & {\verb CEN_max_mu } & $0.0 \leq |\eta| \leq 2.4$\\\hline
     141Subdetector & & $\eta$ & $\phi$ \\
     142\textsc{tracker}        & {\verb CEN_max_tracker }      & $[-2.5; 2.5]$         & $[-\pi ; \pi]$\\
     143\textsc{ecal}, \textsc{hcal} & {\verb CEN_max_calo_cen }& $[-3.0 ; 3.0]$        & $[-\pi ; \pi]$\\
     144\textsc{fcal}           & {\verb CEN_max_calo_fwd }     & $[-5 ; 3]$ \& $[3 ;5]$     & $[-\pi ; \pi]$\\
     145\textsc{muon}           & {\verb CEN_max_mu }           & $[-2.4 ; 2.4]$        & $[-\pi ; \pi]$\\ \hline
    147146\end{tabular}
    148147\label{tab:defEta}
     
    171170\subsection{Tracks reconstruction}
    172171Every stable charged particle with a transverse momentum above some threshold and lying inside the detector volume covered by the tracker provides a track.
    173 By default, a track is assumed to be reconstructed with $90\%$ probability\footnote{\texttt{[code]} The reconstruction efficiency is defined in the smearing datacard by the \texttt{TRACKING\_EFF} term.} if its transverse momentum $p_T$ is higher than $0.9~\textrm{GeV}$ and if its pseudorapidity $|\eta| \leq 2.5$.
     172By default, a track is assumed to be reconstructed with $90\%$ probability\footnote{\texttt{[code]} The reconstruction efficiency is defined in the smearing datacard by the \texttt{TRACKING\_EFF} term.} if its transverse momentum $p_T$ is higher than $0.9~\textrm{GeV}/c$ and if its pseudorapidity $|\eta| \leq 2.5$.
    174173
    175174
     
    182181\label{eq:caloresolution}
    183182\end{equation}
    184 where $S$, $N$ and $C$ are the \textit{stochastic}, \textit{noise} and \textit{constant} terms, respectively.\\
     183where $S$, $N$ and $C$ are the \textit{stochastic}, \textit{noise} and \textit{constant} terms, respectively, and $\oplus$ stands for quadractic additions.\\
    185184
    186185
    187186The particle four-momentum $p^\mu$ are smeared with a parametrisation directly derived from typical detector technical designs\footnote{\texttt{[code] }~\cite{bib:cmsjetresolution,bib:ATLASresolution}. The response of the detector is applied to the electromagnetic and the hadronic particles through the \texttt{SmearElectron} and \texttt{SmearHadron} functions.}.
    188 In the default parametrisation, the calorimeter is assumed to cover the pseudorapidity range $|\eta|<3$ and consists in an electromagnetic and an hadronic part. Coverage between pseudorapidities of $3.0$ and $5.0$ is provided by forward calorimeters, with different response to electromagnetic objects ($e^\pm, \gamma$) or hadrons.
    189 Muons and neutrinos are assumed not to interact with the calorimeters\footnote{In the current \textsc{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 subsequently be handled with care.}.
    190 The default values of the stochastic, noisy and constant terms are given in Tab.~\ref{tab:defResol}.\\
     187In 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.
     188Muons and neutrinos are assumed not to interact with the calorimeters\footnote{In the current \textsc{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.}.
     189The default values of the stochastic, noise and constant terms are given in Tab.~\ref{tab:defResol}.\\
    191190
    192191\begin{table}[!h]
     
    194193\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}).
    195194The corresponding parameter name, in the smearing card, is given. \vspace{0.5cm}}
    196 \begin{tabular}[!h]{lclc}
     195\begin{tabular}[!h]{lllc}
    197196\hline
    198197\multicolumn{2}{c}{Resolution Term}   & Card flag & Value\\\hline
    199198 \multicolumn{4}{l}{\textsc{ecal}} \\
    200         & $S$ & {\verb ELG_Scen }  & $0.05$ \\
    201         & $N$ & {\verb ELG_Ncen }  & $0.25$ \\
     199        & $S$ (GeV$^{1/2}$) & {\verb ELG_Scen }  & $0.05$ \\
     200        & $N$ (GeV)& {\verb ELG_Ncen }  & $0.25$ \\
    202201        & $C$ & {\verb ELG_Ccen }  & $0.0055$ \\
    203202 \multicolumn{4}{l}{\textsc{fcal}, electromagnetic part} \\
    204         & $S$ & {\verb ELG_Sfwd }  & $2.084$ \\
    205         & $N$ & {\verb ELG_Nfwd }  & $0$ \\
     203        & $S$ (GeV$^{1/2}$)& {\verb ELG_Sfwd }  & $2.084$ \\
     204        & $N$ (GeV)& {\verb ELG_Nfwd }  & $0$ \\
    206205        & $C$ & {\verb ELG_Cfwd }  & $0.107$ \\
    207206 \multicolumn{4}{l}{\textsc{hcal}} \\
    208         & $S$ & {\verb HAD_Shcal } & $1.5$ \\
    209         & $N$ & {\verb HAD_Nhcal } & $0$\\
     207        & $S$ (GeV$^{1/2}$)& {\verb HAD_Shcal } & $1.5$ \\
     208        & $N$ (GeV)& {\verb HAD_Nhcal } & $0$\\
    210209        & $C$ & {\verb HAD_Chcal } & $0.05$\\
    211210 \multicolumn{4}{l}{\textsc{fcal}, hadronic part} \\
    212         & $S$ & {\verb HAD_Shf }   & $2.7$\\
    213         & $N$ & {\verb HAD_Nhf }   & $0$. \\
     211        & $S$ (GeV$^{1/2}$)& {\verb HAD_Shf }   & $2.7$\\
     212        & $N$ (GeV)& {\verb HAD_Nhf }   & $0$. \\
    214213        & $C$ & {\verb HAD_Chf }   & $0.13$\\
    215214\hline
     
    219218\end{table}
    220219
    221 The energy of electrons and photons found in the particle list are smeared using the \textsc{ecal} resolution terms. Charged and neutral final state hadrons interact with the \textsc{ecal}, \textsc{hcal} and \textsc{fcal}.
    222 Some long-living particles, such as the $K^0_s$, possessing lifetime $c\tau$ smaller than $10~\textrm{mm}$ are considered as stable particles 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
     220The energy of electrons and photons found in the particle list are smeared using the \textsc{ecal} resolution terms. Charged and neutral final-state hadrons interact with the \textsc{ecal}, \textsc{hcal} and \textsc{fcal}.
     221Some 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 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
    223222\begin{equation}
    224223\left\{
     
