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1\documentclass[a4paper,11pt,oneside,twocolumn]{article}
2%\usepackage[english]{babel}
3\usepackage[ansinew]{inputenc}
4\usepackage{abstract}
5
6\usepackage{amsmath}
7\usepackage{epic}
8\usepackage{wrapfig}
9\usepackage{eepic}
10\usepackage{color}
11\usepackage{latexsym}
12\usepackage{array}
13\usepackage{multicol}
14
15\usepackage{fancyhdr}
16\usepackage{verbatim}
17\addtolength{\textwidth}{1cm} \addtolength{\hoffset}{-0.5cm}
18\usepackage[colorlinks=true, pdfstartview=FitV, linkcolor=blue, citecolor=blue, urlcolor=blue, unicode]{hyperref}
19\usepackage{ifpdf}
20\usepackage{cite}
21
22\usepackage{enumitem}
23
24\newcommand{\dollar}{\$}
25
26\ifpdf
27 \usepackage[pdftex]{graphicx}
28 \graphicspath{{all_png/}}
29 \pdfinfo{
30 /Author (S. Ovyn, X. Rouby)
31 /Title (Delphes, a framework for fast simulation of a general purpose LHC detector)
32 /Subject ()
33 /Keywords (Delphes, Fast simulation, LHC, FROG, Hector, Smearing, FastJet)}
34\else
35 \usepackage[dvips]{graphicx}
36 \graphicspath{{figures/}}
37\fi
38
39%\title{\textsc{Delphes}, a framework for fast simulation \\of a general purpose \textsc{lhc} detector}
40\title{\textsc{Delphes}, a framework for fast simulation \\of a generic collider experiment}
41\author{S. Ovyn and X. Rouby$^\textrm{a}$\\
42 \small{Center for Particle Physics and Phenomenology (CP3)}\\
43 \small{Universit\'e catholique de Louvain}\\
44 \small{B-1348 Louvain-la-Neuve, Belgium}\\ \\
45 \texttt{severine.ovyn@uclouvain.be, xavier.rouby@cern.ch} \\
46}
47\date{}
48
49
50\begin{document}
51
52\twocolumn[
53\maketitle
54
55\begin{center}
56\includegraphics{DelphesLogoSml}
57\end{center}
58
59
60\begin{abstract}
61It 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.
63We introduce here a new framework, \textsc{Delphes}, for fast simulation of
64a general purpose experiment. The simulation includes a tracking system, embedded into a magnetic field, calorimetry and a muon
65system, and possible very forward detectors arranged along the beamline.
66The framework is interfaced to standard file formats (e.g. Les Houches Event File) and outputs observable analysis data objects, like missing transverse energy and collections of electrons or jets.
67The simulation of detector response takes into account the detector resolution, and usual reconstruction algorithms for complex objects, 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.
68An overview of \textsc{Delphes} is given as well as a few use-cases for illustration.
69\vspace{0.5cm}
70
71\noindent
72\textit{Keywords:} \textsc{Delphes}, fast simulation, \textsc{lhc}, smearing, trigger, \textsc{FastJet}, \textsc{Hector}, \textsc{Frog}\\
73\href{http://www.fynu.ucl.ac.be/delphes.html}{http://www.fynu.ucl.ac.be/delphes.html}
74\vspace{1.5cm}
75
76\end{abstract}
77\small{$^\textrm{a}$ Now in Physikalisches Institut, Albert-Ludwigs-Universit\"at Freiburg}
78]
79%\saythanks
80
81\section{Introduction}
82% Motiver l'utilisation d'un simulateur rapide
83% - 1) rapide VS lent
84% - 2) relativement bonne prédiction en premiÚre approximation
85% - 3) permet de comparer
86
87Experiments at high energy colliders are very complex systems in several ways. First, in terms of the various detector subsystems, including tracking, central calorimetry, forward calorimetry, and muon chambers. These detectors differ with their principles, technologies, geometries and sensitivities. Then, due to the requirement of a highly effective online selection (i.e. a \textit{trigger}), subdivided into several levels for an optimal reduction factor, but based only on partially processed data. Finally, in terms of the experiment software, with different data formats (like \textit{raw} or \textit{reconstructed} data), many reconstruction algorithms and particle identification schemes.
88
89This complexity is handled by large collaborations of thousands of people, which restrict the availability of the data, software and documentation to their members. Real data analyses require a full detector simulation, including the various detector inefficiencies, the dead material, the imperfections and the geometrical details. Moreover, detector calibration and alignment are crucial. Such simulation is very complicated, technical and slow. On the other hand, phenomenological studies, looking for the observability of given signals, may require only fast but realistic estimates of the observables.
90
91A new framework, called \textsc{Delphes}~\cite{bib:Delphes}, is introduced here, for the fast simulation of a general purpose collider experiment.
92Using the framework, observables can be estimated for specific signal and background channels, as well as their production and measurement rates, under a set of assumptions.
93Starting from the output of event generators, the simulation of the detector response takes into account the subdetector resolutions, by smearing the kinematical properties of the visible final particles. Tracks of charged particles and calorimetric towers (or \textit{calotowers} are then created.
94
95\textsc{Delphes} includes the most crucial experimental features, like (1) the geometry of both central or forward detectors; (2) lepton isolation; (3) reconstruction of photons, leptons, jets, $b$-jets, $\tau$-jets and missing transverse energy; (4) trigger emulation and (5) an event display (Fig.~\ref{fig:FlowChart}).
96
97\begin{figure*}[t]
98\begin{center}
99%\includegraphics[width=0.9\textwidth]{FlowDelphes}
100\includegraphics[scale=0.78]{FlowDelphes}
101\caption{Flow chart describing the principles behind \textsc{Delphes}. Event files coming from external Monte Carlo generators are read by a convertor stage.
102The kinematical variables of the final state particles are then smeared according to the subdetector resolutions.
103Tracks 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.
104The transport of very forward particle to the near-beam detectors is also simulated.
105Finally, an output file is written, including generator level and analysis object data. If requested, a fully parametrisable trigger can be emulated. Optionnally, the geometry and visualisation files for the 3D event display can also be produced.
106All user parameters are set in the \textit{Smearing Card} and the \textit{Trigger Card}. }
107\label{fig:FlowChart}
108\end{center}
109\end{figure*}
110
111Although 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.
112
113%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.
114
115Three formats of input files can currently 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 \mbox{\textsc{s}td\textsc{hep}} can be used as an input. Besides, \textsc{Delphes} can also provide detector response for events read in ``Les Houches Event Format'' (\textsc{lhef}) and \textsc{root} files obtained using the \texttt{h2root} utility from the \textsc{root} framework~\cite{bib:Root}.
116%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.
117
118\textsc{Delphes} uses the \texttt{ExRootAnalysis} utility~\cite{bib:ExRootAnalysis} to create output data in a \texttt{*.root} file format.
119This 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.\\
120
121
122\section{Detector simulation}
123
124The overall layout of the general purpose detector simulated by \textsc{Delphes} is shown in Fig.~\ref{fig:GenDet3}.
125A 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
126The 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.}.
127If no such file is provided, predifined values are used. The coverage of the various subsystems used in the default configuration are summarised in Tab.~\ref{tab:defEta}.
128
129\begin{table*}[t]
130\begin{center}
131\caption{Default extension in pseudorapidity $\eta$ of the different subdetectors.
