Index: /trunk/paper/CommPhysComp/notes.tex
===================================================================
--- /trunk/paper/CommPhysComp/notes.tex	(revision 559)
+++ /trunk/paper/CommPhysComp/notes.tex	(revision 560)
@@ -36,8 +36,4 @@
 
 \author{X. Rouby}
-%\author{X. Rouby\fnref{freiburg}}
-%\fntext[freiburg]{Now in Physikalisches Institut, Albert-Ludwigs-Universit\"at Freiburg}
-%\ead{xavier.rouby@cern.ch}
-
 \author{V. Lema\^itre}
 
@@ -46,23 +42,11 @@
         B-1348 Louvain-la-Neuve, Belgium}
 
-%\author{X. Rouby}
-%\ead{xavier.rouby@cern.ch}
-
-%\address{Physikalisches Institut,
-%	Albert-Ludwigs-Universit\"at Freiburg,
-%	D-79104 Freiburg-im-Breisgau, Germany}
-
 \begin{abstract}
-% It is always delicate to  know whether theoretical predictions are visible and measurable in a high energy collider experiment due to the complexity of the related detectors, data acquisition chain and software.
-% We introduce here a new \texttt{C++}-based framework, \textit{Delphes}, for fast simulation of
-% a general-purpose experiment. The simulation includes a tracking system, embedded into a magnetic field, calorimetry and a muon
-% system, and possible very forward detectors arranged along the beamline.
-% The framework is interfaced to standard file formats (e.g.\ Les Houches Event File or \texttt{HepMC}) and outputs observable objects for analysis, like missing transverse energy and collections of electrons or jets.
-% The simulation of detector response takes into account the detector resolution, and usual reconstruction algorithms, such as FastJet. A simplified preselection can also be applied on processed data for trigger emulation. Detection of very forward scattered particles relies on the transport in beamlines with the \textit{Hector} software. Finally, the \textsc{FROG} 2D/3D event display is used for visualisation of the collision final states.
-% An overview of \textit{Delphes} is given as well as a few \textsc{LHC} use-cases for illustration.\\ \\
-
-It is sometimes difficult to know whether theoretical predictions can be observed in a high energy collider experiment, especially when expected experimental signature involve jets and missing transverse energy.
-For this purpose, we have designed a new \texttt{C++}-based framework, \textit{Delphes}, performing a fast multipurpose detector response simulation.
-The simulation includes a tracking system, embedded into a magnetic field, calorimeters and a muon system, and possible very forward detectors arranged along the beamline.
+
+This paper presents a new \texttt{C++} framework, \textit{Delphes}, performing a
+fast multipurpose detector response simulation.
+The simulation includes a tracking system, embedded into a magnetic field,
+calorimeters and a muon system, and possible very forward detectors arranged
+along the beamline.
 The framework is interfaced to standard file formats (e.g.\ Les Houches Event File or \texttt{HepMC}) and outputs observables such as isolated leptons, missing transverse energy and collection of jets which can be used for dedicated analyses.
 The simulation of the detector response takes into account the effect of magnetic field, the granularity of the calorimeters and subdetector resolutions.
@@ -72,5 +56,4 @@
 
 \textit{Preprint:} \texttt{CP3-09-01}, \texttt{arXiv:0903.2225 [hep-ph]}\\ \\
-%\includegraphics[scale=0.8]{DELPHESLogoSml}\\
 \includegraphics[scale=0.8]{fig0}\\
 {\bf PROGRAM SUMMARY}\\
@@ -80,9 +63,5 @@
 {\em Current version:} 1.8                                    \\
 {\em Journal Reference:}                                      \\
-  %Leave blank, supplied by Elsevier.
 {\em Catalogue identifier:}                                   \\
-  %Leave blank, supplied by Elsevier.
-%{\em Licensing provisions:}                                   \\
-  %enter "none" if CPC non-profit use license is sufficient.
 {\em Distribution format:}  tar.gz                            \\
 {\em Programming language:}  C++                              \\
@@ -128,22 +107,43 @@
 \section{Introduction}
 
-Multipurpose detectors at high energy colliders are very complex systems. Their simulation is in general performed by means of the GEANT~\citep{bib:geant} package and final observables used for analyses usually require sophisticated reconstruction algorithms.
-
-
-This complexity is handled by large collaborations, and data and the expertise on reconstruction and simulation software are only available to their members. Precise data analyses require a full detector simulation, including transport of the primary and secondary particles through the detector material accounting for the various detector inefficiencies, the dead material, the imperfections and the geometrical details. 
-%\textcolor{blue}{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 signal signatures and their associated backgrounds.
-
-A new framework, called \textit{Delphes}~\citep{bib:delphes}, is introduced here, for the fast simulation of a general-purpose collider experiment.
-Using this framework, observables such as cross-sections and efficiencies after event selection can be estimated for specific reactions.
-Starting from the output of event generators, the simulation of the detector response takes into account the subdetector resolutions, by smearing the kinematics of final-state particles (i.e. those considered as stable by the event generator
-\footnote{In the current \textit{Delphes} version, particles other than electrons ($e^\pm$), photons ($\gamma$), muons ($\mu^\pm$), neutrinos ($\nu_e$, $\nu_\mu$ and $\nu_\tau$) and neutralinos are simulated as hadrons for their interactions with the calorimeters. The simulation of stable particles beyond the Standard Model should therefore be handled with care~\citep{qr:invisibleparticles}.}). 
-% Tracks of charged particles and deposits of energy in calorimetric cells (or \textit{calotowers}) are then created. These two types of quantities are used for the reconstruction of jets and the isolation of leptons.
-
-\textit{Delphes} includes the most crucial experimental features, such as (Fig.~\ref{fig:FlowChart}):
+Multipurpose detectors at high energy colliders are very complex systems. 
+Precise data analyses require a full detector simulation, including transport of
+the primary and secondary particles through the detector material accounting for
+the various detector inefficiencies, the dead material, the imperfections and
+the geometrical details. Their simulation is in general performed by means of
+the GEANT~\citep{bib:geant} package and final observables used for analyses
+usually require sophisticated reconstruction algorithms.
+
+
+This complexity can only be handled by large collaborations. Such simulation is
+very complicated, technical and requires a large \texttt{CPU} power. 
+Phenomenological studies, looking for the observability of given signals, 
+require in general only fast but realistic estimates of the expected signal
+signatures and their associated backgrounds.
+
+In this context, a new framework, called \textit{Delphes}~\citep{bib:delphes},
+has been developped, for a fast simulation of a general-purpose collider
+experiment.
+Using this framework, observables such as cross-sections and efficiencies after
+event selection can be estimated for specific reactions.
+Starting from the output of event generators, the simulation of the detector
+response takes into account the subdetector resolutions, by smearing the
+kinematics of final-state particles (i.e. those considered as stable by the
+event generator
+\footnote{In the current \textit{Delphes} version, particles other than
+electrons ($e^\pm$), photons ($\gamma$), muons ($\mu^\pm$), neutrinos ($\nu_e$,
+$\nu_\mu$ and $\nu_\tau$) and neutralinos are simulated as hadrons for their
+interactions with the calorimeters. The simulation of stable particles beyond
+the Standard Model should therefore be handled with
+care~\citep{qr:invisibleparticles}.}). 
+
+
+\textit{Delphes} includes the most crucial experimental features, such as
+(Fig.~\ref{fig:FlowChart}):
 \begin{enumerate}
 \item the geometry of both central and forward detectors,
 \item the effect of magnetic field on tracks,
-\item the reconstruction of photons, leptons, jets, $b$-jets, $\tau$-jets and missing transverse energy,
+\item the reconstruction of photons, leptons, jets, $b$-jets, $\tau$-jets and
+missing transverse energy,
 \item a lepton isolation,
 \item a trigger emulation,
@@ -155,27 +155,40 @@
 %\includegraphics[scale=0.78]{FlowDELPHES}
 \includegraphics[scale=0.78]{fig1}
-\caption{Flow chart describing the principles behind \textit{Delphes}. Event files coming from external Monte Carlo generators are read by a converter stage (top).
-The kinematics variables of the final-state particles are then smeared according to the tunable subdetector resolutions. 
-Tracks are reconstructed in a simulated solenoidal magnetic field and calorimetric cells sample the energy deposits. Based on these low-level objects, dedicated algorithms are applied for particle identification, isolation and reconstruction. 
-The transport of very forward particles to the near-beam detectors is also simulated. 
-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.
-All user parameters are set in the \textit{Detector/Smearing Card} and the \textit{Trigger Card}. }
+\caption{Flow chart describing the principles behind \textit{Delphes}. Event
+files coming from external Monte Carlo generators are read by a converter stage
+(top).
+The kinematics variables of the final-state particles are then smeared
+according to the tunable subdetector resolutions. 
+Tracks are reconstructed in a simulated solenoidal magnetic field and
+calorimetric cells sample the energy deposits. Based on these low-level objects,
+dedicated algorithms are applied for particle identification, isolation and
+reconstruction. 
+The transport of very forward particles to the near-beam detectors is also
+simulated. 
+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.
+All user parameters are set in the \textit{Detector/Smearing Card} and the
+\textit{Trigger Card}. }
 \label{fig:FlowChart}
 \end{center}
 \end{figure*}
 