    229228\right.
    230229\end{equation}
    231 where $0 \leq F \leq 1$. The electromagnetic part is handled as the same way as the electrons. The resulting 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 worth $0.7$.\\
     230where $0 \leq F \leq 1$. The electromagnetic part is handled the same way for the electrons and photons.
     231The 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 $0.7$.\\
    232232
    233233\subsection{Calorimetric towers}
    234234
    235 The smallest unit for geometrical sampling of the calorimeters is a \textit{tower}; it segments the $(\eta,\phi)$ plane for the energy measurement. No longitudinal segmentation is available in the simulated calorimeters. All undecayed particles, except muons and neutrinos produce a calorimetric tower, either in \textsc{ecal}, in \textsc{hcal} or \textsc{fcal}.
     235The smallest unit for geometrical sampling of the calorimeters is a \textit{tower}; it segments the $(\eta,\phi)$ plane for the energy measurement. No longitudinal segmentation is available in the simulated calorimeters. All undecayed particles, except muons and neutrinos deposit energy in a calorimetric tower, either in \textsc{ecal}, in \textsc{hcal} or \textsc{fcal}.
    236236As the detector is assumed to be cylindical (e.g. symmetric in $\phi$ and with respect to the $\eta=0$ plane), the smearing card stores the number of calorimetric towers with $\phi=0$ and $\eta>0$ (default: $40$ towers). For a given $\eta$, the size of the $\phi$ segmentation is also specified. Fig.~\ref{fig:calosegmentation} illustrates the default segmentation of the $(\eta,\phi)$ plane.
    237237
     
    239239\begin{center}
    240240\includegraphics[width=\columnwidth]{calosegmentation}
    241 \caption{Default segmentation of the calorimeters in the $(\eta,\phi)$ plane. Only the central detectors (\textsc{ecal}, \textsc{hcal} and \textsc{fcal}) are considered.}
     241\caption{Default segmentation of the calorimeters in the $(\eta,\phi)$ plane. Only the central detectors (\textsc{ecal}, \textsc{hcal}) and \textsc{fcal} are considered.}
    242242\label{fig:calosegmentation}
    243243\end{center}
     
    249249
    250250Most 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.
    251 Zero Degree Calorimeters (\textsc{zdc}) are located at zero angle, i.e. are aligned with the beamline axis at the interaction point, and placed at the distance where the paths of incoming and outgoing beams separate (Fig.~\ref{fig:fdets}). 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{cms}).
    252 Forward taggers (called here \textsc{rp220} and \textsc{fp420} as at the \textsc{lhc}) are meant for the measurement of particles following very closely the beam path. To be able to reach these detectors, such particles must have a charge identical to the beam particles, and a momentum very close to the nominal value for 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}).
     251Zero Degree Calorimeters (\textsc{zdc}) are located at zero angle, i.e. are aligned with the beamline axis at the interaction point, and placed beyond the point where the paths of incoming and outgoing beams separate (Fig.~\ref{fig:fdets}). 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}).
     252Forward 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. To be able to reach these detectors, such particles must have a charge identical to the beam particles, and a momentum very close to the nominal value for 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}).
    253253
    254254\begin{figure}[!h]
     
    257257\caption{Default location of the very forward detectors, including \textsc{zdc}, \textsc{rp220} and \textsc{fp420} in the \textsc{lhc} beamline.
    258258Incoming (red) and outgoing (black) beams on one side of the interaction point ($s=0~\textrm{m}$).
    259 The Zero Degree Calorimeter is located in perfect alignment with the beamline axis at the interaction point, at $140~\textrm{m}$, where the beam paths are separated. The forward taggers are near-beam detectors located at $220~\textrm{m}$ and $420~\textrm{m}$. Beamline simulation with \textsc{Hector}~\cite{bib:Hector}.}
     259The 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 \textsc{Hector}~\cite{bib:Hector}.}
    260260\label{fig:fdets}
    261261\end{center}
     
    264264\begin{table*}[t]
    265265\begin{center}
    266 \caption{Default parameters for the forward detectors: distance from the interaction point and detector acceptance. The \textsc{lhc} beamline is assumed around the fifth interaction point. For the \textsc{zdc}, the acceptance depends only on the pseudorapidity $\eta$ of the particle, which should be neutral and stable.
    267 The tagger acceptance is fully determined by the distance in the transverse plane of the detector to the real beam position~\cite{bib:Hector}. It is expressed in terms of the particle energy.
     266\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.
     267The tagger acceptance is fully determined by the distance in the transverse plane of the detector to the real beam position~\cite{bib:Hector}. It is expressed in terms of the particle energy ($E$).
    268268\vspace{0.5cm}}
    269269\begin{tabular}{llcl}
    270270\hline
    271 Detector & Distance & Acceptance & \\ \hline
     271Detector & Distance from \textsc{ip}& Acceptance & \\ \hline
    272272\textsc{zdc}   & $140$ m & $|\eta|> 8.3$       & for $n$ and $\gamma$\\
    273273\textsc{rp220} & $220$ m & $E \in [6100 ; 6880]$ (GeV) & at $2~\textrm{mm}$\\
     
    280280
    281281
    282 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 \textsc{Hector} software~\cite{bib:Hector}, which includes the chromaticity effects and the geometrical aperture of the beamline elements.
     282While 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 \textsc{Hector} software~\cite{bib:Hector}, which includes the chromaticity effects and the geometrical aperture of the beamline elements of any arbitrary collider.
    283283
    284284Some subdetectors have the ability to measure the time of flight of the particle.
    285 This corresponds to the delay after which the particle is observed in the detector, after the bunch crossing. The time of flight measurement of \textsc{zdc} and \textsc{fp420} detector is implemented here. For the \textsc{zdc}, the formula is simply
     285This corresponds to the delay after which the particle is observed in the detector, with respect to the bunch crossing reference time at the interaction point ($t_0$). The time of flight measurement of \textsc{zdc} and \textsc{fp420} detector is implemented here. For the \textsc{zdc}, the formula is simply
    286286\begin{equation}
    287287 t = t_0 + \frac{1}{v} \times \Big( \frac{s-z}{\cos \theta}\Big),
     