132The corresponding parameter name, in the smearing card, is given. \vspace{0.5cm}}
133\begin{tabular}{lll}
134\hline
135\textsc{tracker} & {\verb CEN_max_tracker } & $0.0 \leq |\eta| \leq 2.5$\\
136\textsc{ecal}, \textsc{hcal} & {\verb CEN_max_calo_cen } & $0.0 \leq |\eta| \leq 3.0$\\
137\textsc{fcal} & {\verb CEN_max_calo_fwd } & $3.0 \leq |\eta| \leq5.0$\\
138\textsc{muon} & {\verb CEN_max_mu } & $0.0 \leq |\eta| \leq 2.4$\\\hline
139\end{tabular}
140\label{tab:defEta}
141\end{center}
142\end{table*}
143
144\begin{figure}[!h]
145\begin{center}
146\includegraphics[width=\columnwidth]{Detector_Delphes_3}
147\caption{
148Profile of layout of the generic detector geometry assumed in \textsc{Delphes}. The innermost layer, close to the interaction point, is a central tracking system (pink).
149It is surrounded by a central calorimeter volume (green) with both electromagnetic and hadronic sections.
150The 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.
151The 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.
152}
153\label{fig:GenDet3}
154\end{center}
155\end{figure}
156
157
158\subsubsection*{Magnetic field}
159In addition to the subdetectors, the effects of a dipolar magnetic field is simulated for the charged particles\footnote{\texttt{[code] }See the \texttt{TrackPropagation} class.}. This simply modifies the corresponding particle direction before it enters the calorimeters.
160
161
162
163\subsection{Tracks reconstruction}
164Every stable charged particle with a transverse momentum above some threshold and lying inside the fiducial volume of the tracker provides a track.
165By 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 $|\eta| \leq 2.5$.
166
167
168\subsection{Simulation of calorimeters}
169
170The energy of each particle considered as stable in the generator particle list is smeared, with a Gaussian distribution depending on the calorimeter resolution. This resolution varies with the sub-calorimeter (\textsc{ecal}, \textsc{hcal}, \textsc{fcal}) measuring the particle.
171The response of each sub-calorimeter is parametrised as a function of the energy:
172\begin{equation}
173\frac{\sigma}{E} = \frac{S}{\sqrt{E}} \oplus \frac{N}{E} \oplus C,
174\label{eq:caloresolution}
175\end{equation}
176where $S$, $N$ and $C$ are the \textit{stochastic}, \textit{noise} and \textit{constant} terms, respectively.\\
177
178
179The particle four-momentum $p^\mu$ are smeared with a parametrisation directly derived from the detector techinal designs\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.}.
180In 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.
181Muons and neutrinos are assumed no 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.}.
182The default values of the stochastic, noisy and constant terms are given in Tab.~\ref{tab:defResol}.\\
183
184\begin{table}[!h]
185\begin{center}
186\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}).
187The corresponding parameter name, in the smearing card, is given. \vspace{0.5cm}}
188\begin{tabular}[!h]{lclc}
189\hline
190\multicolumn{2}{c}{Resolution Term} & Card flag & Value\\\hline
191 \multicolumn{4}{l}{\textsc{ecal}} \\
192 & $S$ & {\verb ELG_Scen } & $0.05$ \\
193 & $N$ & {\verb ELG_Ncen } & $0.25$ \\
194 & $C$ & {\verb ELG_Ccen } & $0.0055$ \\
195 \multicolumn{4}{l}{\textsc{fcal}, electromagnetic part} \\
196 & $S$ & {\verb ELG_Sfwd } & $2.084$ \\
197 & $N$ & {\verb ELG_Nfwd } & $0$ \\
198 & $C$ & {\verb ELG_Cfwd } & $0.107$ \\
199 \multicolumn{4}{l}{\textsc{hcal}} \\
200 & $S$ & {\verb HAD_Shcal } & $1.5$ \\
201 & $N$ & {\verb HAD_Nhcal } & $0$\\
202 & $C$ & {\verb HAD_Chcal } & $0.05$\\
203 \multicolumn{4}{l}{\textsc{fcal}, hadronic part} \\
204 & $S$ & {\verb HAD_Shf } & $2.7$\\
205 & $N$ & {\verb HAD_Nhf } & $0$. \\
206 & $C$ & {\verb HAD_Chf } & $0.13$\\
207\hline
208\end{tabular}
209\label{tab:defResol}
210\end{center}
211\end{table}
212
213The 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}.
214Some 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
215\begin{equation}
216\left\{
217\begin{array}{l}
218E_{\textsc{hcal}} = E \times F \\
219E_{\textsc{ecal}} = E \times (1-F) \\
220\end{array}
221\right.
222\end{equation}
223where $0 \leq F \leq 1$. The electromagnetic part is handled as the electrons. The resulting final energy 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 $0.7$.\\
224
225\subsection{Calorimetric towers}
226
227The smallest unit for geometrical sampling of the calorimeters is a \textit{tower}; it segments the $(\eta,\phi)$ plane for the energy measurement.
228All undecayed particles, except muons and neutrinos produce a calorimetric tower, either in \textsc{ecal}, in \textsc{hcal} or \textsc{fcal}.
229As the detector is assumed to be 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.
230
231
232
233\begin{figure}[!h]
234\begin{center}
235\includegraphics[width=\columnwidth]{calosegmentation}
236\caption{Default segmentation of the calorimeters in the $(\eta,\phi)$ plane. Only the central detectors (\textsc{ecal}, \textsc{hcal} and \textsc{fcal}) are considered.}
237\label{fig:calosegmentation}
238\end{center}
239\end{figure}
240
241The calorimetric towers directly enter in the calculation of the missing transverse energy (\textsc{met}), and as input for the jet reconstruction algorithms. No longitudinal segmentation is available in the simulated calorimeters. No sharing between neighbouring towers is implemented when particles enter a tower very close to its geometrical edge.
242
243\subsection{Very forward detectors simulation}
244
245Most 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.
246Zero 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 pseudorapirities (e.g. $|\eta_{\textrm{n,}\gamma}| > 8.3$ in \textsc{cms}).
247Forward 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 millimeters from the true beam trajectory and this distance defines their acceptance (Tab.~\ref{tab:fdetacceptance}).
248
249\begin{figure}[!h]
250\begin{center}
251\includegraphics[width=\columnwidth]{fdets}
252\caption{Default location of the very forward detectors, including \textsc{zdc}, \textsc{rp220} and \textsc{fp420} in the \textsc{lhc} beamline.
253Incoming (red) and outgoing (black) beams on one side of the interaction point ($s=0~\textrm{m}$).
254The 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 $420~\textrm{m}$.}
255\label{fig:fdets}
256\end{center}
257\end{figure}
258
259\begin{table*}[t]
260\begin{center}
261\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.
262The 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.
263\vspace{0.5cm}}
264\begin{tabular}{llcl}
265\hline
266Detector & Distance & Acceptance & \\ \hline
267\textsc{zdc} & $140$ m & $|\eta|> 8.3$ & for $n$ and $\gamma$\\
268\textsc{rp220} & $220$ m & $E \in [6100 ; 6880]$ (GeV) & at $2~\textrm{mm}$\\
269\textsc{fp420} & $420$ m & $E \in [6880 ; 6980]$ (GeV) & at $4~\textrm{mm}$\\
270\hline
271\end{tabular}
272\label{tab:fdetacceptance}
273\end{center}
274\end{table*}
275
276
277While 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.
278
279Some subdetectors have the ability to measure the time of flight of the particle.
280This 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
281\begin{equation}
282 t = t_0 + \frac{1}{v} \times \Big( \frac{s-z}{\cos \theta}\Big),
283\end{equation}
284where $t$ is the time of flight, $t_0$ is the true time coordinate of the vertex from which the particle originates, $v$ the particle velocity, $s$ is the \textsc{zdc} distance to the interaction point, $z$ is the longitudinal coordinate of the vertex from which the particle comes from, $\theta$ is the particle emission angle. This assumes that the neutral particle observed in the \textsc{zdc} is highly relativistic, i.e. travelling at the speed of light $c$. We also assume that $\cos \theta = 1$, i.e. $\theta \approx 0$ or equivalently $\eta$ is large. As an example, $\eta = 5$ leads to $\theta = 0.013$ and $1 - \cos \theta < 10^{-4}$.