-Although \textit{Delphes} yields much realistic results than a simple ``parton-level" analysis, it has some limitations. Detector geometry is idealised, being uniform, symmetric around the beam axis, and having no cracks nor dead material. Secondary interactions, multiple scatterings, photon conversion and bremsstrahlung are also neglected.
-
-Several common datafile formats can be used as input in \textit{Delphes} \citep{qr:inputformat},
-%\footnote{\texttt{[code] }See the \texttt{HEPEVTConverter}, \texttt{HepMCConverter}, \texttt{LHEFConverter} and \texttt{STDHEPConverter} classes.}. 
-in order to process events from many different generators. 
-% The standard Monte Carlo event structures \texttt{StdHEP}~\citep{bib:stdhep} and \texttt{HepMC}~\citep{bib:hepmc} can be used as an input. Besides, \textit{Delphes} can also provide detector response for events read in ``Les Houches Event Format'' (\textsc{LHEF}~\citep{bib:lhe}) and \texttt{*.root} files obtained from \texttt{*.hbook} using the \texttt{h2root} utility from the \textsc{ROOT} framework~\citep{bib:Root}.
-%Afterwards, \textit{Delphes} performs a simple trigger simulation and reconstruct "high-level objects". These informations are organised in classes and each objects are ordered with respect to the transverse momentum.
-\textit{Delphes} creates output data in a ROOT ntuple \citep{bib:Root}.
-This output contains a copy of the generator-level data, the analysis data objects after reconstruction, and possibly the results of the trigger emulation \citep{qr:outputformat}.
-In option
-%\footnote{\texttt{[code]} See the \texttt{FLAG\_LHCO} variable in the detector datacard. This text file format is shortly described in the user manual.}, 
-\textit{Delphes} can produce a reduced output file in \texttt{*.lhco} text format, which is limited to the list of the reconstructed high-level objects in the final states~\citep{qr:lhco}.
+Although \textit{Delphes} yields much realistic results than a simple
+``parton-level" analysis, it has some limitations. Detector geometry is
+idealised, being uniform, symmetric around the beam axis, and having no cracks
+nor dead material. Secondary interactions, multiple scatterings, photon
+conversion and bremsstrahlung are also neglected.
+
+Several common datafile formats can be used as input in \textit{Delphes}
+\citep{qr:inputformat}, in order to process events from many different
+generators. \textit{Delphes} creates output data in a ROOT ntuple
+\citep{bib:Root}. This output contains a copy of the generator-level data, the
+analysis data objects after reconstruction, and possibly the results of the
+trigger emulation \citep{qr:outputformat}.
+In option \textit{Delphes} can produce a reduced output file in \texttt{*.lhco}
+text format, which is limited to the list of the reconstructed high-level
+objects in the final states~\citep{qr:lhco}.
 
 
@@ -183,31 +196,29 @@
 \section{Simulation of the detector response}
 
-The overall layout of the multipurpose detector simulated by \textit{Delphes} is shown in Fig.~\ref{fig:GenDet3}.
-It consists in a central tracking system (\textsc{TRACKER}) surrounded by an electromagnetic and a hadron calorimeters (\textsc{ECAL} and \textsc{HCAL}, each with a central region and two endcaps) and two forward calorimeters (\textsc{FCAL}).
-%  ensure a larger geometric coverage for the measurement of the missing transverse energy. 
-Finally, a muon system (\textsc{MUON}) encloses the central detector volume.
-
-A detector card \citep{qr:detectorcard} allows a large spectrum of running conditions by modifying basic detector parameters, including calorimeter and tracking coverage and resolution, thresholds or jet algorithm parameters. 
-Even if \textit{Delphes} has been developped for the simulation of general-purpose detectors at the \textsc{LHC} (namely, \textsc{CMS} and \textsc{ATLAS}), this input parameter file interfaces a flexible parametrisation for other cases, e.g.\ at future linear colliders~\citep{qr:datacards}.
-If no detector card is provided, predefined values based on ``typical'' \textsc{CMS} acceptances and resolutions are used. 
-%\footnote{\texttt{[code] }Detector and trigger cards for the \textsc{ATLAS} and \textsc{CMS} experiments are also provided in \texttt{data/} directory.}. 
-The geometrical coverage of the various subsystems used in the default configuration are summarised in Tab.~\ref{tab:defEta}.
-The detector is assumed to be strictly symmetric around the beam axis.
+The overall layout of the multipurpose detector simulated by \textit{Delphes}
+is shown in Fig.~\ref{fig:GenDet3}. It consists in a central tracking system
+(\textsc{TRACKER}) surrounded by an electromagnetic and a hadron calorimeters
+(\textsc{ECAL} and \textsc{HCAL}, each with a central region and two endcaps)
+and two forward calorimeters (\textsc{FCAL}). Finally, a muon system
+(\textsc{MUON}) encloses the central detector volume.
+
+A detector card \citep{qr:detectorcard} allows a large spectrum of running
+conditions by modifying basic detector parameters, including calorimeter and
+tracking coverage and resolution, thresholds or jet algorithm parameters. 
+Even if \textit{Delphes} has been developped for the simulation of
+general-purpose detectors at the \textsc{LHC} (namely, \textsc{CMS} and
+\textsc{ATLAS}), this input parameter file interfaces a flexible parametrisation
+for other cases, e.g.\ at future linear colliders~\citep{qr:datacards}.
+If no detector card 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}. The detector is assumed to be strictly symmetric around
+the beam axis.
 
 \begin{table}[t]
-% \begin{table*}[t]
 \begin{center}
 \caption{Default extension in pseudorapidity $\eta$ of the different subdetectors. 
 Full azimuthal ($\phi$) acceptance is assumed.
  \vspace{0.5cm}}
-% \begin{tabular}{llcc}
-% \hline
-% Subdetector & & $\eta$ & $\phi$ \\
-% \textsc{TRACKER} 	& {\verb CEN_max_tracker } 	& $[-2.5; 2.5]$ 	& $[-\pi ; \pi]$\\
-% \textsc{ECAL}, \textsc{HCAL} & {\verb CEN_max_calo_cen }& $[-1.7 ; 1.7]$	& $[-\pi ; \pi]$\\
-% \textsc{ECAL}, \textsc{HCAL} endcaps & {\verb CEN_max_calo_ec }& $[-3 ; -1.7] \& [1.7 ; 3]$	& $[-\pi ; \pi]$\\
-% \textsc{FCAL} 		& {\verb CEN_max_calo_fwd } 	& $[-5 ; -3]$ \& $[3 ;5]$     & $[-\pi ; \pi]$\\
-% \textsc{MUON} 		& {\verb CEN_max_mu } 		& $[-2.4 ; 2.4]$        & $[-\pi ; \pi]$\\ \hline
-% \end{tabular}
 \begin{tabular}{lcc}
 \hline
@@ -221,5 +232,4 @@
 \label{tab:defEta}
 \end{center}
-% \end{table*}
 \end{table}
 
@@ -229,8 +239,10 @@
 \includegraphics[width=\columnwidth]{fig2}
 \caption{
-Profile of layout of the generic detector geometry assumed in \textit{Delphes}. The innermost layer, close to the interaction point, is a central tracking system (pink).
-It is surrounded by a central calorimeter volume (green) with both electromagnetic and hadronic sections. 
-The outer layer of the central system (red) is muon system. In addition, two end-cap calorimeters (blue) extend the pseudorapidity coverage of the central detector. 
-% The detector parameters are defined in the user-configuration card. The extension of the various subdetectors, as defined in Tab.~\ref{tab:defEta}, are clearly visible. The detector is assumed to be strictly symmetric around the beam axis (black line).
+Profile of layout of the generic detector geometry assumed in \textit{Delphes}.
+The innermost layer, close to the interaction point, is a central tracking
+system (pink). It is surrounded by a central calorimeter volume (green) with
+both electromagnetic and hadronic sections. The outer layer of the central
+system (red) is muon system. In addition, two end-cap calorimeters (blue) extend
+the pseudorapidity coverage of the central detector.
 Additional forward detectors are not depicted.
 }
@@ -241,23 +253,41 @@
 