    307307From 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.
    308308\subsubsection*{Electrons and photons}
    309 Photon and electron ($e^\pm$) candidates are reconstructed if they fall into the acceptance of the tracking system and have a transverse momentum above a threshold (default $p_T > 10~\textrm{GeV}$). A calorimetric tower will be seen in the detector, an electrons leave in addition a track. Consequently, electrons and photons creates as usual a candidate in the jet collection.
     309Electron ($e^\pm$) and photon candidates are reconstructed 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 tower will be seen in the detector, an electrons will leave in addition a track. Subsequently, electrons and photons create a candidate in the jet collection.
    310310
    311311\subsubsection*{Muons}
    312312
    313 Generator level muons entering the detector acceptance are considered as candidates for the analysis level.
    314 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 : $p_T > 10~\textrm{GeV}$) and of the pseudorapidity coverage of the muon system of the detector (default: $-2.4 \leq \eta \leq 2.4$).
     313Generator-level muons entering the detector acceptance are considered as candidates for the analysis level.
     314The 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: $-2.4 \leq \eta \leq 2.4$).
    315315The application of the detector resolution on the muon momentum depends on a Gaussian smearing of the $p_T$ variable\footnote{\texttt{[code]} See the \texttt{SmearMuon} method.}. Neither $\eta$ nor $\phi$ variables are modified beyond the calorimeters: no additional magnetic field is applied. In addition, multiple scattering is also neglected. This implies that low energy muons have in \textsc{Delphes} a better resolution than in a real detector. Moreover, muons leave no deposit in calorimeters.
    316316
    317317\subsubsection*{Charged lepton isolation}
    318318
    319 To improve the quality of the contents of the charged lepton collections, additional criteria can be applied to impose some isolation. This requires that electron or muon candidates are isolated in the detector from any other particle, within a small cone. In \textsc{Delphes}, charged lepton isolation demands that there is no other charged particle with $p_T>2~\textrm{GeV}$ within a cone of $\Delta R = \sqrt{\Delta \eta^2 + \Delta \phi^2} <0.5$ around the lepton. The result (i.e. \textit{isolated} or \textit{not}) is added to the charged lepton measured properties\footnote{\texttt{[code] }See the \texttt{IsolFlag} output of the \texttt{Electron} or \texttt{Muon} collections in the \texttt{Analysis} tree.}. No calorimetric isolation is applied. \\
     319To 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 \textsc{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. The result (i.e. \textit{isolated} or \textit{not}) is added to the charged lepton measured properties\footnote{\texttt{[code] }See the \texttt{IsolFlag} output of the \texttt{Electron} or \texttt{Muon} collections in the \texttt{Analysis} tree.}. No calorimetric isolation is applied. \\
    320320
    321321
     
    328328
    329329A realistic analysis requires a correct treatment of particles which have hadronised. Therefore, the most widely currently used jet algorithms have been integrated into the \textsc{Delphes} framework using the \textsc{FastJet} tools~\cite{bib:FastJet}.
    330 Six different jet reconstruction schemes are available\footnote{\texttt{[code] }The choice is done by allocating the \texttt{JET\_jetalgo } input parameter in the smearing card.}. The first three belong to the cone algorithm class while the last three are using a sequential recombination scheme. For all of them, the towers are used as input for the jet clustering. Jet algorithms also differ in their sensitivity to soft particles or collinear splittings, and with their computing speed performance.
     330Six different jet reconstruction schemes are available\footnote{\texttt{[code] }The choice is done by allocating the \texttt{JET\_jetalgo } input parameter in the smearing card.}. The first three belong to the cone algorithm class while the last three are using a sequential recombination scheme. For all of them, the towers are used as input for the jet clustering. Jet algorithms differ in their sensitivity to soft particles or collinear splittings, and in their computing speed performances.
     331By default, reconstruction uses a cone algorithm with $\Delta R=0.7$.
     332Jets are stored if their transverse energy is higher\footnote{\texttt{[code] PTCUT\_jet }variable in the smearing card.} than $20~\textrm{GeV}$.
    331333 
    332334\subsubsection*{Cone algorithms}
     
    348350\subsubsection*{Recombination algorithms}
    349351 
    350 The three following jet algorithms are safe for soft radiations (\textit{infrared}) and collinear splittings. They rely on recombination schemes where calorimeter tower pairs are successively merged. The definitions of the jet algorithms are similar except for the definition of the \textit{distances} $d$ used during the merging procedure. Two such variables are defined: the distance $d_{ij}$ between each pair of towers $(i,j)$, and a variable $d_{iB}$ (\textit{beam distance}) depending on the transverse momentum of the tower $i$.
     352The three sequential recombination jet algorithms are safe with respect to soft radiations (\textit{infrared}) and collinear splittings. They rely on recombination schemes where calorimeter tower pairs are successively merged. The definitions of the jet algorithms are similar except for the definition of the \textit{distances} $d$ used during the merging procedure. Two such variables are defined: the distance $d_{ij}$ between each pair of towers $(i,j)$, and a variable $d_{iB}$ (\textit{beam distance}) depending on the transverse momentum of the tower $i$.
    351353
    352354The jet reconstruction algorithm browses the calotower 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 towers $i$ and $j$ are merged into a single tower 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 tower is declared as a final jet and is removed from the input list. This procedure is repeated until no towers 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 calotower $i$ and $\Delta R_{ij}= \sqrt{(y_i-y_j)^2+(\phi_i-\phi_j)^2}$ as the jet-radius parameter:
     
    379381\end{enumerate}
    380382 
    381 By default, reconstruction uses a cone algorithm with $\Delta R=0.7$. Jets are stored if their transverse energy is higher\footnote{\texttt{[code] PTCUT\_jet }variable in the smearing card.} than $20~\textrm{GeV}$.
    382383
    383384 
    384385\subsection{$b$-tagging}
    385386
    386 A jet is tagged as $b$-jets if its direction lies in the acceptance of the tracker and if it is associated to a parent $b$-quark. A $b$-tagging efficiency of $40\%$ is assumed if the jet has a parent $b$ quark. For $c$-jets and light jets (i.e. originating in $u$,$d$,$s$ quarks or in gluons), a fake $b$-tagging efficiency of $10 \%$ and $1 \%$ respectively is assumed\footnote{\texttt{[code] }Corresponding to the \texttt{TAGGING\_B}, \texttt{MISTAGGING\_C} and \texttt{MISTAGGING\_L} constants, for (respectively) the efficiency of tagging of a $b$-jet, the efficiency of mistagging a $c$-jet as a $b$-jet, and the efficiency of mistagging a light jet ($u$,$d$,$s$,$g$) as a $b$-jet.}
     387A 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\footnote{\texttt{[code] }Corresponding to the \texttt{TAGGING\_B}, \texttt{MISTAGGING\_C} and \texttt{MISTAGGING\_L} constants, for (respectively) the efficiency of tagging of a $b$-jet, the efficiency of mistagging a $c$-jet as a $b$-jet, and the efficiency of mistagging a light jet ($u$,$d$,$s$,$g$) as a $b$-jet.}
    387388%(Fig.~\ref{fig:btag})
    388389.
     