285The formula then reduces to
286\begin{equation}
287 t = \frac{1}{c} \times (s-z)
288\end{equation}
289Only neutrons and photons are currently assumed to be able to reach the \textsc{zdc}. All other particles are neglected in the \textsc{zdc}.
290To fix the ideas, if the \textsc{zdc} is located at $s=140~\textrm{m}$, neglecting $z$ and $\theta$, and assuming that $v=c$, one gets $t=0.47~\mu\textrm{s}$.
291
292\section{High-level object reconstruction}
293
294Analysis 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\footnote{\texttt{[code] }All these processed data are located under the \texttt{Analysis} tree.} in the output file created by \textsc{Delphes}.
295In addition, some detector data are added: tracks, calorometric towers and hits in \textsc{zdc}, \textsc{rp220} and \textsc{fp420}.
296While electrons, muons and photons are easily identified, some other objects are more difficult to measure, like jets or missing energy due to invisible particles.
297
298For most of these objects, their four-momentum $p^\mu$ and related quantities are directly accessible in \textsc{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).
299
300
301
302\subsection{Photon and charged lepton reconstruction}
303From 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.
304\subsubsection*{Electrons and photons}
305Photon 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.
306
307\subsubsection*{Muons}
308
309Generator level muons entering the detector acceptance are considered as candidates for the analysis level.
310The acceptance is defined in terms of a transverse momentum threshold to overpass (default : $p_T > 10~\textrm{GeV}$) and of the pseudorapidity coverage of the muon system of the detector (default: $-2.4 \leq \eta \leq 2.4$).
311The 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.
312
313\subsubsection*{Charged lepton isolation}
314
315To 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.}.\\
316
317
318
319
320
321
322
323\subsection{Jet reconstruction}
324
325A realistic analysis requires a correct treatment of final state particles which hadronise. Therefore, the most widely currently used jet algorithms have been integrated into the \textsc{Delphes} framework using the \textsc{FastJet} tools~\cite{bib:FastJet}.
326Six 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 recombinaison scheme. For all of them, the towers are used as input of the jet clustering. Jet algorithms also differ with their sensitivity to soft particles or collinear splittings, and with their computing speed performance.
327
328\subsubsection*{Cone algorithms}
329
330\begin{enumerate}
331
332\item {\it CDF Jet Clusters}~\cite{bib:jetclu}: Algorithm forming jets by associating together towers lying within a circle (default radius $\Delta R=0.7$) in the $(\eta$, $\phi)$ space.
333The so-called \textsc{Jetclu} cone jet algorithm that was used by \textsc{cdf} in Run II is used.
334All towers with a transverse energy $E_T$ higher than a given threshold (default: $E_T > 1~\textrm{GeV}$) are used to seed the jet candidates.
335The existing \textsc{FastJet} code has been modified to allow easy modification of the tower pattern in $\eta$, $\phi$ space.
336In the following versions of \textsc{Delphes}, a new dedicated plug-in will be created on this purpose\footnote{\texttt{[code] }\texttt{JET\_coneradius} and \texttt{JET\_seed} variables in the smearing card.}.
337
338\item {\it CDF MidPoint}~\cite{bib:midpoint}: Algorithm developped for the \textsc{cdf} Run II to reduce infrared and collinear sensitivity compared to purely seed-based cone by adding `midpoints' (energy barycenters) in the list of cone seeds.
339
340\item {\it Seedless Infrared Safe Cone}~\cite{bib:SIScone}: The \textsc{SISCone} algorithm is simultaneously insensitive to additional soft particles and collinear splittings, and fast enough to be used in experimental analysis.
341
342\end{enumerate}
343
344\subsubsection*{Recombination algorithms}
345
346The three following jet algorithms are safe for soft radiations (\textit{infrared}) and collinear splittings. They rely on recombination schemes where neighbouring calotower 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 $i$.
347
348The 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:
349
350\begin{enumerate}[start=4]
351
352\item {\it Longitudinally invariant $k_t$ jet}~\cite{bib:ktjet}:
353\begin{equation}
354\begin{array}{l}
355 d_{ij} = \min(k_{ti}^2,k_{tj}^2)\Delta R_{ij}^2/R^2 \\
356 d_{iB}=k_{ti}^2 \\
357\end{array}
358\end{equation}
359
360\item {\it Cambridge/Aachen jet}~\cite{bib:aachen}:
361\begin{equation}
362\begin{array}{l}
363d_{ij} = \Delta R_{ij}^2/R^2\\
364d_{iB}=1 \\
365\end{array}
366\end{equation}
367
368\item {\it Anti $k_t$ jet}~\cite{bib:antikt}: where hard jets are exactly circular in the $(y,\phi)$ plane
369\begin{equation}
370\begin{array}{l}
371d_{ij} = \min(1/k_{ti}^2,1/k_{tj}^2)\Delta R_{ij}^2/R^2 \\
372d_{iB}=1/k_{ti}^2 \\
373\end{array}
374\end{equation}
375\end{enumerate}
376
377By 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 $20~\textrm{GeV}$.
378
379
380\subsection{$b$-tagging}
381
382A 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.}
383%(Fig.~\ref{fig:btag})
384.
385The (mis)tagging relies on the true particle identity (\textsc{pid}) of the most energetic particle within a cone around the observed $(\eta,\phi)$ region, with a radius $\Delta R$ of $0.7$.
386
387%\begin{figure}[!h]
388%\begin{center}
389%\includegraphics[width=0.6\columnwidth]{btag}
390%\caption{Default efficiency of $b$-tag for jets coming from $b$ quarks, $c$ quarks and from other particles (jets from gluons or $u$, $d$ and $s$ quarks).}
391%\label{fig:btag}
392%\end{center}
393%\end{figure}
394
395
396\subsection{\texorpdfstring{$\tau$}{\texttau} identification}
397
398Jets originating from $\tau$-decays are identified using an identification procedure consistent with the one applied in a full detector simulation~\cite{bib:cmsjetresolution}.
399The tagging rely 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 criterium. Secondly, the particles arisen from the $\tau$ lepton produce narrow jets in the calorimeter (\textit{collimation}).
400
401\begin{table}[!h]
402\begin{center}
403\caption{ Branching rations for $\tau^-$ lepton~\cite{bib:pdg}. $h^\pm$ and $h^0$ refer to charged and neutral hadrons, respectively. $n \geq 0$ and $m \geq 0$ are integers.
404\vspace{0.5cm} }
405\begin{tabular}[!h]{ll}
406\hline
407 \multicolumn{2}{l}{\textbf{Leptonic decays}}\\
408 $ \tau^- \rightarrow e^- \ \bar \nu_e \ \nu_\tau$ & $17.9\% $ \\
409 $ \tau^- \rightarrow \mu^- \ \bar \nu_\mu \ \nu_\tau$ & $17.4\%$ \\
410 \multicolumn{2}{l}{\textbf{Hadronic decays}}\\
411 $ \tau^- \rightarrow h^-\ n\times h^\pm \ m\times h^0\ \nu_\tau$ & $64.7\%$ \\
412 $ \tau^- \rightarrow h^-\ m\times h^0 \ \nu_\tau$ & $50.1\%$ \\
413 $ \tau^- \rightarrow h^-\ h^+ h^- m\times h^0 \ \nu_\tau$ & $14.6\%$ \\
414\hline
415\end{tabular}
416\label{tab:taudecay}
417\end{center}
418\end{table}
419
420
421%\begin{wrapfigure}{l}{0.3\columnwidth}
422\begin{figure}[!h]
423\begin{center}
424\includegraphics[width=0.6\columnwidth]{Tau}
425\caption{Illustration of the identification of $\tau$-jets. The jet cone is narrow and contains only one track.}
426\label{h_WW_ss_cut1}
427\end{center}
428\end{figure}
429%\end{wrapfigure}
430
431
432\subsubsection*{Electromagnetic collimation}
433
434To 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.