 \subsection{Magnetic field}
-In addition to the subdetectors, the effects of a solenoidal magnetic field are simulated for the charged particles~\citep{qr:magneticfield}
-%\footnote{\texttt{[code] }See the \texttt{TrackPropagation} class.}
-. This affects the position at which charged particles enter the calorimeters and their corresponding tracks. The field extension is limited to the tracker volume and is in particular not applied for muon chambers. Howerver, this is not a limiting factor as the resolution applied for muon reconstruction is the one expected by the experiment, which consequently includes the effects of the magnetic field within the muon system.
+In addition to the subdetectors, the effects of a solenoidal magnetic field are
+simulated for the charged particles~\citep{qr:magneticfield}. This affects the
+position at which charged particles enter the calorimeters and their
+corresponding tracks. The field extension is limited to the tracker volume and
+is in particular not applied for muon chambers. Howerver, this is not a limiting
+factor as the resolution applied for muon reconstruction is the one expected by
+the experiment, which consequently includes the effects of the magnetic field
+within the muon system.
 
 
 \subsection{Tracks reconstruction}
 Every stable charged particle with a transverse momentum above some threshold and lying inside the detector volume covered by the tracker provides a track. 
-By default, a track is assumed to be reconstructed with $90\%$ probability
-%\footnote{\texttt{[code]} The reconstruction efficiency is defined in the detector 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 
-$|\eta| \leq 2.5$~\citep{qr:tracks}. No smearing is currently applied on tracks.
+By default, a track is assumed to be reconstructed with $90\%$ probability if
+its transverse momentum $p_T$ is higher than $0.9~\textrm{GeV}/c$ and if its
+pseudorapidity $|\eta| \leq 2.5$~\citep{qr:tracks}. No smearing is currently
+applied on tracks.
 
 
 \subsection{Calorimetric cells}
 
-The response of the calorimeters to energy deposits of incoming particles depends on their segmentation and resolution, as well as on the nature of the particles themselves. In CMS and ATLAS detectors, for instance, the calorimeter characteristics are not identical in every direction, with typically finer resolution and granularity in the central regions~\citep{bib:cmsjetresolution,bib:ATLASresolution}. It is thus very important to compute the exact coordinates of the entry point of the particles into the calorimeters, via the magnetic field calculations.
-
-The smallest unit for geometrical sampling of the calorimeters is a \textit{cell}; it segments the $(\eta,\phi)$ plane for the energy measurement. No longitudinal segmentation is available in the simulated calorimeters. \textit{Delphes} assumes that ECAL and HCAL have the same segmentations and that the detector is symmetric in $\phi$ and with respect to the $\eta=0$ plane~\citep{qr:calorimetriccells}.
-Fig.~\ref{fig:calosegmentation} illustrates the default calorimeter segmentation.
+The response of the calorimeters to energy deposits of incoming particles
+depends on their segmentation and resolution, as well as on the nature of the
+particles themselves. In CMS and ATLAS detectors, for instance, the calorimeter
+characteristics are not identical in every direction, with typically finer
+resolution and granularity in the central
+regions~\citep{bib:cmsjetresolution,bib:ATLASresolution}. It is thus very
+important to compute the exact coordinates of the entry point of the particles
+into the calorimeters, via the magnetic field calculations.
+
+The smallest unit for geometrical sampling of the calorimeters is a
+\textit{cell}; it segments the $(\eta,\phi)$ plane for the energy measurement.
+No longitudinal segmentation is available in the simulated
+calorimeters. \textit{Delphes} assumes that ECAL and HCAL have the same
+segmentations and that the detector is symmetric in $\phi$ and with respect to
+the $\eta=0$ plane~\citep{qr:calorimetriccells}.
+Fig.~\ref{fig:calosegmentation} illustrates the default calorimeter
+segmentation.
 
 \begin{figure}[!ht]
@@ -284,22 +314,18 @@
 \begin{table}[!h]
 \begin{center}
-\caption{Default values for the resolution of the central and forward calorimeters (for both electromagnetic and hadronic parts). Resolution is parametrised by the \textit{stochastic} ($S$), \textit{noise} ($N$) and \textit{constant} ($C$) terms (Eq.~\ref{eq:caloresolution})~\citep{qr:resolutionterms}.
-%The corresponding parameter name, in the detector card, is given. 
+\caption{Default values for the resolution of the central and forward
+calorimeters (for both electromagnetic and hadronic parts). Resolution is
+parametrised by the \textit{stochastic} ($S$), \textit{noise} ($N$) and
+\textit{constant} ($C$) terms
+(Eq.~\ref{eq:caloresolution})~\citep{qr:resolutionterms}.
 \vspace{0.5cm}}
 \begin{tabular}[!h]{lccc}
 \hline
-%\multicolumn{2}{c}{Resolution Term}   & Value\\\hline
         & $S$ (GeV$^{1/2}$) & $N$ (GeV) & $C$ \\\hline
- %\multicolumn{4}{l}{\textsc{ECAL}} \\
   ECAL            & $0.05$   & $0.25$ & $0.0055$ \\
- %\multicolumn{4}{l}{\textsc{ECAL}, end caps} \\
   ECAL, end caps  & $0.05$  & $0.25$ & $0.0055$ \\
- %\multicolumn{4}{l}{\textsc{FCAL}, electromagnetic part} \\
   FCAL, e.m. part & $2.084$ & $0$    & $0.107$ \\
- %\multicolumn{4}{l}{\textsc{HCAL}} \\
   HCAL            & $1.5$   & $0$    & $0.05$\\
- %\multicolumn{4}{l}{\textsc{HCAL}, end caps} \\
   HCAL, end caps  & $1.5$   & $0$    & $0.05$\\
- %\multicolumn{4}{l}{\textsc{FCAL}, hadronic part} \\
   FCAL, had. part & $2.7$   & $0$    & $0.13$\\
 \hline
@@ -310,6 +336,16 @@
 
 
-Electrons and photons leave their energy in the electromagnetic parts of the calorimeters (\textsc{ECAL} and \textsc{FCAL}, e.m.), while charged and neutral final-state hadrons interact with the hadronic parts (\textsc{HCAL} and \textsc{FCAL}, had.).
-Some long-living particles, such as the $K^0_s$ and $\Lambda$'s, with lifetime $c\tau$ smaller than $10~\textrm{mm}$ are considered as stable particles by the generators although they may decay before the calorimeters. The energy smearing of such particles is therefore performed using the expected fraction of the energy, determined according to their decay products, that would be deposited into the \textsc{ECAL} ($E_{\textsc{ECAL}}$) and into the \textsc{HCAL} ($E_{\textsc{HCAL}}$). Defining $F$ as the fraction of the energy leading to a \textsc{HCAL} deposit, the two energy values are given by
+Electrons and photons leave their energy in the electromagnetic parts of the
+calorimeters (\textsc{ECAL} and \textsc{FCAL}, e.m.), while charged and neutral
+final-state hadrons interact with the hadronic parts (\textsc{HCAL} and
+\textsc{FCAL}, had.).
+Some long-living particles, such as the $K^0_s$ and $\Lambda$'s, with lifetime
+$c\tau$ smaller than $10~\textrm{mm}$ are considered as stable particles by the
+generators although they may decay before the calorimeters. The energy smearing
+of such particles is therefore performed using the expected fraction of the
+energy, determined according to their decay products, that would be deposited
+into the \textsc{ECAL} ($E_{\textsc{ECAL}}$) and into the \textsc{HCAL}
+($E_{\textsc{HCAL}}$). Defining $F$ as the fraction of the energy leading to a
+\textsc{HCAL} deposit, the two energy values are given by
 \begin{equation}
 \left\{
@@ -320,9 +356,17 @@
 \right.
 \end{equation}
-where $0 \leq F \leq 1$. The electromagnetic part is handled similarly as for electrons and photons. 
-The resulting calorimetry energy measurement given after the application of the smearing is then $E = E_{\textsc{HCAL}} + E_{\textsc{ECAL}}$. For $K_S^0$ and $\Lambda$ hadrons, the energy fraction is $F$ is assumed to be $0.7$~\citep{qr:emhadratios}.\\
-
-
-No sharing between neighbouring cells is implemented when particles enter a cell very close to its geometrical edge. Due to the finite segmentation, the smearing, as defined in Eq.~\ref{eq:caloresolution}, is applied directly on the accumulated electromagnetic and hadronic energies of each calorimetric cell. The calorimetric cells enter in the calculation of the missing transverse energy (\textsc{MET}), and are used as input for the jet reconstruction algorithms.
+where $0 \leq F \leq 1$. The electromagnetic part is handled similarly as for
+electrons and photons. The resulting calorimetry energy measurement given after
+the application of the smearing is then $E = E_{\textsc{HCAL}} +
+E_{\textsc{ECAL}}$. For $K_S^0$ and $\Lambda$ hadrons, the energy fraction is
+$F$ is assumed to be $0.7$~\citep{qr:emhadratios}.\\
+
+
+No sharing between neighbouring cells is implemented when particles enter a
+cell very close to its geometrical edge. Due to the finite segmentation, the
+smearing, as defined in Eq.~\ref{eq:caloresolution}, is applied directly on the
+accumulated electromagnetic and hadronic energies of each calorimetric cell. The
+calorimetric cells enter in the calculation of the missing transverse energy
+(\textsc{MET}), and are used as input for the jet reconstruction algorithms.
 