    402403Jets originating from $\tau$-decays are identified using an identification procedure consistent with the one applied in a full detector simulation~\cite{bib:cmsjetresolution}.
    403404The 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}).
     405
    404406
    405407\begin{table}[!h]
     
    422424\end{table}
    423425
    424 
    425 %\begin{wrapfigure}{l}{0.3\columnwidth}
    426426\begin{figure}[!h]
    427427\begin{center}
     
    429429\caption{Illustration of the identification of $\tau$-jets. The jet cone is narrow and contains only one track. The small cone shown as the red one is used for the \textit{electromagnetic collimation}, while the green cone is the cone radius used to reconstruct the jet originating from the $\tau$-decay.}
    430430\label{h_WW_ss_cut1}
    431 \end{center}
    432 \end{figure}
    433 %\end{wrapfigure}
    434 
    435 
    436 \subsubsection*{Electromagnetic collimation}
    437 
    438 To use the narrowness of the $\tau$-jet, the \textit{electromagnetic collimation} $C_{\tau}^{em}$ is defined as the sum of the energy of towers in a small cone of radius $R^\textrm{em}$ around the jet axis, divided by the energy of the reconstructed jet.
    439 To be taken into account, a calorimeter tower should have a transverse energy $E_T^\textrm{tower}$ above a given threshold.
    440 A large fraction of the jet energy is expected in this small cone. This fraction, or collimation factor, is represented in Fig.~\ref{fig:tau2} for the default values (see Tab.~\ref{tab:tauRef}).
    441 
    442 \begin{figure}[!h]
    443 \begin{center}
    444 \includegraphics[width=\columnwidth]{Tau2}
    445 \caption{Distribution of the electromagnetic collimation $C_\tau$ variable for true $\tau$-jets, normalised to unity. This distribution is shown for associated $WH$ photoproduction~\cite{bib:whphotoproduction}, where the Higgs boson decays into a $W^+ W^-$ pair. Each $W$ boson decays into a $\ell \nu_\ell$ pair, where $\ell = e, \mu, \tau$.
    446 Events generated with \textsc{MadGraph/MadEvent}~\cite{bib:mgme}.
    447 Final state hadronisation is performed by \textsc{Pythia}~\cite{bib:pythia}.
    448 Histogram entries correspond to true $\tau$-jets, matched with generator level data. }
    449 \label{fig:tau2}
    450 \end{center}
    451 \end{figure}
    452 
    453 \subsubsection*{Tracking isolation}
    454 
    455 The tracking isolation for the $\tau$ identification requires that the number of tracks associated to a particle with a significant transverse momentum is one and only one in a cone of radius $R^\textrm{tracks}$ (3-prong $\tau$s are dropped).
    456 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}.
    457 
    458 
    459 
    460 \begin{figure}[!h]
    461 \begin{center}
    462 \includegraphics[width=\columnwidth]{Tau1}
    463 \caption{Distribution of the number of tracks $N^\textrm{tracks}$ within a small jet cone for true $\tau$-jets, normalised to unity. Photoproduced $WH$ events, where $W$ bosons decay leptonically ($e,\mu,\tau$), as in Fig.~\ref{fig:tau2}.
    464 Histogram entries correspond to true $\tau$-jets, matched with generator level data.}
    465 \label{fig:tau1}
    466431\end{center}
    467432\end{figure}
     
    481446\multicolumn{3}{l}{\textbf{Tracking isolation}} \\
    482447$R^\textrm{tracks}$ & \texttt{TAU\_track\_scone} & $0.4$\\
    483 min $p_T^{tracks}$      & \texttt{PTAU\_track\_pt } & $2$ GeV\\
     448min $p_T^{tracks}$      & \texttt{PTAU\_track\_pt } & $2$ GeV$/c$\\
    484449\multicolumn{3}{l}{\textbf{$\tau$-jet candidate}} \\
    485 $\min p_T$ & \texttt{TAUJET\_pt} & $10$ GeV\\
     450$\min p_T$ & \texttt{TAUJET\_pt} & $10$ GeV$/c$\\
    486451\hline
    487452\end{tabular}
     
    489454\end{center}
    490455\end{table}
     456
     457
     458\subsubsection*{Electromagnetic collimation}
     459
     460To use the narrowness of the $\tau$-jet, the \textit{electromagnetic collimation} $C_{\tau}^{em}$ is defined as the sum of the energy of towers in a small cone of radius $R^\textrm{em}$ around the jet axis, divided by the energy of the reconstructed jet.
     461To be taken into account, a calorimeter tower should have a transverse energy $E_T^\textrm{tower}$ above a given threshold.
     462A large fraction of the jet energy is expected in this small cone. This fraction, or collimation factor, is represented in Fig.~\ref{fig:tau2} for the default values (see Tab.~\ref{tab:tauRef}).
     463
     464\begin{figure}[!h]
     465\begin{center}
     466\includegraphics[width=\columnwidth]{Tau2}
     467\caption{Distribution of the electromagnetic collimation $C_\tau$ variable for true $\tau$-jets, normalised to unity. This distribution is shown for associated $WH$ photoproduction~\cite{bib:whphotoproduction}, where the Higgs boson decays into a $W^+ W^-$ pair. Each $W$ boson decays into a $\ell \nu_\ell$ pair, where $\ell = e, \mu, \tau$.
     468Events generated with \textsc{MadGraph/MadEvent}~\cite{bib:mgme}.
     469Final state hadronisation is performed by \textsc{Pythia}~\cite{bib:pythia}.
     470Histogram entries correspond to true $\tau$-jets, matched with generator-level data. }
     471\label{fig:tau2}
     472\end{center}
     473\end{figure}
     474
     475\subsubsection*{Tracking isolation}
     476
     477The tracking isolation for the $\tau$ identification requires that the number of tracks associated to a particle with a significant transverse momentum is one and only one in a cone of radius $R^\textrm{tracks}$ (3-prong $\tau$s are dropped).
     478This 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}.
     479
     480
     481
     482\begin{figure}[!h]
     483\begin{center}
     484\includegraphics[width=\columnwidth]{Tau1}
     485\caption{Distribution of the number of tracks $N^\textrm{tracks}$ within a small jet cone for true $\tau$-jets, normalised to unity. Photoproduced $WH$ events, where $W$ bosons decay leptonically ($e,\mu,\tau$), as in Fig.~\ref{fig:tau2}.
     486Histogram entries correspond to true $\tau$-jets, matched with generator-level data.}
     487\label{fig:tau1}
     488\end{center}
     489\end{figure}
     490
    491491
    492492\subsubsection*{Purity}
     