435To be taken into account, a calorimeter tower should have a transverse energy $E_T^\textrm{tower}$ above a given threshold.
436A 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}).
437
438\begin{figure}[!h]
439\begin{center}
440\includegraphics[width=\columnwidth]{Tau2}
441\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 $\ell = e, \mu, \tau$.
442Events generated with \textsc{MadGraph/MadEvent}~\cite{bib:mgme}.
443Final state hadronisation is performed by \textsc{Pythia}~\cite{bib:pythia}.
444Histogram entries correspond to true $\tau$-jets, matched with generator level data. }
445\label{fig:tau2}
446\end{center}
447\end{figure}
448
449\subsubsection*{Tracking isolation}
450
451The 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 $R^\textrm{tracks}$.
452This cone should be entirely pointing to the tracker to be taken into account. Default values of these parameters are given in Tab.~\ref{tab:tauRef}.
453
454
455
456\begin{figure}[!h]
457\begin{center}
458\includegraphics[width=\columnwidth]{Tau1}
459\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}.
460Histogram entries correspond to true $\tau$-jets, matched with generator level data.}
461\label{fig:tau1}
462\end{center}
463\end{figure}
464
465
466\begin{table}[!h]
467\begin{center}
468\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 calotowers $E_T^\textrm{tower}$ 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.
469\vspace{0.5cm} }
470\begin{tabular}[!h]{lll}
471\hline
472Parameter & Card flag & Value\\\hline
473\multicolumn{3}{l}{\textbf{Electromagnetic collimation}} \\
474$R^\textrm{em}$ & \texttt{TAU\_energy\_scone } & $0.15$\\
475min $E_{T}^\textrm{tower}$ & {\verb JET_M_seed } & $1.0$~GeV\\
476$C_{\tau}$ & \texttt{TAU\_energy\_frac} & $0.95$\\
477\multicolumn{3}{l}{\textbf{Tracking isolation}} \\
478$R^\textrm{tracks}$ & \texttt{TAU\_track\_scone} & $0.4$\\
479min $p_T^{tracks}$ & \texttt{PTAU\_track\_pt } & $2$ GeV\\
480\multicolumn{3}{l}{\textbf{$\tau$-jet candidate}} \\
481$\min p_T$ & \texttt{TAUJET\_pt} & $10$ GeV\\
482\hline
483\end{tabular}
484\label{tab:tauRef}
485\end{center}
486\end{table}
487
488\subsubsection*{Purity}
489Once both electromagnetic collimation and tracking isolation are applied, a threshold on the $p_T$ of the $\tau$-jet candidate is requested to purify the collection. This procedure selects $\tau$ leptons decaying hadronically with a typical efficiency of $60\%$.
490
491\subsection{Missing transverse energy}
492In an ideal detector, momentum conservation imposes the transverse momentum of the observed final state $\overrightarrow{p_T}^\textrm{obs}$ to be equal to the $\overrightarrow{p_T}$ vector sum of the invisible particles, written $\overrightarrow{p_T}^\textrm{miss}$.
493\begin{equation}
494\overrightarrow{p_T} = \left(
495\begin{array}{c}
496p_x\\
497p_y\\
498\end{array}
499\right)
500~ \textrm{and} ~
501\left\{
502\begin{array}{l}
503 p_x^\textrm{miss} = - p_x^\textrm{obs} \\
504 p_y^\textrm{miss} = - p_y^\textrm{obs} \\
505\end{array}
506\right.
507\end{equation}
508The \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.
509In a real experiment, calorimeters measure energy and not momentum. Any problem affecting the detector (dead channels, misalignment, noisy towers, cracks) worsens directly the measured missing transverse energy $\overrightarrow {E_T}^\textrm{miss}$. In this document, \textsc{met} is based on the calorimetric towers and only muons and neutrinos are not taken into account for its evaluation:
510\begin{equation}
511\overrightarrow{E_T}^\textrm{miss} = - \sum^\textrm{towers}_i \overrightarrow{E_T}(i)
512\end{equation}
513
514
515\section{Trigger emulation}
516
517New 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 $2 \times 10^{-3}~\textrm{nb}$ ($pp \rightarrow WH$, $m_H=115~\textrm{GeV}$).
518
519High statistics are required for data analyses, consequently imposing high luminosity, i.e. a high collision rate.
520As 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.
521This 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.}.
522Dedicated 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.
523
524Most 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 $p_T^e > 50~\textrm{GeV}$.
525
526A 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.
527In a real experiment, the online selection is often divided into several steps (or \textit{levels}).
528This splits the overall reduction factor into a product of smaller factors, corresponding to the different trigger levels.
529This is related to the architecture of the experiment data acquisition chain, with limited electronic buffers requiring a quick decision for the first trigger level.
530First 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.
531Later levels are more complex, of finer-but-not-final quality and based on full detector data.
532
533Real triggers are thus intrinsically based on reconstructed data with a worse resolution than final analysis data.
534On the contrary, same data are used in \textsc{Delphes} for trigger emulation and for final analyses.
535
536\section{Validation}
537
538\textsc{Delphes} performs a fast simulation of a collider experiment.
539Its quality and validity are assessed by comparing to resolution of the reconstructed data to the \textsc{cms} detector expectations.
540
541Electrons and muons match by construction to the experiment designs, as the Gaussian smearing of their kinematical properties is defined according to the experiment resolution.
542Similarly, the $b$-tagging efficiency (for real $b$-jets) and misidentification rates (for fake $b$-jets) are taken from the expected values of the experiment.
543Unlike these simple objects, jets and missing transverse energy should be carefully cross-checked.
544
545\subsection{Jet resolution}
546
547The 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.
548
549This 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
550\begin{equation}
551\Delta R = \sqrt{ \big(\eta^\textrm{rec} - \eta^\textrm{MC} \big)^2 + \big(\phi^\textrm{rec} - \phi^\textrm{MC} \big)^2}<0.25.
552\end{equation}
553The jets made of generator-level particles, or \textsc{mc} jets, are obtained by applying the same clustering algorithm to all particles considered as stable after hadronisation.
554Jets produced by \textsc{Delphes} and satisfying the matching criterium are called hereafter \textit{reconstructed jets}.
555
556The ratio of the transverse energies of every reconstructed jet $E_T^\textrm{rec}$ and its corresponding \textsc{mc} jet $E_T^\textrm{MC}$ is calculated in each $\hat{p}_T$ bin.
557The $E_T^\textrm{rec}/E_T^\textrm{MC}$ histogram is fitted with a Gaussian distribution in the interval \mbox{$\pm 2$~\textsc{rms}} centered around the mean value.
558The resolution in each $\hat{p}_T$ bin is obtained by the fit mean $\langle x \rangle$ and variance $\sigma^2(x)$:
559\begin{equation}
560%\frac{\sigma(R_{jet})}{\langle R_{jet} \rangle }=
561\frac{\sigma \Big (\frac{E_T^{rec}}{E_T^{MC}} \Big)_\textrm{fit}}{ \Big \langle \frac{E_T^{rec}}{E_T^{MC}} \Big \rangle_\textrm{fit}}~
562\Big( \hat{p}_T(i) \Big)\textrm{, for all }i.