 
@@ -331,58 +375,94 @@
 \section{High-level object reconstruction}
 
-The output file created by \textit{Delphes}~\citep{qr:analysistree} stores the final collections of particles ($e^\pm$, $\mu^\pm$, $\gamma$) and objects (light jets, $b$-jets, $\tau$-jets, $E_T^\textrm{miss}$). In addition, some detector data are added, such as tracks, calorimetric cells and hits in the very forward detectors (\textsc{ZDC}, \textsc{RP220} and \textsc{FP420}, see Sec.~\ref{sec:vfd}). While electrons, muons and photons are easily identified, other quantities are more difficult to evaluate as they rely on sophisticated algorithms (e.g. jets or missing energy).
-
-For most of these objects, their four-momentum and related quantities are directly accessible in \textit{Delphes} output ($E$, $\vec{p}$, $p_T$, $\eta$ and $\phi$). Additional properties are available for specific objects (like the charge and the isolation status for $e^\pm$ and $\mu^\pm$, the result of application of $b$-tag for jets and time-of-flight for some detector hits).
+The output file created by \textit{Delphes}~\citep{qr:analysistree} stores the
+final collections of particles ($e^\pm$, $\mu^\pm$, $\gamma$) and objects (light
+jets, $b$-jets, $\tau$-jets, $E_T^\textrm{miss}$). In addition, some detector
+data are added, such as tracks, calorimetric cells and hits in the very forward
+detectors (\textsc{ZDC}, \textsc{RP220} and \textsc{FP420}, see
+Sec.~\ref{sec:vfd}). While electrons, muons and photons are easily identified,
+other quantities are more difficult to evaluate as they rely on sophisticated
+algorithms (e.g. jets or missing energy).
+
+For most of these objects, their four-momentum and related quantities are
+directly accessible in \textit{Delphes} output ($E$, $\vec{p}$, $p_T$, $\eta$
+and $\phi$). Additional properties are available for specific objects (like the
+charge and the isolation status for $e^\pm$ and $\mu^\pm$, the result of
+application of $b$-tag for jets and time-of-flight for some detector hits).
 
 \subsection{Photon and charged lepton}
-From here onwards, \textit{electrons} refer to both positrons ($e^+$) and electrons ($e^-$), and $\textit{charged leptons}$ refer to electrons and muons ($\mu^\pm$), leaving out the $\tau^\pm$ leptons as they decay before being detected. 
-
-The electron, muon and photon collections contains only the true final-state particles identified via the generator-data.
-In addition, these particles must pass fiducial cuts taking into account the magnetic field effects and some additional reconstruction cuts.
-
-Consequently, no fake candidates enter these collections. However, when needed, fake candidates can be added into the collections at the analysis level, when processing \textit{Delphes} output data. As effects like bremsstrahlung are not taken into account along the lepton propagation in the tracker, no clustering is needed for the electron reconstruction in \textit{Delphes}.
+From here onwards, \textit{electrons} refer to both positrons ($e^+$) and
+electrons ($e^-$), and $\textit{charged leptons}$ refer to electrons and muons
+($\mu^\pm$), leaving out the $\tau^\pm$ leptons as they decay before being
+detected. 
+
+The electron, muon and photon collections contains only the true final-state
+particles identified via the generator-data. In addition, these particles must
+pass fiducial cuts taking into account the magnetic field effects and some
+additional reconstruction cuts.
+
+Consequently, no fake candidates enter these collections. However, when needed,
+fake candidates can be added into the collections at the analysis level, when
+processing \textit{Delphes} output data. As effects like bremsstrahlung are not
+taken into account along the lepton propagation in the tracker, no clustering is
+needed for the electron reconstruction in \textit{Delphes}.
 
 \subsubsection*{Electrons and photons}
-Real electron ($e^\pm$) and photon candidates are associated to the final-state collections if they fall into the acceptance of the tracking system and have a transverse momentum above some threshold (default: $p_T > 10~\textrm{GeV}/c$). 
-Assuming a good measurement of the track parameters in the real experiment, the electron energy can be reasonably recovered. 
-\textit{Delphes} assumes a perfect algorithm for clustering and Brehmstrahlung recovery. Electron energy is smeared according to the resolution of the calorimetric cell where it points to, but independently from any other deposited energy is this cell. 
+Real electron ($e^\pm$) and photon candidates are associated to the final-state
+collections if they fall into the acceptance of the tracking system and have a
+transverse momentum above some threshold (default: $p_T > 10~\textrm{GeV}/c$). 
+Assuming a good measurement of the track parameters in the real experiment, the
+electron energy can be reasonably recovered. \textit{Delphes} assumes a perfect
+algorithm for clustering and Brehmstrahlung recovery. Electron energy is smeared
+according to the resolution of the calorimetric cell where it points to, but
+independently from any other deposited energy is this cell. 
 Electrons and photons may create a candidate in the jet collection.
 
 \subsubsection*{Muons}
-Generator-level muons entering the muon detector acceptance (default: $-2.4 \leq \eta \leq 2.4$) and overpassing some threshold (default : $p_T > 10~\textrm{GeV}/c$) are considered as good candidates for analyses.
-The application of the detector resolution on the muon momentum depends on a Gaussian smearing of the $p_T$~\citep{qr:muonsmearing}.
-%\footnote{\texttt{[code]} See the \texttt{SmearMuon} method.}. 
-Neither $\eta$ nor $\phi$ variables are modified beyond the calorimeters: no additional magnetic field is applied. Multiple scattering is neglected. This implies that low energy muons have in \textit{Delphes} a better resolution than in a real detector.  At last, the particles which might leak out of the calorimeters into the muon systems (\textit{punch-through}) are not considered as muon candidates in \textit{Delphes}.
+Generator-level muons entering the muon detector acceptance (default: $-2.4
+\leq \eta \leq 2.4$) and overpassing some threshold (default : $p_T >
+10~\textrm{GeV}/c$) are considered as good candidates for analyses.
+The application of the detector resolution on the muon momentum depends on a
+Gaussian smearing of the $p_T$~\citep{qr:muonsmearing}.
+Neither $\eta$ nor $\phi$ variables are modified beyond the calorimeters: no
+additional magnetic field is applied. Multiple scattering is neglected. This
+implies that low energy muons have in \textit{Delphes} a better resolution than
+in a real detector.  At last, the particles which might leak out of the
+calorimeters into the muon systems (\textit{punch-through}) are not considered
+as muon candidates in \textit{Delphes}.
 