    519519\section{Trigger emulation}
    520520
    521 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 $100~\textrm{nb}$ ($p_T > 200~\textrm{GeV}$), while Higgs boson cross-section within the \textsc{sm} can be as small as $2 \times 10^{-3}~\textrm{nb}$ ($pp \rightarrow WH$, $m_H=115~\textrm{GeV}$).
     521New 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 $2 \times 10^{-3}~\textrm{nb}$ ($pp \rightarrow WH$, $m_H=115~\textrm{GeV}/c^2$).
    522522
    523523%High statistics are required for data analyses, consequently imposing high luminosity, i.e. a high collision rate.
    524524As 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.
    525 This data selection is supposed to reject only well-known \textsc{sm} events\footnote{However, some bandwidth is allocated to random triggers that stores a small fraction of the events without any selection criteria.}.
     525This data selection is supposed to reject only well-known \textsc{sm} events\footnote{However, some bandwidth is allocated to minimum-bias and/or zero-bias (``random'') triggers that stores a small fraction of the events without any selection criteria.}.
    526526Dedicated 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.
    527527
    528 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 $p_T^\textrm{jet} > 100~\textrm{GeV}$ and $p_T^e > 50~\textrm{GeV}$.
    529 
    530 A trigger emulation is included in \textsc{Delphes}, using a fully parametrisable \textit{trigger table}\footnote{\texttt{[code] }The trigger card is the \texttt{data/trigger.dat} file.}. When enabled, this trigger is applied on analysis object data.
     528Most 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 $p_T^e > 50~\textrm{GeV}/c$.
     529
     530A trigger emulation is included in \textsc{Delphes}, using a fully parametrisable \textit{trigger table}\footnote{\texttt{[code] }The trigger card is the \texttt{data/trigger.dat} file.}. When enabled, this trigger is applied on analysis-object data.
    531531In a real experiment, the online selection is often divided into several steps (or \textit{levels}).
    532532This splits the overall reduction factor into a product of smaller factors, corresponding to the different trigger levels.
    533533This is related to the architecture of the experiment data acquisition chain, with limited electronic buffers requiring a quick decision for the first trigger level.
    534 First level triggers are then fast and simple but based only on partial data as not all detector front-ends are readable within the decision latency.
    535 Later levels are more complex, of finer-but-not-final quality and based on full detector data.
     534First-level triggers are then fast and simple but based only on partial data as not all detector front-ends are readable within the decision latency.
     535Higher level triggers are more complex, of finer-but-not-final quality and based on full detector data.
    536536
    537537Real triggers are thus intrinsically based on reconstructed data with a worse resolution than final analysis data.
     
    549549\subsection{Jet resolution}
    550550 
    551 The majority of interesting processes at the \textsc{lhc} contain jets in the final state. The jet resolution obtained using \textsc{Delphes} is therefore a crucial point for its validation. Even if \textsc{Delphes} contains six algorithms for jet reconstruction, only the jet clustering algorithm (\textsc{jetclu}) with $R=0.7$ is used to validate the jet collection.
     551The majority of interesting processes at the \textsc{lhc} contain jets in the final state. The jet resolution obtained using \textsc{Delphes} is therefore a crucial point for its validation. Even if \textsc{Delphes} contains six algorithms for jet reconstruction, we use here the jet clustering algorithm (\textsc{jetclu}) with $R=0.7$ to validate the jet collection.
    552552
    553553This validation is based on $pp \rightarrow gg$ events produced with \textsc{MadGraph/MadEvent} and hadronised using \textsc{Pythia}~\cite{bib:mgme,bib:pythia}. The events were arranged in $14$ bins of gluon transverse momentum $\hat{p}_T$. In each $\hat{p}_T$ bin, every jet in \textsc{Delphes} is matched to the closest jet of generator-level particles, using the spatial separation between the two jet axes
     
    585585\subsection{MET resolution}
    586586 
    587 All major detectors at hadron colliders have been designed to be as much hermetic as possible in order to detect the presence of one or more neutrinos through apparent missing transverse energy.
     587All major detectors at hadron colliders have been designed to be as much hermetic as possible in order to detect the presence of one or more neutrinos and/or new weakly interacting particles through apparent missing transverse energy.
    588588The resolution of the $\overrightarrow{E_T}^\textrm{miss}$ variable, as obtained with \textsc{Delphes}, is then crucial.
    589589
     
    610610\sigma_x = \alpha ~\sqrt(E_T) ~~~(\mathrm{GeV}^{1/2}),
    611611\end{equation}
    612 where the $\alpha$ parameter is depending on the resolution of the calorimeters.
    613 
    614 The \textsc{met} resolution expected for the \textsc{cms} detector for similar events is $\sigma_x = (0.6-0.7) ~ \sqrt(E_T) ~ \mathrm{GeV}^{1/2}$ with no pile-up\footnote{\textit{Pile-up} events are extra simultaneous $pp$ collision occurring at the same bunch crossing.}~\cite{bib:cmsjetresolution}, which compares very well with the $\alpha = 0.68$ obtained with \textsc{Delphes}.
     612where the $\alpha$ parameter depends on the resolution of the calorimeters.
     613
     614The \textsc{met} resolution expected for the \textsc{cms} detector for similar events is $\sigma_x = (0.6-0.7) ~ \sqrt(E_T) ~ \mathrm{GeV}^{1/2}$ with no pile-up\footnote{\textit{Pile-up} events are extra simultaneous $pp$ collision occurring at high-luminosity in the same bunch crossing.}~\cite{bib:cmsjetresolution}, which compares very well with the $\alpha = 0.68$ obtained with \textsc{Delphes}.
    615615
    616616\subsection{\texorpdfstring{$\tau$}{\texttau}-jet efficiency}
    617617Due to the complexity of their reconstruction algorithm, $\tau$-jets have also to be checked.
    618 Tab.~\ref{tab:taurecoefficiency} lists the reconstruction efficiencies for the hadronic $\tau$-jets in the \textsc{cms} experiment and in \textsc{Delphes}. Agreement is good enough to validate this reconstruction.
     618Table~\ref{tab:taurecoefficiency} lists the reconstruction efficiencies for the hadronic $\tau$-jets in the \textsc{cms} experiment and in \textsc{Delphes}. Agreement is good enough to validate also this reconstruction.
    619619
    620620\begin{table}[!h]
     
    625625\multicolumn{2}{c}{\textsc{cms}} & \\
    626626$Z \rightarrow \tau^+ \tau^-$                    & $38 \%$ &  \\
    627 $H \rightarrow \tau^+ \tau^-$ & $36 \%$ & $m_H = 150~\textrm{GeV}$ \\
    628 $H \rightarrow \tau^+ \tau^-$ & $47 \%$ & $m_H = 300~\textrm{GeV}$ \\
     627$H \rightarrow \tau^+ \tau^-$ & $36 \%$ & $m_H = 150~\textrm{GeV}/c^2$ \\
     628$H \rightarrow \tau^+ \tau^-$ & $47 \%$ & $m_H = 300~\textrm{GeV}/c^2$ \\
    629629\multicolumn{2}{c}{\textsc{Delphes}} & \\
    630 $H \rightarrow \tau^+ \tau^-$ &$42 \%$  & $m_H = 140~\textrm{GeV}$ \\
     630$H \rightarrow \tau^+ \tau^-$ &$42 \%$  & $m_H = 140~\textrm{GeV}/c^2$ \\
    631631\hline
    632632\end{tabular}
     