563\end{equation}
564
565\begin{figure}[!h]
566\begin{center}
567\includegraphics[width=\columnwidth]{resolutionJet}
568\caption{Resolution of the transverse energy of reconstructed jets $E_T^\textrm{rec}$ as a function of the transverse energy of the closest jet of generator-level particles $E_T^\textrm{MC}$. The maximum separation between the reconstructed and \textsc{mc} jets is $\Delta R= 0.25$. Pink line is the fit result for comparison to the \textsc{cms} resolution, in blue.}
569\label{fig:jetresol}
570\end{center}
571\end{figure}
572
573The resulting jet resolution as a function of $E_T^\textrm{MC}$ is shown in Fig.~\ref{fig:jetresol}.
574This distribution is fitted with a function of the following form:
575\begin{equation}
576\frac{a}{E_T^\textrm{MC}}\oplus \frac{b}{\sqrt{E_T^\textrm{MC}}}\oplus c,
577\end{equation}
578where $a$, $b$ and $c$ are the fit parameters.
579It is then compared to the resolution obtained with a recent version of the simulation package of the \textsc{cms} detector~\cite{bib:cmsjetresolution}. The resolution curves from \textsc{Delphes} and \textsc{cms} are in good agreement.
580
581\subsection{MET resolution}
582
583All 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.
584The resolution of the $\overrightarrow{E_T}^\textrm{miss}$ variable, as obtained with \textsc{Delphes}, is then crucial.
585
586The samples used to study the \textsc{met} performance are identical to those used for the jet validation.
587It is worth noting that the contribution to $E_T^\textrm{miss}$ from muons is negligible in the studied sample.
588The input samples are divided in five bins of scalar $E_T$ sums $(\Sigma E_T)$. This sum, called \textit{total visible transverse energy}, is defined as the scalar sum of transverse energy in all towers.
589The quality of the \textsc{met} reconstruction is checked via the resolution on its horizontal component $E_x^\textrm{miss}$.
590
591The $E_x^\textrm{miss}$ resolution is evaluated in the following way.
592The distribution of the difference between $E_x^\textrm{miss}$ in \textsc{Delphes} and at generator-level is fitted with a Gaussian function in each $(\Sigma E_T)$ bin. The fit \textsc{rms} gives the \textsc{met} resolution in each bin.
593The resulting value is plotted in Fig.~\ref{fig:resolETmis} as a function of the total visible transverse
594energy.
595
596\begin{figure}[!h]
597\begin{center}
598\includegraphics[width=\columnwidth]{resolutionETmis}
599\caption{$\sigma(E^\textrm{miss}_{x})$ as a function on the scalar sum of all towers ($\Sigma E_T$) for $pp \rightarrow gg$ events.}
600\label{fig:resolETmis}
601\end{center}
602\end{figure}
603
604The resolution $\sigma_x$ of the horizontal component of \textsc{met} is observed to behave like
605\begin{equation}
606\sigma_x = \alpha ~(\Sigma E_T) ~~~(\mathrm{GeV}^{1/2}),
607\end{equation}
608where the $\alpha$ parameter is depending on the resolution of the calorimeters.
609
610The \textsc{met} resolution expected for the \textsc{cms} detector for similar events is $\sigma_x = (0.6-0.7) ~ (\Sigma E_T) ~ \mathrm{GeV}^{1/2}$ with no pile-up\footnote{\textit{Pile-up} events are extra simultaneous $pp$ collision occuring at the same bunch crossing.}~\cite{bib:cmsjetresolution}.
611The same quantity obtained by \textsc{Delphes} is in excellent agreement with the expectations of the general purpose detector, as $\alpha = 0.68$.
612
613\subsection{\texorpdfstring{$\tau$}{\texttau}-jet efficiency}
614Due to the complexity of their reconstruction algorithm, $\tau$-jets have also to be checked.
615Tab.~\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.
616
617\begin{table}[!h]
618\begin{center}
619\caption{Reconstruction efficiencies of $\tau$-jets in decays from $Z$ or $H$ bosons, in \textsc{Delphes} and in the \textsc{cms} experiment~\cite{bib:cmstauresolution}.\vspace{0.5cm}}
620\begin{tabular}{lll}
621\hline
622\multicolumn{2}{c}{\textsc{cms}} & \\
623$Z \rightarrow \tau^+ \tau^-$ & $38 \%$ & \\
624$H \rightarrow \tau^+ \tau^-$ & $36 \%$ & $m_H = 150~\textrm{GeV}$ \\
625$H \rightarrow \tau^+ \tau^-$ & $47 \%$ & $m_H = 300~\textrm{GeV}$ \\
626\multicolumn{2}{c}{\textsc{Delphes}} & \\
627$H \rightarrow \tau^+ \tau^-$ &$42 \%$ & $m_H = 140~\textrm{GeV}$ \\
628\hline
629\end{tabular}
630\label{tab:taurecoefficiency}
631\end{center}
632\end{table}
633
634
635\section{Visualisation}
636
637When performing an event analysis, a visualisation tool is useful to convey information about the detector layout and the event topology in a simple way. The \textit{Fast and Realistic OpenGL Displayer} \textsc{frog}~\cite{bib:Frog} has been interfaced in \textsc{Delphes}, allowing an easy display of the defined detector configuration\footnote{\texttt{[code] } To prepare the visualisation, the \texttt{FLAG\_frog} parameter should be equal to $1$.}.
638
639% \begin{figure}[!h]
640% \begin{center}
641% \includegraphics[width=\columnwidth]{Detector_Delphes_1}
642% \caption{Layout of the generic detector geometry assumed in \textsc{Delphes}. The innermost layer, close to the interaction point, is a central tracking system (pink), embedded into a solenoidal magnetic field.
643% It is surrounded by a central calorimeter volume (green) with both electromagnetic and hadronic sections.
644% The outer layer of the central system (red) consist of a muon system.
645% In addition, two end-cap calorimeters (blue) extend the pseudorapidity coverage of the central detector.
646% The actual detector granularity and extension is defined in the smearing card.
647% The detector is assumed to be strictly symmetric around the beam axis (black line).
648% Additional forward detectors are not depicted.}
649% \label{fig:GenDet}
650% \end{center}
651% \end{figure}
652
653Two and three-dimentional 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 \textsc{Delphes} is shown in Fig.~\ref{fig:GenDet3}
654%, \ref{fig:GenDet}
655 and~\ref{fig:GenDet2}.
656As pointed before, the detector is assumed to be strictly symmetric around the beam axis.
657The extensions of the central tracking system, the central calorimeters and both forward calorimeters are visible.
658Nevertheless, 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.
659
660\begin{figure}[!h]
661\begin{center}
662\includegraphics[width=\columnwidth]{Detector_Delphes_2b}
663\caption{Layout of the generic detector geometry assumed in \textsc{Delphes}. Open 3D-view of the detector with solid volumes. Same colour codes as for Fig.~\ref{fig:GenDet3} are applied. Additional forward detectors are not depicted.}
664\label{fig:GenDet2}
665\end{center}
666\end{figure}
667
668Deeper understanding of interesting physics processes is possible by displaying the events themselves.
669The visibility of each set of objects ($e^\pm$, $\mu^\pm$, $\tau^\pm$, jets, transverse missing energy) is enhanced by a color coding.
670Moreover, kinematical information of each object is visible by a simple mouse action.
671As an illustration, an associated photoproduction of a $W$ boson and a $t$ quark is shown in Fig.~\ref{fig:wt}.
672This 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}.
673This leading proton survives from the photon emission and subsequently from the $pp$ interaction, and is present in the final state.
674As 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.
675The experimental signature is a lack of hadronic activity in one forward hemisphere, where the surviving proton escapes.