 \subsubsection*{Charged lepton isolation}
 \label{sec:isolation}
 
-To improve the quality of the contents of the charged lepton collections, isolation criteria can be applied. This requires that electron or muon candidates are isolated in the detector from any other particle, within a small cone. In \textit{Delphes}, charged lepton isolation demands that there is no other charged particle with $p_T>2~\textrm{GeV}/c$ within a cone of $\Delta R = \sqrt{\Delta \eta^2 + \Delta \phi^2} <0.5$ centered on the cell associated to the charged lepton $\ell$, obviously taking the magnetic field into account.
+To improve the quality of the contents of the charged lepton collections,
+isolation criteria can be applied. This requires that electron or muon
+candidates are isolated in the detector from any other particle, within a small
+cone. In \textit{Delphes}, charged lepton isolation demands that there is no
+other charged particle with $p_T>2~\textrm{GeV}/c$ within a cone of $\Delta R =
+\sqrt{\Delta \eta^2 + \Delta \phi^2} <0.5$ centered on the cell associated to
+the charged lepton $\ell$, obviously taking the magnetic field into account.
 
 The result (i.e.\ \textit{isolated} or \textit{not}) is added to the charged lepton measured properties.
 In addition, the sum $P_T$ of the transverse momenta of all tracks but the lepton one within the isolation cone is 
 provided~\citep{qr:isolflag}:
-%\footnote{\texttt{[code] }See the \texttt{IsolFlag} and \texttt{IsolPt} values in the \texttt{Electron} or \texttt{Muon} collections in the \texttt{Analysis} tree, as well as the \texttt{ISOL\_PT} and \texttt{ISOL\_Cone} variables in the detector card.}
 $$ P_T = \sum_{i \neq \ell}^\textrm{tracks} p_T(i)$$
 
-No calorimetric isolation is applied, but the charged lepton collections contain also the ratio $\rho_\ell$ between (1) the sum of the transverse energies in all calorimetric cells in a $N \times N$ grid around the lepton, and (2) the lepton transverse momentum~\citep{qr:caloisolation}:
-%\footnote{\texttt{[code] }Calorimetric isolation parameters in the detector card are \texttt{ISOL\_Calo\_ET} and  \texttt{ISOL\_Calo\_Grid}.}:
-$$ \rho_\ell = \frac{\Sigma_i E_T(i)}{p_T(\ell)}~,~ i\textrm{ in }N \times N \textrm { grid centred on }\ell.$$
-
-
-% \subsubsection*{Forward neutrals}
-% 
-% The zero degree calorimeter hits correspond to neutral particles with a lifetime long enough to reach these detectors (default: $c \tau \geq 140~\textrm{m}$) and very large pseudorapidities (default: $|\eta|>8.3$). In current versions of \textit{Delphes}, only photons and neutrons are considered. Photons are identified thanks to the electromagnetic section of the calorimeter, and if their energy overpasses a given threshold (def. $20$~GeV). Similarly, neutrons are reconstructed according to the resolution of the hadronic section, if their energy exceeds a threshold (def. $50$~GeV)~\citep{qr:fwdneutrals}.
-% %\footnote{\texttt{[code]} These thresholds are defined by the \texttt{ZDC\_gamma\_E} and \texttt{ZDC\_n\_E} variables in the detector card.} (def. $50$~GeV).
-
+No calorimetric isolation is applied, but the charged lepton collections
+contain also the ratio $\rho_\ell$ between (1) the sum of the transverse
+energies in all calorimetric cells in a $N \times N$ grid around the lepton, and
+(2) the lepton transverse momentum~\citep{qr:caloisolation}:
+$$ \rho_\ell = \frac{\Sigma_i E_T(i)}{p_T(\ell)}~,~ i\textrm{ in }N \times N
+\textrm { grid centred on }\ell.$$
 
 
 \subsection{Jet reconstruction}
 
-A realistic analysis requires a correct treatment of partons which have hadronised. Therefore, the most widely currently used jet algorithms have been integrated into the \textit{Delphes} framework using the FastJet tools\footnote{A more detailed description of the jet algorithms is given in the User Manual, in appendix.}. 
-Six different jet reconstruction schemes are available~\citep{bib:FASTJET,qr:jetalgo}. 
-%\footnote{\texttt{[code] }The choice is done by allocating the \texttt{JET\_jetalgo } input parameter in the detector 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 calorimetric cells are used as inputs. Jet algorithms differ in their sensitivity to soft particles or collinear splittings, and in their computing speed performances.
+A realistic analysis requires a correct treatment of partons which have
+hadronised. Therefore, the most widely currently used jet algorithms have been
+integrated into the \textit{Delphes} framework using the FastJet
+tools\footnote{A more detailed description of the jet algorithms is given in the
+User Manual, in appendix.}. Six different jet reconstruction schemes are
+available~\citep{bib:FASTJET,qr:jetalgo}. For all of them, the calorimetric
+cells are used as inputs. Jet algorithms differ in their sensitivity to soft
+particles or collinear splittings, and in their computing speed performances.
  
 \subsubsection*{Cone algorithms}
@@ -390,75 +470,80 @@
 \begin{enumerate}
  
-\item {\it CDF Jet Clusters}~\citep{bib:jetclu}: Cone algorithm forming jets by combining cells lying within a circle (default radius $\Delta R=0.7$) in the $(\eta$, $\phi)$ space. Jets are seeded by all cells with 
- transverse energy $E_T$ above a given threshold (default: $E_T > 1~\textrm{GeV}$)~\citep{qr:jetparams}. 
- 
-\item {\it CDF MidPoint}~\citep{bib:midpoint}: Cone algorithm with additional ``midpoints'' (energy barycentres) in the list of seeds.
- 
-\item {\it Seedless Infrared Safe Cone}~\citep{bib:SIScone}: The \textsc{SISC}one algorithm is simultaneously insensitive to additional soft particles and collinear splittings.
+\item {\it CDF Jet Clusters}~\citep{bib:jetclu}: Cone algorithm forming jets by
+combining cells lying within a circle (default radius $\Delta R=0.7$) in the
+$(\eta$, $\phi)$ space. Jets are seeded by all cells with transverse energy
+$E_T$ above a given threshold (default: $E_T >
+1~\textrm{GeV}$)~\citep{qr:jetparams}. 
+ 
+\item {\it CDF MidPoint}~\citep{bib:midpoint}: Cone algorithm with additional
+``midpoints'' (energy barycentres) in the list of seeds.
+ 
+\item {\it Seedless Infrared Safe Cone}~\citep{bib:SIScone}: The
+\textsc{SISC}one algorithm is simultaneously insensitive to additional soft
+particles and collinear splittings.
 \end{enumerate}
 
 \subsubsection*{Recombination algorithms}
 
-The next three jet algorithms rely on recombination schemes where calorimeter cell pairs are successively merged:
-
-% Two such variables are defined: the distance $d_{ij}$ between each pair of cells $(i,j)$, and a variable $d_{iB}$ (\textit{beam distance}) depending on the transverse momentum of the cell $i$.
-
-% The jet reconstruction algorithm browses the calorimetric cell list. It starts by finding the minimum value $d_\textrm{min}$ of all the distances $d_{ij}$ and $d_{iB}$. If $d_\textrm{min}$ is a $d_{ij}$, the cells $i$ and $j$ are merged into a single cell with a four-momentum $p^\mu = p^\mu (i) + p^\mu (j)$ (\textit{E-scheme recombination}). If $d_\textrm{min}$ is a $d_{iB}$, the cell is declared as a final jet and is removed from the input list. This procedure is repeated until no cells are left in the input list. Further information on these jet algorithms is given here below, using $k_{ti}$, $y_{i}$ and $\phi_i$ as the transverse momentum, rapidity and azimuth of calorimetric cell $i$ and $\Delta R_{ij}= \sqrt{(y_i-y_j)^2+(\phi_i-\phi_j)^2}$ as the jet-radius parameter:
+The next three jet algorithms rely on recombination schemes where calorimeter
+cell pairs are successively merged:
  
 \begin{enumerate}[start=4]
- 
 \item {\it Longitudinally invariant $k_t$ jet}~\citep{bib:ktjet},
-% \begin{equation}
-% \begin{array}{l}
-%   d_{ij} = \min(k_{ti}^2,k_{tj}^2)\Delta R_{ij}^2/R^2 \\
-%   d_{iB}=k_{ti}^2 \\
-% \end{array}
-% \end{equation}
- 
 \item {\it Cambridge/Aachen jet}~\citep{bib:aachen},
-% \begin{equation}
-% \begin{array}{l}
-% d_{ij} = \Delta R_{ij}^2/R^2\\
-% d_{iB}=1 \\
-% \end{array}
-% \end{equation}
- 
-\item {\it Anti $k_t$ jet}~\citep{bib:antikt}, where hard jets are exactly circular in the $(y,\phi)$ plane.
-% \begin{equation}
-% \begin{array}{l}
-% d_{ij} =  \min(1/k_{ti}^2,1/k_{tj}^2)\Delta R_{ij}^2/R^2 \\
-% d_{iB}=1/k_{ti}^2 \\
-% \end{array}
-% \end{equation}
+\item {\it Anti $k_t$ jet}~\citep{bib:antikt}, where hard jets are exactly
+circular in the $(y,\phi)$ plane.
 \end{enumerate}
 
-The recombination algorithms are safe with respect to soft radiations (\textit{infrared}) and collinear splittings. Their implementations are similar except for the definition of the \textit{distances} used during the merging procedure. 
-
-By default, reconstruction uses the CDF cone algorithm. 
-Jets are stored if their transverse energy is higher than $20~\textrm{GeV}$~\citep{qr:ptcutjet}. 
+The recombination algorithms are safe with respect to soft radiations
+(\textit{infrared}) and collinear splittings. Their implementations are similar
+except for the definition of the \textit{distances} used during the merging
+procedure. 
+
+By default, reconstruction uses the CDF cone algorithm. Jets are stored if their
+transverse energy is higher than $20~\textrm{GeV}$~\citep{qr:ptcutjet}. 
  