    654654% \end{figure}
    655655 
    656 Two and three-dimensional representations of the detector configuration can be used for communication purpose, as it clearly shows the geometric coverage of the different detector subsystems. As an illustration, the generic detector geometry assumed in this paper is shown in Fig.~\ref{fig:GenDet3}
     656Two and three-dimensional representations of the detector configuration can be used for communication purposes, as they clearly illustrate the geometric coverage of the different detector subsystems.
     657As an example, the generic detector geometry assumed in this paper is shown in Fig.~\ref{fig:GenDet3}
    657658%, \ref{fig:GenDet}
    658659 and~\ref{fig:GenDet2}. 
    659 As pointed before, the detector is assumed to be strictly symmetric around the beam axis.
    660660The extensions of the central tracking system, the central calorimeters and both forward calorimeters are visible. 
    661 Nevertheless, it should be noticed that only the geometrical coverage is depicted and that the calorimeter segmentation is not taken into account in the drawing of the detector. Moreover, both the radius and the length of each sub-detectors are just display parameters and are insignificant for the physics simulation.
     661Note that only the geometrical coverage is depicted and that the calorimeter segmentation is not taken into account in the drawing of the detector. Moreover, both the radius and the length of each sub-detectors are just display parameters and are not relevant for the physics simulation.
    662662 
    663663\begin{figure}[!h]
     
    673673Moreover, kinematics information of each object is visible by a simple mouse action.
    674674As an illustration, an associated photoproduction of a $W$ boson and a $t$ quark is shown in Fig.~\ref{fig:wt}.
    675 This corresponds to a $pp(\gamma p \rightarrow Wt)pX$ process, where the $Wt$ couple is induced by an incoming photon emitted by one interacting proton~\cite{bib:wtphotoproduction}.
    676 This leading proton survives from the photon emission and subsequently from the $pp$ interaction, and is present in the final state.
     675This corresponds to a $pp(\gamma p \rightarrow Wt)pX$ process, where the $Wt$ couple is induced by an incoming photon emitted by one of the colliding proton~\cite{bib:wtphotoproduction}.
     676This leading proton survives after photon emission and is present in the final state.
    677677As the energy and virtuality of the emitted photon are low, the surviving proton does not leave the beam and escapes from the central detector without being detected.
    678 The experimental signature is a lack of hadronic activity in one forward hemisphere, where the surviving proton escapes.
     678The experimental signature is a lack of hadronic activity in the forward hemisphere where the surviving proton escapes.
    679679The $t$ quark decays into a $W$ boson and a $b$ quark.
    680680Both $W$ bosons decay into leptons ($W \rightarrow \mu \nu_\mu$ and $W \rightarrow e \nu_e$).
     
    685685%\includegraphics[width=\columnwidth]{Events_Delphes_1}
    686686\includegraphics[width=\columnwidth]{DisplayWt}
    687 \caption{Example of $pp(\gamma p \rightarrow Wt)pY$ event, with $t \rightarrow Wb$.
     687\caption{Example of $pp(\gamma p \rightarrow Wt)pY$ event display in different orientations, with $t \rightarrow Wb$.
    688688One $W$ boson decays into a $\mu \nu_\mu$ pair and the second one into a $e \nu_e$ pair.
    689689The surviving proton leaves a forward hemisphere with no hadronic activity.
     
    694694\end{figure}
    695695
    696 For the comparison, Fig.~\ref{fig:gg} depicts an inclusive gluon pair production $pp \rightarrow ggX$.
     696For comparison, Fig.~\ref{fig:gg} depicts an inclusive gluon pair production $pp \rightarrow ggX$.
    697697The event final state contains more jets, in particular along the beam axis, which is expected as the interacting protons are destroyed by the collision. Two muon candidates and large missing transverse energy are also visible.
    698698
     
    713713% It has already been used for several phenomenological studies, in particular in photon interactions at the \textsc{lhc}.
    714714%
    715 % \textsc{Delphes} takes the output of event generators, in various formats, and yields analysis object data.
     715% \textsc{Delphes} takes the output of event generators, in various formats, and yields analysis-object data.
    716716% The simulation applies the resolutions of central and forward detectors by smearing the kinematical properties of final state particles.
    717717% It yields tracks in a solenoidal magnetic field and calorimetric towers.
     
    726726%
    727727% \subsection{version 2}
    728 We have described here the major features of the \textsc{Delphes} framework, introduced for the fast simulation of a collider experiment. This framework is a tool meant for feasibility studies in phenomenology, probing the observability of models in collider experiments. It has already been used for several analyses, in particular in photon interactions at the \textsc{lhc}~\cite{bib:wtphotoproduction, bib:papierquisortirajamais, bib:papiersimon}.
    729 
    730 \textsc{Delphes} takes the output of event generators and yields analysis object data.
     728We have described here the major features of the \textsc{Delphes} framework, introduced for the fast simulation of a collider experiment. This framework is a tool meant for feasibility studies in phenomenology, gauging the observability of model prodictions in collider experiments.
     729
     730\textsc{Delphes} takes as an input the output of event-generators and yields analysis-object data in the form of \texttt{TTree} in a \textsc{root} file.
    731731The simulation includes central and forward detectors to produce realistic observables using standard reconstruction algorithms.
    732732Moreover, the framework allows trigger emulation and 3D event visualisation.
     
    734734\textsc{Delphes} has been developed using the parameters of the \textsc{cms} experiment but can be easily extended to \textsc{atlas} and other non-\textsc{lhc} experiments, as at Tevatron or at the \textsc{ilc}. Further developments include a more flexible design for the subdetector assembly and possibly the implementation of an event mixing module for pile-up event simulation.
    735735
     736This framework has already been used for several analyses, in particular in photon-induced interactions at the \textsc{lhc}~\cite{bib:wtphotoproduction, bib:papierquisortirajamais, bib:papiersimon}.
    736737
    737738
    738739\section*{Acknowledgements}
    739740\addcontentsline{toc}{section}{Acknowledgements}
    740 The authors would like to thank Jer\^ome de Favereau, Christophe Delaere, Vincent Lema\^itre, Muriel Vander Donckt and David d'Enterria for useful discussions and comments, and Loic Quertenmont for support in interfacing \textsc{Frog}. We are also really grateful to Alice Dechambre and Simon de Visscher for being beta testers of the complete package.
     741The authors would like to thank Jer\^ome de Favereau, Christophe Delaere, Muriel Vander Donckt and David d'Enterria for useful discussions and comments, and Loic Quertenmont for support in interfacing \textsc{Frog}. We are also really grateful to Alice Dechambre and Simon de Visscher for being beta testers of the complete package.
    741742Part of this work was supported by the Belgian Federal Office for Scientific, Technical and Cultural Affairs through the Interuniversity Attraction Pole P6/11.
    742743
     