676The $t$ quark decays into a $W$ boson and a $b$ quark.
677Both $W$ bosons decay into leptons ($W \rightarrow \mu \nu_\mu$ and $W \rightarrow \tau \nu_\tau$).
678The balance between the missing transverse energy and the charged lepton pair is clear, as well as the presence of an empty forward region.
679
680\begin{figure}[!h]
681\begin{center}
682\includegraphics[width=\columnwidth]{Events_Delphes_1}
683\caption{Example of $pp(\gamma p \rightarrow Wt)pY$ event, with $t \rightarrow Wb$. One $W$ boson decays into a $\mu \nu_\mu$ pair and the second one into a $\tau \nu_\tau$ pair. The surviving proton leaves a forward hemisphere with no hadronic activity. The isolated muon is shown as the blue vector. The $\tau$-jet is the cone around the green vector, while the reconstructed missing energy is shown in gray. One jet is visible in one forward region, along the beamline axis, opposite to the direction of the escaping proton.}
684\label{fig:wt}
685\end{center}
686\end{figure}
687
688\section{Conclusion and perspectives}
689
690% \subsection{version 1}
691% We have described here the major features of the \textsc{Delphes} framework, introduced for the fast simulation of a collider experiment.
692% It has already been used for several phenomenological studies, in particular in photon interactions at the \textsc{lhc}.
693%
694% \textsc{Delphes} takes the output of event generators, in various formats, and yields analysis object data.
695% The simulation applies the resolutions of central and forward detectors by smearing the kinematical properties of final state particles.
696% It yields tracks in a solenoidal magnetic field and calorimetric towers.
697% Realistic reconstruction algorithms are run, including the \textsc{FastJet} package, to produce collections of $e^\pm$, $\mu^\pm$, jets and $\tau$-jets. $b$-tag and missing transverse energy are also evaluated.
698% The output is validated by comparing to the \textsc{cms} expected performances.
699% A trigger stage can be emulated on the output data.
700% At last, event visualisation is possible through the \textsc{Frog} 3D event display.
701%
702%
703% \textsc{Delphes} has been developped 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.
704%
705%
706% \subsection{version 2}
707We 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}.
708
709\textsc{Delphes} takes the output of event generators and yields analysis object data.
710The simulation includes central and forward detectors to produce realistic observables using standard reconstruction algorithms.
711Moreover, the framework allows trigger emulation and 3D event visualisation.
712
713\textsc{Delphes} has been developped 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.
714
715
716
717\section*{Acknowledgements}
718\addcontentsline{toc}{section}{Acknowledgements}
719The authors would like to thank 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 greatful to Alice Dechambre and Simon de Visscher for being beta testers of the complete package.
720Part of this work was supported by the Belgian Federal Office for Scientific, Technical and Cultural Affairs through the Interuniversity Attraction Pole P6/11.
721
722
723\begin{thebibliography}{99}
724\addcontentsline{toc}{section}{References}
725
726\bibitem{bib:Delphes} \textsc{Delphes}, \href{http://www.fynu.ucl.ac.be/delphes.html}{www.fynu.ucl.ac.be/delphes.html}
727%hepforge:
728\bibitem{bib:Root} %\textsc{Root}, \textit{An Object Oriented Data Analysis Framework},
729R. Brun, F. Rademakers, Nucl. Inst. \& Meth. in \textbf{Phys. Res. A} 389 (1997) 81-86.
730\bibitem{bib:ExRootAnalysis} %\textit{The} \textsc{ExRootAnalysis} \textit{analysis steering utility},
731P. Demin, (2006), unpublished. Now part of \textsc{MadGraph/MadEvent}.
732\bibitem{bib:Hector} %\textsc{Hector}, \textit{a fast simulator for the transport of particles in beamlines},
733X. Rouby, J. de Favereau, K. Piotrzkowski, \textbf{JINST} 2 P09005 (2007).
734\bibitem{bib:FastJet} %\textit{The} \textsc{FastJet} \textit{package},
735M. Cacciari, G. Salam, \textbf{Phys. Lett. B} 641 (2006) 57.
736\bibitem{bib:jetclu} %\textsc{cdf} Run I legacy algorithm,
737F. Abe et al. (CDF Coll.), \textbf{Phys. Rev. D} 45, (1992) 1448.
738\bibitem{bib:midpoint} %Run II Jet Physics: Proceedings of the Run II QCD and Weak Boson Physics Workshop,
739G.C. Blazey, et al., \href{http://arxiv.org/abs/hep-ex/0005012}{arXiv:hep-ex/0005012}.
740\bibitem{bib:SIScone} %\textsc{SIScone}, \textit{A practical Seedless Infrared-Safe Cone jet algorithm},
741G.P. Salam, G. Soyez, \textbf{JHEP} 0705:086 (2007).
742\bibitem{bib:ktjet} S. Catani, Y. L. Dokshitzer, M. H. Seymour, B. R. Webber, \textbf{Nucl. Phys. B} 406 (1993) 187; S. D. Ellis, D. E. Soper, \textbf{Phys. Rev. D} 48 (1993) 3160.
743\bibitem{bib:aachen} Y.L. Dokshitzer, G.D. Leder, S. Moretti, B.R. Webber, \textbf{JHEP} 9708 (1997) 001; M. Wobisch, T. Wengler, arXiv:hep-ph/9907280.
744\bibitem{bib:antikt} %\textit{The anti-kt jet clustering algorithm},
745M. Cacciari, G. P. Salam, G. Soyez, \textbf{JHEP} 0804 (2008) 063.
746\bibitem{bib:cmsjetresolution} CMS Collaboration, \textbf{CERN/LHCC} 2006-001; \textbf{CMS IN} 2007/053.
747\bibitem{bib:pdg} C. Amsler et al. (Particle Data Group), \textbf{Phys. Lett. B} 667 (2008) 1.
748\bibitem{bib:whphotoproduction} S. Ovyn, \textbf{Nucl. Phys. Proc. Suppl.} 179-180 (2008) 269-276.
749\bibitem{bib:mgme} %\textsc{MadGraph/MadEvent v4}, \textit{The New Web Generation},
750J. Alwall, et al., \textbf{JHEP} 0709:028 (2007).
751\bibitem{bib:pythia} %\textsc{Pythia 6.4}, \textit{Physics and Manual},
752T. Sjostrand, S. Mrenna, P. Skands, \textbf{JHEP} 05 (2006) 026.
753\bibitem{bib:cmstauresolution} %\textit{Study of $\tau$-jet identification in CMS},
754R. Kinnunen, \textbf{CMS NOTE} 1997/002.
755\bibitem{bib:Frog} L. Quertenmont, V. Roberfroid, hep-ex/xxx.
756\bibitem{bib:wtphotoproduction} J. de Favereau de Jeneret, S. Ovyn, \textbf{Nucl. Phys. Proc. Suppl.} 179-180 (2008) 277-284; S. Ovyn, J. de Favereau de Jeneret, \href{http://arxiv.org/pdf/0806.4841v1}{arXiv:hep-ph/0806.4841}
757\bibitem{bib:mcfio} P. Lebrun, L. Garren, Copyright (c) 1994-1995 Universities Research Association, Inc.
758\end{thebibliography}
759
760\onecolumn
761\appendix
762
763\section{User manual}
764
765The available code is a zipped tar file which comes with everything needed to run the \textsc{Delphes} package, assuming a running.
766The package includes \texttt{ExRootAnalysis}~\cite{bib:ExRootAnalysis}, \textsc{Hector}~\cite{bib:Hector},
767\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}.
768Nevertheless 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/}.