 
 \subsubsection*{Energy flow}
 
-In jets, several particle can leave their energy into a given calorimetric cell, which broadens the jet energy resolution. However, the energy of charged particles associated to jets can be deduced from their reconstructed track, thus providing a way to identify some of the components of cells with multiple hits. When the \textit{energy flow} is switched on in \textit{Delphes}
-%\footnote{\texttt{[code]} Set \texttt{JET\_Eflow} to $1$ or $0$ in the detector card in order to switch on or off the energy flow for jet reconstruction.}
-, the energy of tracks pointing to calorimetric cells is subtracted and smeared separately, before running the chosen jet reconstruction algorithm. This option allows a better jet $E$ reconstruction~\citep{qr:energyflow}.
+In jets, several particle can leave their energy into a given calorimetric cell,
+which broadens the jet energy resolution. However, the energy of charged
+particles associated to jets can be deduced from their reconstructed track, thus
+providing a way to identify some of the components of cells with multiple hits.
+When the \textit{energy flow} is switched on in \textit{Delphes}, the energy of
+tracks pointing to calorimetric cells is subtracted and smeared separately,
+before running the chosen jet reconstruction algorithm. This option allows a
+better jet $E$ reconstruction~\citep{qr:energyflow}.
  
 \subsection{$b$-tagging}
 \label{btagging}
 
-A jet is tagged as $b$-jets if its direction lies in the acceptance of the tracker and if it is associated to a parent $b$-quark. By default, a $b$-tagging efficiency of $40\%$ is assumed if the jet has a parent $b$ quark. For $c$-jets and light jets (i.e.\ originating in $u$, $d$, $s$ quarks or in gluons), a fake $b$-tagging efficiency of $10 \%$ and $1 \%$ respectively is assumed~\citep{qr:btag}.
-%\footnote{\texttt{[code] }Corresponding to the \texttt{BTAG\_b}, \texttt{BTAG\_mistag\_c} and \texttt{BTAG\_mistag\_l} constants, for (respectively) the efficiency of tagging of a $b$-jet, the efficiency of mistagging a $c$-jet as a $b$-jet, and the efficiency of mistagging a light jet ($u$,$d$,$s$,$g$) as a $b$-jet.}.
-The (mis)tagging relies on the true parton identity of the most energetic parton within a cone around the $(\eta,\phi)$ region, with a radius equal to the one used to reconstruct the jet (default: $\Delta R$ of $0.7$). In current version of \textit{Delphes}, the displacement of secondary vertices is not simulated.
+A jet is tagged as $b$-jets if its direction lies in the acceptance of the
+tracker and if it is associated to a parent $b$-quark. By default, a $b$-tagging
+efficiency of $40\%$ is assumed if the jet has a parent $b$ quark. For $c$-jets
+and light jets (i.e.\ originating in $u$, $d$, $s$ quarks or in gluons), a fake
+$b$-tagging efficiency of $10 \%$ and $1 \%$ respectively is
+assumed~\citep{qr:btag}. The (mis)tagging relies on the identity of
+the most energetic parton within a cone around the jet axis, with a
+radius equal to the one used to reconstruct the jet (default: $\Delta R$ of
+$0.7$). In current version of \textit{Delphes}, the displacement of secondary
+vertices is not simulated.
 
 \subsection{\texorpdfstring{$\tau$}{\texttau} identification}
 
-Jets originating from $\tau$-decays are identified using a procedure consistent with the one applied in a full detector simulation~\citep{bib:cmsjetresolution}.
-The tagging relies on two properties of the $\tau$ lepton. First, $77\%$ of the $\tau$ hadronic decays contain only one charged hadron associated to a few neutrals (Tab.~\ref{tab:taudecay}). Secondly, the particles arisen from the $\tau$ lepton produce narrow jets in the calorimeter (this is defined as the jet \textit{collimation}). 
+Jets originating from $\tau$-decays are identified using a procedure consistent
+with the one applied in a full detector simulation~\citep{bib:cmsjetresolution}.
+The tagging relies on two properties of the $\tau$ lepton. First, $77\%$ of the
+$\tau$ hadronic decays contain only one charged hadron associated to a few
+neutrals (Tab.~\ref{tab:taudecay}). Secondly, the particles arisen from the
+$\tau$ lepton produce narrow jets in the calorimeter (this is defined as the jet
+\textit{collimation}). 
 
 
 \begin{table}[!h]
 \begin{center}
-\caption{ Branching ratios for $\tau^-$ lepton~\citep{bib:pdg}. $h^\pm$ and $h^0$ refer to charged and neutral hadrons, respectively. $n \geq 0$ and $m \geq 0$ are integers.
+\caption{ Branching ratios for $\tau^-$ lepton~\citep{bib:pdg}. $h^\pm$ and
+$h^0$ refer to charged and neutral hadrons, respectively. $n \geq 0$ and $m \geq
+0$ are integers.
 \vspace{0.5cm}  }
 \begin{tabular}[!h]{lll}
@@ -491,18 +576,4 @@
 \caption{Default values for parameters used in $\tau$-jet reconstruction algorithm. Electromagnetic collimation requirements involve the inner \textit{small} cone radius $R^\textrm{em}$, the minimum transverse energy for calorimetric cells $E_T^\textrm{cell}$ and the collimation factor $C_\tau$. Tracking isolation constrains the number of tracks with a significant transverse momentum $p_T^\textrm{tracks}$ in a cone of radius $R^\textrm{tracks}$.  Finally, the $\tau$-jet collection is purified by the application of a cut on the $p_T$ of $\tau$-jet candidates~\citep{qr:taujets}.
 \vspace{0.5cm}  }
-% \begin{tabular}[!h]{lll}
-% \hline
-% Parameter  & Card flag & Value\\\hline
-% \multicolumn{3}{l}{\textbf{Electromagnetic collimation}} \\
-% $R^\textrm{em}$     & \texttt{TAU\_energy\_scone } & $0.15$\\
-% min $E_{T}^\textrm{tower}$     & {\verb JET_M_seed }  & $1.0$~GeV\\
-% $C_{\tau}$         & \texttt{TAU\_energy\_frac} & $0.95$\\
-% \multicolumn{3}{l}{\textbf{Tracking isolation}} \\
-% $R^\textrm{tracks}$ & \texttt{TAU\_track\_scone} & $0.4$\\
-% min $p_T^\textrm{tracks}$      & \texttt{PTAU\_track\_pt } & $2$ GeV$/c$\\
-% \multicolumn{3}{l}{\textbf{$\tau$-jet candidate}} \\
-% $\min p_T$ & \texttt{TAUJET\_pt} & $10$ GeV$/c$\\
-% \hline
-% \end{tabular}
 \begin{tabular}[!h]{lll}
 \hline
@@ -525,7 +596,12 @@
 \subsubsection*{Electromagnetic collimation}
 