    794795\section{User manual}
    795796 
    796 The available code is a zipped tar file which comes with everything needed to run the \textsc{Delphes} package, assuming a running \textsc{root} installation.
     797The available \texttt{C++}-code is compressed in a zipped tar file which contains with everything needed to run the \textsc{Delphes} package, assuming a running \textsc{root} installation.
    797798The package includes \texttt{ExRootAnalysis}~\cite{bib:ExRootAnalysis}, \textsc{Hector}~\cite{bib:Hector},
    798799\textsc{FastJet}~\cite{bib:FastJet}, and \textsc{Frog}~\cite{bib:Frog}, as well as the conversion codes to read standard \mbox{\textsc{s}td\textsc{hep}} input files (\texttt{mcfio} and \texttt{stdhep})~\cite{bib:mcfio}.
    799 Nevertheless in order to visualise the events with the \textsc{Frog} software, some external libraries may be required, as explained in \href{http://projects.hepforge.org/frog/}{http://projects.hepforge.org/frog/}.
     800In order to visualise the events with the \textsc{Frog} software, a few additional external libraries may be required, as explained in \href{http://projects.hepforge.org/frog/}{http://projects.hepforge.org/frog/}.
    800801 
    801802\subsection{Getting started}
    802803 
    803 In order to run \textsc{Delphes} on your system, first download its sources and compile it:\\
     804In order to run \textsc{Delphes} on your system, first download its sources and compile them:\\
    804805\texttt{wget http://www.fynu.ucl.ac.be/users/s.ovyn/Delphes/files/Delphes\_V\_*.tar.gz}\\
    805806Replace the \texttt{*} symbol by the proper version number\footnote{Refer to the download page on the \textsc{Delphes} website \href{http://www.fynu.ucl.ac.be/users/s.ovyn/Delphes/download.html}{http://www.fynu.ucl.ac.be/users/s.ovyn/Delphes/download.html}.}.
     
    825826\subsection{Running \textsc{Delphes} on your events}
    826827 
    827 In this chapter, we will explain how to use \textsc{Delphes} to perform a fast simulation of a general purpose detector on your event files. The first step to use \textsc{Delphes} is to create the list of input event files (e.g. {\verb inputlist.list }). As an important comment, don't forget that all the files comprised in the list file should have the same type (\texttt{*.hep}, \texttt{*.lhe} or \texttt{*.root}). In the simplest way of running \textsc{Delphes}, you need this input file and you need to specify the name of the output file that will contain the generator-level data (\texttt{GEN} tree), the analysis data objects after reconstruction (\texttt{Analysis} tree), and the results of the trigger emulation (\texttt{Trigger} tree).
     828In this sub-appendix, we will explain how to use \textsc{Delphes} to perform a fast simulation of a general-purpose detector on your event files. The first step to use \textsc{Delphes} is to create the list of input event files (e.g. {\verb inputlist.list }). It is important to novice that all the files comprised in the list file should have the same of extension (\texttt{*.hep}, \texttt{*.lhe} or \texttt{*.root}). In the simplest way to run \textsc{Delphes}, you need this input file and you need to specify the name of the output file that will contain the generator-level data (\texttt{GEN} tree), the analysis data objects after reconstruction (\texttt{Analysis} tree), and the results of the trigger emulation (\texttt{Trigger} tree).
    828829 
    829830\begin{quote}
     
    835836\subsubsection{Setting up the configuration}
    836837 
    837 The program is driven by two datacards (default cards are {\verb data/DataCardDet.dat } and {\verb data/trigger.dat }) which allow a large spectrum of running conditions.
    838 Please note that either the user provides these two datacards, either the running will be done using the default parameters defined in the constructor of the class \texttt{RESOLution}. If you choose a different detector or running configuration, you will need to edit the datacards accordingly.
     838The program is driven by two datacards (default cards are {\verb data/DataCardDet.dat } and {\verb data/trigger.dat }) which allow the user to choose among a large spectrum of running conditions.
     839Please note that if the user does not provide these two datacards, the running will be done using the default parameters defined in the constructor of the class \texttt{RESOLution} (see next). If you choose a different detector or running configuration, you will need to edit the datacards accordingly.
    839840 
    840841\begin{enumerate}
     
    846847\begin{itemize}
    847848 \item detector parameters, including calorimeter and tracking coverage and resolution, transverse energy thresholds for object reconstruction and jet algorithm parameters.
    848  \item four flags ({\verb FLAG_bfield }, {\verb FLAG_vfd }, {\verb FLAG_trigger } and {\verb FLAG_frog }), which should be assigned if the magnetic field propagation, the very forward detectors simulation, the trigger selection and the preparation for \textsc{Frog} display (respectively) have to be run by \textsc{Delphes}.
     849 \item four flags ({\verb FLAG_bfield }, {\verb FLAG_vfd }, {\verb FLAG_trigger } and {\verb FLAG_frog }), should be set in order to configure the magnetic field propagation, the very forward detectors simulation, the trigger selection and the preparation for \textsc{Frog} display (respectively).
    849850 \end{itemize}
    850851 
     
    852853\begin{quote}
    853854\begin{verbatim}
    854 # Detector extension, in pseudorapidity units
     855# Detector extension, in pseudorapidity units (|eta|)
    855856CEN_max_tracker    2.5     // Maximum tracker coverage
    856857CEN_max_calo_cen   3.0     // central calorimeter coverage
     
    877878 
    878879# Muon smearing
    879 MU_SmearPt        0.01    // transverse momentum Pt in GeV
     880MU_SmearPt        0.01    // transverse momentum Pt in GeV/c
    880881 
    881882# Tracking efficiencies
     
    910911           10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 20 20
    911912 
    912 # Thresholds for reconstructed objects, in GeV
     913# Thresholds for reconstructed objects, in GeV/c
    913914PTCUT_elec       10.0
    914915PTCUT_muon       10.0
     
    936937TRACK_radius      129     // radius of the BField coverage, in cm
    937938TRACK_length      300     // length of the BField coverage, in cm
    938 TRACK_bfield_x    0       // X composant of the BField, in T
    939 TRACK_bfield_y    0       // Y composant of the BField, in T
    940 TRACK_bfield_z    3.8     // Z composant of the BFieldn in T
     939TRACK_bfield_x    0       // X component of the BField, in T
     940TRACK_bfield_y    0       // Y component of the BField, in T
     941TRACK_bfield_z    3.8     // Z component of the BFieldn in T
    941942 
    942943# Very forward detector extension, in pseudorapidity
     