769
770\subsection{Getting started}
771
772In order to run \textsc{Delphes} on your system, first download is sources and compile it:\\
773\begin{quote}
774\begin{verbatim}
775me@mylap:~$ http://www.fynu.ucl.ac.be/users/s.ovyn/Delphes/files/Delphes_V_*.tar.gz
776me@mylap:~$ tar -xvf Delphes_V_*.tar.gz
777me@mylap:~$ cd Delphes_V_*.*
778me@mylap:~$ ./genMakefile.tcl > Makefile
779me@mylap:~$ make
780\end{verbatim}
781\end{quote}
782\subsection{Running \textsc{Delphes} on your events}
783
784In 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 }) file. 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 of \textsc{Delphes} that will contain the particle-level information ({\verb GEN } {\verb tree }), the analysis data objects after reconstruction ({\verb Analysis } {\verb tree }), and the results of the trigger emulation ({\verb Trigger } {\verb tree }).
785
786\begin{quote}
787\begin{verbatim}
788me@mylaptop:~$ ./Delphes inputlist.list OutputRootFileName.root
789\end{verbatim}
790\end{quote}
791
792\subsubsection{Setting the run configuration}
793
794The 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.
795Please note that the either you provide those two datacards, either the running will be done using the default parameters defined in the constructor of the class {\verb RESOLution()}. If you chose a different detector or running configuration you will need to edit the datacards accordingly.
796
797\begin{enumerate}
798
799\item{\bf The run card }
800
801Contains all needed information to run \textsc{Delphes}
802\begin{itemize}
803 \item The following parameters are available: detector parameters, including calorimeter and tracking coverage and resolution, transverse energy thresholds allowed for reconstructed objects, jet algorithm to use as well as jet parameters.
804 \item Four flags, {\verb FLAG_bfield }, {\verb FLAG_vfd }, {\verb FLAG_trigger } and {\verb FLAG_frog } should be assigned to decide if the magnetic field propagation, the very forward detectors acceptance, the trigger selection and the preparation for \textsc{Frog} display respectively are running by \textsc{Delphes}.
805 \end{itemize}
806
807If no datacard is provided ny the user, the default one is used that contains the followings smearing and running parameters:
808\begin{quote}
809\begin{verbatim}
810# Detector characteristics
811CEN_max_tracker 2.5 // Maximum tracker coverage
812CEN_max_calo_cen 3.0 // central calorimeter coverage
813CEN_max_calo_fwd 5.0 // forward calorimeter pseudorapidity coverage
814CEN_max_mu 2.4 // muon chambers pseudorapidity coverage
815
816# Energy resolution for electron/photon
817# \sigma/E = C + N/E + S/\sqrt{E}
818ELG_Scen 0.05 // S term for central ECAL
819ELG_Ncen 0.25 // N term for central ECAL
820ELG_Ccen 0.005 // C term for central ECAL
821ELG_Cfwd 0.107 // S term for FCAL
822ELG_Sfwd 2.084 // C term for FCAL
823ELG_Nfwd 0.0 // N term for FCAL
824
825# Energy resolution for hadrons in ecal/hcal/hf
826# \sigma/E = C + N/E + S/\sqrt{E}
827HAD_Shcal 1.5 // S term for central HCAL
828HAD_Nhcal 0. // N term for central HCAL
829HAD_Chcal 0.05 // C term for central HCAL
830HAD_Shf 2.7 // S term for FCAL
831HAD_Nhf 0. // N term for FCAL
832HAD_Chf 0.13 // C term for FCAL
833
834# Muon smearing
835MU_SmearPt 0.01
836
837# Tracking efficiencies
838TRACK_ptmin 0.9 // minimal pT
839TRACK_eff 100 // efficiency associated to the tracking
840
841# Calorimetric towers
842TOWER_number 40
843### list of the edges of each tower in eta for eta>0 assuming
844###a symmetric detector in eta<0
845### the list starts with the lower edge of the most central tower
846### the list ends with the higher edged of the most forward tower
847### there should be NTOWER+1 values
848TOWER_eta_edges 0. 0.087 0.174 0.261 0.348 0.435 0.522 0.609 0.696 0.783
849 0.870 0.957 1.044 1.131 1.218 1.305 1.392 1.479 1.566 1.653
850 1.740 1.830 1.930 2.043 2.172 2.322 2.500 2.650 2.868 2.950
851 3.125 3.300 3.475 3.650 3.825 4.000 4.175 4.350 4.525 4.700
852 5.000
853
854### list of the tower size in phi (in degrees), assuming that all
855### towers are similar in phi for a given eta value
856### the list starts with the phi-size of the most central tower (eta=0)
857### the list ends with the phi-size of the most forward tower
858### there should be NTOWER values
859#TOWER_dphi 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 10
860 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 20 20
861
862# Thresholds for reconstructed objetcs
863PTCUT_elec 10.0
864PTCUT_muon 10.0
865PTCUT_jet 20.0
866PTCUT_gamma 10.0
867PTCUT_taujet 10.0
868
869# General jet variable
870JET_coneradius 0.7 // generic jet radius
871JET_jetalgo 1 // Jet aglorithm selection
872JET_seed 1.0 // minimum seed to start jet reconstruction
873
874# Tagging definition
875BTAG_b 40
876BTAG_mistag_c 10
877BTAG_mistag_l 1
878
879# FLAGS
880FLAG_bfield 0 // 1 to run the bfield propagation else 0
881FLAG_vfd 1 // 1 to run the very forward detectors else 0
882FLAG_trigger 1 // 1 to run the trigger selection else 0
883FLAG_frog 1 // 1 to run the FROG event display
884
885# In case BField propagation allowed
886TRACK_radius 129 // radius of the BField coverage
887TRACK_length 300 // length of the BField coverage
888TRACK_bfield_x 0 // X composant of the BField
889TRACK_bfield_y 0 // Y composant of the BField
890TRACK_bfield_z 3.8 // Z composant of the BField
891
892# In case Very forward detectors allowed
893VFD_min_calo_vfd 5.2 // very forward calorimeter (if any) like CASTOR
894VFD_max_calo_vfd 6.6
895VFD_min_zdc 8.3
896VFD_s_zdc 140 // distance of the ZDC, from the IP, in [m]
897
898RP_220_s 220 // distance of the RP to the IP, in meters
899RP_220_x 0.002 // distance of the RP to the beam, in meters
900RP_420_s 420 // distance of the RP to the IP, in meters
901RP_420_x 0.004 // distance of the RP to the beam, in meters
902
903# In case FROG event display allowed
904NEvents_Frog 100
905
906\end{verbatim}
907\end{quote}
908
909
910\item{\bf The trigger card }
911
912Contains the definition of all trigger bits. Cuts can be applied on the transverse momentum of electrons, muons, jets, tau-jets, photons and transverse missing energy. The following ``codename'' should be used so that \textsc{Delphes} can correctly translate the input list of trigger bit into selection algorithms:
913
914\begin{quote}
915\begin{tabular}{ll}
916{\it Trigger flag} & {\it Corresponding object}\\
917{\verb ELEC_PT } & electron \\
918{\verb MUON_PT } & muon \\
919{\verb JET_PT } & jet \\
920{\verb TAUJET_PT } & tau-jet \\
921{\verb ETMIS_PT } & transverse missing energy \\
922{\verb GAMMA_PT } & photon \\
923\end{tabular}
924\end{quote}
925
926Moreover, each line in the trigger datacard is allocated to exactly one trigger bit and start with the name of the correcponding trigger. Logical combinaison of several conditions is also possible. If the trigger bit uses the presence of multiple identical objects, the order of their thresholds is not meaningless: they must be defined in decreasing order. Finally, the different requirements on the objects must be separated by a {\verb && } flag. The default trigger card can be found in the data repository of \textsc{Delphes}. An exemple of trigger table consistent with the previous rules is given here:
927\begin{quote}
928\begin{verbatim} DoubleElec >> ELEC_PT: '20' && ELEC_PT: '10' SingleElec and Single Muon >> ELEC_PT: '20' && MUON_PT: '15'
929\end{verbatim}
930\end{quote}
931
932An example (the default trigger card) can be found in {\verb files/trigger.dat }.