-To use the narrowness of the $\tau$-jet, the \textit{electromagnetic collimation} $C_{\tau}$ is defined as the sum of the energy of cells in a small cone of radius $R^\textrm{em}$ around the jet axis, divided by the energy of the reconstructed jet. 
-To be taken into account, a calorimeter cell should have a transverse energy $E_T^\textrm{cell}$ above a given threshold. 
-A large fraction of the jet energy is expected in this small cone. This fraction, or \textit{collimation factor}, is represented in Fig.~\ref{fig:tau2} for the default values (see Tab.~\ref{tab:tauRef}).
+To use the narrowness of the $\tau$-jet, the \textit{electromagnetic
+collimation} $C_{\tau}$ is defined as the sum of the energy of cells in a small
+cone of radius $R^\textrm{em}$ around the jet axis, divided by the energy of the
+reconstructed jet. To be taken into account, a calorimeter cell should have a
+transverse energy $E_T^\textrm{cell}$ above a given threshold. A large fraction
+of the jet energy is expected in this small cone. This fraction, or
+\textit{collimation factor}, is represented in Fig.~\ref{fig:tau2} for the
+default values (see Tab.~\ref{tab:tauRef}).
 
 \begin{figure}[!ht]
@@ -543,6 +619,10 @@
 \subsubsection*{Tracking isolation}
 
-The tracking isolation for the $\tau$ identification requires that the number of tracks associated to particles with significant transverse momenta is one and only one in a cone of radius $R^\textrm{tracks}$ ($3-$prong $\tau$-jets are dropped). 
-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}.
+The tracking isolation for the $\tau$ identification requires that the number
+of tracks associated to particles with significant transverse momenta is one and
+only one in a cone of radius $R^\textrm{tracks}$ ($3-$prong $\tau$-jets are
+dropped). 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}.
 
 
@@ -560,57 +640,64 @@
 
 \subsubsection*{Purity}
-Once both electromagnetic collimation and tracking isolation are applied, a threshold on the $p_T$ of the $\tau$-jet candidate is requested to purify the collection. This procedure selects $\tau$ leptons decaying hadronically with a typical efficiency of $66\%$. 
+Once both electromagnetic collimation and tracking isolation are applied, a
+threshold on the $p_T$ of the $\tau$-jet candidate is requested to purify the
+collection. This procedure selects $\tau$ leptons decaying hadronically with a
+typical efficiency of $66\%$. 
 
 \subsection{Missing transverse energy}
-In an ideal detector, momentum conservation imposes the transverse momentum of the observed final state $\overrightarrow{p_T}^\textrm{obs}$ to be equal to the $\overrightarrow{p_T}$ vector sum of the invisible particles, written $\overrightarrow{p_T}^\textrm{miss}$.
-\begin{equation}
-\overrightarrow{p_T} = \left(
-\begin{array}{c}
-p_x\\
-p_y\\
-\end{array}
-\right) 
-~ \textrm{and} ~
-\left\{
-\begin{array}{l}
- p_x^\textrm{miss} = - p_x^\textrm{obs} \\
- p_y^\textrm{miss} = - p_y^\textrm{obs} \\
-\end{array}
-\right.
-\end{equation}
-The \textit{true} missing transverse energy, i.e.\ at generator-level, is calculated as the opposite of the vector sum of the transverse momenta of all visible particles -- or equivalently, to the vector sum of invisible particle transverse momenta. 
-In a real experiment, calorimeters measure energy and not momentum. Any problem affecting the detector (dead channels, misalignment, noisy cells, cracks) worsens directly the measured missing transverse energy $\overrightarrow {E_T}^\textrm{miss}$. In \textit{Delphes}, \textsc{MET} is based on the calorimetric cells only. Muons and neutrinos are therefore not taken into account for its evaluation:
+In an ideal detector, momentum conservation imposes the transverse momentum of
+the observed final state $\overrightarrow{p_T}^\textrm{obs}$ to be equal and
+in opposite direction to the $\overrightarrow{p_T}$ vector sum of the
+invisible particles, written $\overrightarrow{p_T}^\textrm{miss}$.
+The \textit{true} missing transverse energy, i.e.\ at generator-level, is
+calculated as the opposite of the vector sum of the transverse momenta of all
+visible particles -- or equivalently, to the vector sum of invisible particle
+transverse momenta. 
+In a real experiment, calorimeters measure energy and not momentum. Any problem
+affecting the detector (dead channels, misalignment, noisy cells, cracks)
+worsens directly the measured missing transverse energy $\overrightarrow
+{E_T}^\textrm{miss}$. In \textit{Delphes}, \textsc{MET} is based on the
+calorimetric cells only. Muons and neutrinos are therefore not taken into
+account for its evaluation:
 \begin{equation}
 \overrightarrow{E_T}^\textrm{miss} = - \sum^\textrm{cells}_i \overrightarrow{E_T}(i)
 \end{equation}
-However, as muon candidates, tracks and calorimetric cells are available in the output file, the missing transverse energy can always be reprocessed a posteriori with more specialised algorithms.
+However, as muon candidates, tracks and calorimetric cells are available in the
+output file, the missing transverse energy can always be reprocessed a
+posteriori with more specialised algorithms.
 
 \section{Trigger emulation}
 
-% New physics in collider experiment are often characterised in phenomenology by low cross-section values, compared to the Standard Model (\textsc{SM}) processes. 
-%For instance at the \textsc{LHC} ($\sqrt{s}=14~\textrm{TeV}$), the cross-section of inclusive production of $b \bar b$ pairs is expected to be $10^7~\textrm{nb}$, or inclusive jets at $100~\textrm{nb}$ ($p_T > 200~\textrm{GeV}/c$), while Higgs boson cross-section within the \textsc{SM} can be as small as $2 \times 10^{-3}~\textrm{nb}$ ($pp \rightarrow WH$, $m_H=115~\textrm{GeV}/c^2$).
-
-%High statistics are required for data analyses, consequently imposing high luminosity, i.e.\ a high collision rate.
-% As only a tiny fraction of the observed events can be stored for subsequent \textit{offline} analyses, a very large data rejection factor should be applied directly as the events are produced.
-% This data selection is supposed to reject only well-known \textsc{SM} events\footnote{In real experiments, some bandwidth is allocated to minimum-bias and/or zero-bias (``random'') triggers that stores a small fraction of  random events without any selection criteria.}.
-% Dedicated algorithms of this \textit{online} selection, or \textit{trigger}, should be fast and very efficient for data rejection, in order to preserve the experiment output bandwidth. They must also be as inclusive as possible to avoid loosing interesting events.
-
-Most of the usual trigger algorithms select events containing leptons, jets, and \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 $p_T^e > 50~\textrm{GeV}/c$.
-
-A trigger emulation is included in \textit{Delphes}, using a fully parametrisable \textit{trigger table} \citep{qr:triggercard}. When enabled, this trigger is applied on analysis-object data.
-In a real experiment, the online selection is often divided into several steps (or \textit{levels}). 
-% This splits the overall reduction factor into a product of smaller factors, corresponding to the different trigger levels. 
-% This is related to the architecture of the experiment data acquisition chain, with limited electronic buffers requiring a quick decision for the first trigger level. 
-First-level triggers are fast and simple but based only on partial data as not all detector front-ends are readable within the decision latency. 
-Higher level triggers are more complex, of finer-but-not-final quality and based on full detector data. 
-
-Real triggers are thus intrinsically based on reconstructed data with a worse resolution than final analysis data. 
-On the contrary, same data are used in \textit{Delphes} for trigger emulation and for final analyses.
+Most of the usual trigger algorithms select events containing leptons, jets, and
+\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 $p_T^e >
+50~\textrm{GeV}/c$.
+
+A trigger emulation is included in \textit{Delphes}, using a fully
+parametrisable \textit{trigger table} \citep{qr:triggercard}. When enabled, this
+trigger is applied on analysis-object data. In a real experiment, the online
+selection is often divided into several steps (or \textit{levels}). 
+corresponding to the different trigger levels.
+First-level triggers are fast and simple but based only on partial data as not
+all detector front-ends are readable within the decision latency. 
+Higher level triggers are more complex, of finer-but-not-final quality and
+based on full detector data. 
+
+Real triggers are thus intrinsically based on reconstructed data with a worse
+resolution than final analysis information. On the contrary, the same
+information is used in \textit{Delphes} for the trigger emulation and for final
+analyses.
 