    944945VFD_min_calo_vfd  5.2     // very forward calorimeter (if any) like CASTOR
    945946VFD_max_calo_vfd  6.6
    946 VFD_min_zdc       8.3
     947VFD_min_zdc       8.3     // zero-degree neutral calorimeter
    947948VFD_s_zdc         140     // distance of the ZDC, from the IP, in [m]
    948949 
     
    957958\end{verbatim}
    958959\end{quote}
    959 In general, energies and momenta are expressed in GeV, and  magnetic fields in T.
     960In general, energies, momenta and masses are expressed in GeV ,GeV$/c$, Gev$/c^2$ respectively, and  magnetic fields in T.
    960961Geometrical extension are often referred in terms of pseudorapidity $\eta$, as the detectors are supposed to be symmetric in $\phi$.
    961962 
    962963\item{\bf The trigger card }
    963964 
    964 This card contains the definitions of all trigger bits. Cuts can be applied on the transverse momentum $p_T$ of electrons, muons, jets, $\tau$-jets, photons and the missing transverse energy. The following codes should be used so that \textsc{Delphes} can correctly translate the input list of trigger bits into selection algorithms:
     965This card contains the definitions of all trigger-bits. Cuts can be applied on the transverse momentum $p_T$ of electrons, muons, jets, $\tau$-jets, photons and the missing transverse energy. The following codes should be used so that \textsc{Delphes} can correctly translate the input list of trigger-bits into selection algorithms:
    965966 
    966967\begin{quote}
     
    976977\end{quote}
    977978 
    978 Each line in the trigger datacard is allocated to exactly one trigger bit and starts with the name of the corresponding trigger.
     979Each line in the trigger datacard is allocated to exactly one trigger-bit and starts with the name of the corresponding trigger.
    979980Logical combination of several conditions is also possible.
    980 If the trigger bit requires the presence of multiple identical objects, the order of their $p_T$ thresholds is very important: they must be defined in \textit{decreasing} order. Finally, the different requirements on the objects must be separated by a {\verb && } flag.
     981If the trigger-bit requires the presence of multiple identical objects, the order of their $p_T$ thresholds is very important: they must be defined in \textit{decreasing} order. Finally, the different requirements on the objects must be separated by a {\verb && } flag.
    981982The default trigger card can be found in the data repository of \textsc{Delphes} (\texttt{data/trigger.dat}).
    982983An example of trigger table consistent with the previous rules is given here:
     
    10191020\subsubsection{Contents of the \textsc{Delphes} ROOT trees}
    10201021 
    1021 The \textsc{Delphes} output file (\texttt{*.root}) is subdivided into three \textit{trees}, corresponding to generator-level data, analysis object data and trigger output. These \textit{trees} are structures that organise the output data into \textit{branches} containing data (or \textit{leaves}) related with each others, like the kinematics properties ($E$, $p_x$, $\eta$, $\ldots$) of a given particle.
     1022The \textsc{Delphes} output file (\texttt{*.root}) is subdivided into three \textit{trees}, corresponding to generator-level data, analysis-object data and trigger output. These \textit{trees} are structures that organise the output data into \textit{branches} containing data (or \textit{leaves}) related with each others, like the kinematics properties ($E$, $p_x$, $\eta$, $\ldots$) of a given particle.
    10221023
    10231024Here is the exhaustive list of \textit{branches} availables in these \textit{trees}, together with their corresponding physical objet and \texttt{ExRootAnalysis} class:
     
    10271028~~~Particle & generator particles from \textsc{hepevt}     & {\verb TRootGenParticle }\\
    10281029{\bf Trigger  } & &\\
    1029 ~~~TrigResult & Acceptance of different trigger bits       & {\verb TRootTrigger }\\
     1030~~~TrigResult & Acceptance of different trigger-bits       & {\verb TRootTrigger }\\
    10301031\end{tabular}
    10311032\end{quote}
     
    10521053\multicolumn{2}{l}{\textbf{Most common leaves}}\\
    10531054 \texttt{~~~float E;     }&\texttt{ // particle energy in GeV }\\
    1054  \texttt{~~~float Px;    }&\texttt{ // particle momentum vector (x component) in GeV }\\
    1055  \texttt{~~~float Py;    }&\texttt{ // particle momentum vector (y component) in GeV }\\
    1056  \texttt{~~~float Pz;    }&\texttt{ // particle momentum vector (z component) in GeV }\\
    1057  \texttt{~~~float PT;    }&\texttt{ // particle transverse momentum in GeV }\\
     1055 \texttt{~~~float Px;    }&\texttt{ // particle momentum vector (x component) in GeV$/c$ }\\
     1056 \texttt{~~~float Py;    }&\texttt{ // particle momentum vector (y component) in GeV$/c$ }\\
     1057 \texttt{~~~float Pz;    }&\texttt{ // particle momentum vector (z component) in GeV$/c$ }\\
     1058 \texttt{~~~float PT;    }&\texttt{ // particle transverse momentum in GeV$/c$ }\\
    10581059 \texttt{~~~float Eta;   }&\texttt{ // particle pseudorapidity   }\\
    10591060 \texttt{~~~float Phi;   }&\texttt{ // particle azimuthal angle in rad }\\
     
    10721073   \texttt{~~~int D2;       }&\texttt{ // particle 2nd daughter }\\
    10731074   \texttt{~~~float Charge; }&\texttt{ // electrical charge in units of e}\\
    1074    \texttt{~~~float T;      }&\texttt{ // particle vertex position (t component, in mm/c) }\\
     1075   \texttt{~~~float T;      }&\texttt{ // particle vertex position (t component, in mm$/c$) }\\
    10751076   \texttt{~~~float X;      }&\texttt{ // particle vertex position (x component, in mm) }\\
    10761077   \texttt{~~~float Y;      }&\texttt{ // particle vertex position (y component, in mm) }\\
    10771078   \texttt{~~~float Z;      }&\texttt{ // particle vertex position (z component, in mm) }\\
    1078    \texttt{~~~float M;      }&\texttt{ // particle mass in GeV}\\
     1079   \texttt{~~~float M;      }&\texttt{ // particle mass in GeV$/c^2$}\\
    10791080\end{tabular}
    10801081\end{quote}
     
    11891190\item Go back into the main directory and type
    11901191\begin{quote}
    1191 \texttt{me@mylaptop:~\$ ./Utilities/FROG/frog}.
     1192\texttt{me@mylaptop:~\$ ./Utilities/FROG/frog}
    11921193\end{quote}
    11931194\end{itemize}
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