933
934\end{enumerate}
935
936\subsubsection{Running the code}
937
938Create the above cards (data/mydetector.dat and data/mytrigger.dat). Create a text file containing the list of input files that will be used by \textsc{Delphes} (with extension *.lhe, *.root or *.hep)
939To run the code, type the following
940\begin{quote}
941\begin{verbatim}
942me@mylaptop:~$ ./Delphes inputlist.list OutputRootFileName.root data/mydetector.dat data/mytrigger.dat
943\end{verbatim}
944\end{quote}
945
946
947\subsection{Getting the \textsc{Delphes} information}
948
949\subsubsection{Contents of the \textsc{Delphes} \textsc{root} trees}
950
951As said upwards, the \textsc{Delphes} \textsc{root} file is subdivided into three \textsc{trees}. All the branches available in those \textsc{trees} together with the reconstructed objects they correspond to are summarised here:
952
953\begin{quote}
954\begin{tabular}{lll}
955{\bf GEN \textsc{tree}} & &\\
956Particle & generator particles from \textsc{hepevt} & {\verb TRootGenParticle }\\
957{\bf Analysis \textsc{tree}} & & \\
958Jet & Jet collection & {\verb TRootJet }\\
959TauJet & Collection of jets tagged as $\tau$-jets & {\verb TRootTauJet }\\
960Electron & Collection of electrons & {\verb TRootElectron }\\
961Muon & Collection of muons & {\verb TRootMuon }\\
962Photon & Collection of photons & {\verb TRootPhoton }\\
963Tracks & Tracker tracks & {\verb TRootTracks }\\
964ETmis & Transverse missing energy information & {\verb TRootETmis }\\
965CaloTower & Calorimetric towers & {\verb TRootCalo }\\
966ZDChits & ????? & {\verb TRootZdcHits }\\
967RP220hits & ????? & {\verb TRootRomanPotHits }\\
968FP420hits &????? & {\verb TRootRomanPotHits }\\
969{\bf Trigger } & &\\
970TrigResult & Acceptance of different trigger bits & {\verb TRootTrigger }\\
971\end{tabular}
972\end{quote}
973
974The third column shows the names of the corresponding classes to be written in a \textsc{root} tree. All classes except the {\verb TRootTrigger }, the {\verb TRootETmis } and the {\verb TRootRomanPotHits } inherit from the class {\verb TRootParticle} which includes the following member functions for accessing the components:
975
976\begin{quote}
977\begin{verbatim}
978
979 float E; // particle energy in GeV
980 float Px; // particle momentum vector (x component) in GeV
981 float Py; // particle momentum vector (y component) in GeV
982 float Pz; // particle momentum vector (z component) in GeV
983
984 float PT; // particle transverse momentum in GeV
985 float Eta; // particle pseudorapidity float Phi; // particle azimuthal angle in rad
986\end{verbatim}
987\end{quote}
988
989In addition to their four-momentum and related quantities, additional properties are available for specific objects. Those are summarized in the following table:
990\begin{quote}
991\begin{tabular}{ll}
992{\bf \texttt{Particle} leave } &\\ \texttt{ int PID; }&\texttt{ // particle HEP ID number }\\
993 \texttt{ int Status; }&\texttt{ // particle status }\\
994 \texttt{ int M1; }&\texttt{ // particle 1st mother }\\
995 \texttt{ int M2; }&\texttt{ // particle 2nd mother }\\
996 \texttt{ int D1; }&\texttt{ // particle 1st daughter }\\
997 \texttt{ int D2; }&\texttt{ // particle 2nd daughter }\\
998 \texttt{ float Charge; }&\texttt{ // electrical charge }\\
999 \texttt{ float T; }&\texttt{ // particle vertex position (t component) }\\
1000 \texttt{ float X; }&\texttt{ // particle vertex position (x component) }\\
1001 \texttt{ float Y; }&\texttt{ // particle vertex position (y component) }\\
1002 \texttt{ float Z; }&\texttt{ // particle vertex position (z component) }\\
1003 \texttt{ float M; }&\texttt{ // particle mass }\\
1004{\bf \texttt{Electron} and \texttt{Muon} leaves } &\\
1005 \texttt{ int Charge } &\\
1006 \texttt{ bool IsolFlag } &\\
1007{\bf \texttt{Jet} leave } &\\
1008 \texttt{ bool Btag } &\\
1009{\bf \texttt{ZDChits} leave } &\\
1010 \texttt{float T; }&\texttt{ // time of flight [s] }\\
1011 \texttt{ int side; }&\texttt{ // -1 or +1 }\\
1012\end{tabular}
1013\end{quote}
1014
1015\subsection{Running an analysis on your \textsc{Delphes} events}
1016
1017To analyze the {\verb Root } {\verb TTree } ntuple of \textsc{Delphes}, the simplest way is to use the {\verb Analysis_Ex.cpp } code which is coming in the {\verb Examples } repository of \textsc{Delphes}. Note that all of this is optional and done to facilitate the analysis, as the output from \textsc{Delphes} is viewable with the standard TBrowser or \textsc{root} and can be analyzed using the MakeClass facility. To run the {\verb Examples/Analysis_Ex.cpp } code, the two following arguments are required: a text file containing the input \textsc{Delphes} root files to run, and the name of the output root file. To run the code:
1018 \begin{quote}
1019\begin{verbatim}
1020./Analysis_Ex input_file.list output_file.root
1021\end{verbatim}
1022 \end{quote}
1023
1024
1025
1026\subsubsection{sdflksdjf}
1027The \texttt{Examples/Trigger\_Only.cpp} code permits to run the trigger selection separately from the general detector simulation on output \textsc{Delphes} root files. An input \textsc{Delphes} root file is mandatory as argument. The new tree containing the trigger information will be added in these file. The trigger datacard is also necessary. To run the code:
1028 \begin{quote}
1029\begin{verbatim}
1030./Trigger_Only input_file.root data/trigger.dat
1031\end{verbatim}
1032 \end{quote}
1033
1034\subsection{Running the \textsc{Frog} event display}
1035
1036\begin{itemize}
1037\item If the { \verb FLAG_frog } was switched on, two files were created during the run of \textsc{Delphes}: {\verb DelphesToFrog.vis } and {\verb DelphesToFrog.geom }. They contain all the needed information to run frog.
1038\item To display the events and the geometry, you first need to compile \textsc{Frog}. Go to the {\verb Utilities/FROG } and type {\verb make }.
1039\item Go back into the main directory and type {\verb ./Utilities/FROG/frog }.
1040\end{itemize}
1041
1042\end{document}
1043
1044%[25] ATLAS Collaboration, Detector and Physics Performance Technical Design
1045% Report, Vols. 1 and 2, CERN–LHCC–99–14 and CERN–LHCC–99–15.
1046%[26] CMS Collaboration, CMS Physics Technical Design Report, CERN/LHCC 2006–001.
1047%[27] A. Djouadi, J. Lykken, K. Monig, Y. Okada, M. J. Oreglia and S. Yamashita,
1048% International Linear Collider Reference Design Report Volume 2: PHYSICS
1049% AT THE ILC, arXiv:0709.1893 [hep-ph].
1050
1051% personnes qui pourraient être intéressées:
1052% Alice, Benjamin
1053% auteurs de arXiv:0801.3359
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