 \section{\label{sec:vfd}Very forward detector simulation}
 
-Most of the recent experiments in beam colliders have additional instrumentation along the beamline. These extend the $\eta$ coverage to higher values, for the detection of very forward final-state particles. In \textit{Delphes}, Zero Degree Calorimeters, roman pots and forward taggers have been implemented (Fig.~\ref{fig:fdets}), similarly to the plans for CMS and ATLAS collaborations~\citep{bib:cmsjetresolution, bib:ATLASresolution}.
+Most of the recent experiments in beam colliders have additional
+instrumentation along the beamline. These extend the $\eta$ coverage to higher
+values, for the detection of very forward final-state particles. In
+\textit{Delphes}, Zero Degree Calorimeters, roman pots and forward taggers have
+been implemented (Fig.~\ref{fig:fdets}), similarly as for CMS and
+ATLAS collaborations~\citep{bib:cmsjetresolution, bib:ATLASresolution}.
 
 \begin{figure}[!ht]
@@ -618,16 +705,25 @@
 %\includegraphics[width=\columnwidth]{fdets}
 \includegraphics[width=\columnwidth]{fig4}
-\caption{Default location of the very forward detectors, including \textsc{ZDC}, \textsc{RP220} and \textsc{FP420} in the \textsc{LHC} beamline.
-Incoming (beam 1, red) and outgoing (beam 2, black) beams on one side of the fifth interaction point (\textsc{IP5}, $s=0~\textrm{m}$ on the plot).
-The Zero Degree Calorimeter is located in perfect alignment with the beamline axis at the interaction point, at $140~\textrm{m}$, the beam paths are separated. The forward taggers are near-beam detectors located at $220~\textrm{m}$ and $420~\textrm{m}$. Beamline simulation with \textit{Hector}~\citep{bib:hector}. All very forward detectors are located symmetrically around the interaction point. }
+\caption{Default location of the very forward detectors, including
+\textsc{ZDC}, \textsc{RP220} and \textsc{FP420} in the \textsc{LHC} beamline.
+Incoming (beam 1, red) and outgoing (beam 2, black) beams on one side of the
+fifth interaction point (\textsc{IP5}, $s=0~\textrm{m}$ on the plot).
+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
+well separated. The forward taggers are near-beam detectors located at
+$220~\textrm{m}$ and $420~\textrm{m}$. Beamline simulation with
+\textit{Hector}~\citep{bib:hector}. All very forward detectors are located
+symmetrically around the interaction point. }
 \label{fig:fdets}
 \end{center}
 \end{figure}
 
-%\begin{table*}[t]  % the star (*) allows to arrange the table over the two columns
 \begin{table}[t]
 \begin{center}
-\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.
-% The tagger acceptance is fully determined by the distance in the transverse plane of the detector to the real beam position~\citep{bib:hector}. 
+\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.
 It is expressed in terms of the particle energy ($E$).
 All detectors are located on both sides of the interaction point.
@@ -635,5 +731,4 @@
 \begin{tabular}{llcl}
 \hline
-%Detector & Distance from \textsc{IP}& Acceptance & \\ \hline
 Detector & Distance & Acceptance & \\ \hline
 \textsc{ZDC}   & $\pm 140$ m & $|\eta|> 8.3$       & for $n$ and $\gamma$\\
@@ -649,44 +744,50 @@
 \subsection{Zero Degree Calorimeters}
 
-In direct sight of the interaction point, on both sides of the central detector, the Zero Degree Calorimeters (\textsc{ZDC}s) are located at zero angle, i.e.\ are aligned with the beamline axis at the interaction point. They are placed beyond the point where the paths of incoming and outgoing beams separate. These allow the measurement of stable neutral particles ($\gamma$ and $n$) coming from the interaction point, with large pseudorapidities (e.g.\ $|\eta_{\textrm{n,}\gamma}| > 8.3$ in \textsc{ATLAS} and \textsc{CMS}).
-
-The trajectory of the neutrals observed in the \textsc{ZDC}s is a straight line, while charged particles are deflected away from their acceptance window by the powerful magnets located in front of them. The fact that additional charged particles may enter the \textsc{ZDC} acceptance is neglected in the current versions of \textit{Delphes}.
+In direct sight of the interaction point, on both sides of the central
+detector, the Zero Degree Calorimeters (\textsc{ZDC}s) are located at zero
+angle, i.e.\ are aligned with the beamline axis at the interaction point. They
+are placed beyond the point where the paths of incoming and outgoing beams
+separate. These allow the measurement of stable neutral particles ($\gamma$ and
+$n$) coming from the interaction point, with large pseudorapidities (e.g.\
+$|\eta_{\textrm{n,}\gamma}| > 8.3$ in \textsc{ATLAS} and \textsc{CMS}).
+
+The trajectory of the neutrals observed in the \textsc{ZDC}s is a straight
+line, while charged particles are deflected away from their acceptance window by
+the powerful magnets located in front of them. The fact that additional charged
+particles may enter the \textsc{ZDC} acceptance is neglected in the current
+versions of \textit{Delphes}.
 
 The \textsc{ZDC}s have the ability to measure the time-of-flight of the particle.
-This corresponds to the delay $t$ after which the particle is observed in the detector, with respect to the bunch crossing reference time at the interaction point ($t_0$): 
+This corresponds to the delay $t$ after which the particle is observed in the
+detector, with respect to the bunch crossing reference time at the interaction
+point ($t_0$): 
 \begin{equation}
  t = t_0 + \frac{1}{v} \times \Big( \frac{s-z}{\cos \theta}\Big) \approx \frac{1}{c} \times (s-z),
 \end{equation}
-where $t_0$ is thus the true time coordinate of the vertex from which the particle originates, $v$ the particle velocity, $s$ is the \textsc{ZDC} distance to the interaction point, $z$ is the longitudinal coordinate of the vertex, $\theta$ is the particle emission angle. It is assumed that the neutral particle observed in the \textsc{ZDC} is highly relativistic and very forward.
-% 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 $1 - \cos \theta < 10^{-4}$.
-% The formula then reduces to
-% \begin{equation}
-%  t = \frac{1}{c} \times (s-z).
-% \end{equation}
-% For example, a photon takes $0.47~\mu\textrm{s}$ to reach a \textsc{ZDC} located at $s=140~\textrm{m}$, neglecting $z$ and $\theta$. 
-For the time-of-flight measurement, a Gaussian smearing can be applied according to the detector resolution (Tab.~\ref{tab:defResolZdc})~\citep{qr:resolutionterms}. 
-%In the current version of \textit{Delphes}, only neutrons, antineutrons and photons are assumed to be able to reach the \textsc{ZDC}s, all other particles being neglected.
-
-The \textsc{ZDC}s are composed of an electromagnetic and a hadronic sections, for the measurement of photons and neutrons, respectively. The energy of the observed neutral is smeared according to Eq.~\ref{eq:caloresolution} and the corresponding section resolutions (Tab.~\ref{tab:defResolZdc}). The \textsc{ZDC} hits do not enter in the calorimeter cell list used for reconstruction of jets and missing transverse energy.
+where $t_0$ is thus the true time coordinate of the vertex from which the
+particle originates, $v$ the particle velocity, $s$ is the \textsc{ZDC} distance
+to the interaction point, $z$ is the longitudinal coordinate of the vertex,
+$\theta$ is the particle emission angle. It is assumed that the neutral particle
+observed in the \textsc{ZDC} is highly relativistic and very forward.
+For the time-of-flight measurement, a Gaussian smearing can be applied according
+to the detector resolution
+(Tab.~\ref{tab:defResolZdc})~\citep{qr:resolutionterms}. 
+
+
+The \textsc{ZDC}s are composed of an electromagnetic and a hadronic sections,
+for the measurement of photons and neutrons, respectively. The energy of the
+observed neutral is smeared according to Eq.~\ref{eq:caloresolution} and the
+corresponding section resolutions (Tab.~\ref{tab:defResolZdc}). The \textsc{ZDC}
+hits do not enter in the calorimeter cell list used for reconstruction of jets
+and missing transverse energy.
 
 \begin{table}[!h]
 \begin{center}
-\caption{Default values for the resolution of the zero degree calorimeters. Resolution on energy measurement is parametrised by the \textit{stochastic} ($S$), \textit{noise} ($N$) and \textit{constant} ($C$) terms (Eq.~\ref{eq:caloresolution})~\citep{qr:resolutionterms}. The time-of-flight is smeared according to a Gaussian function.
+\caption{Default values for the resolution of the zero degree calorimeters.
+Resolution on energy measurement is parametrised by the \textit{stochastic}
+($S$), \textit{noise} ($N$) and \textit{constant} ($C$) terms
+(Eq.~\ref{eq:caloresolution})~\citep{qr:resolutionterms}. The time-of-flight is
+smeared according to a Gaussian function.
 \vspace{0.5cm}}
-% \begin{tabular}[!h]{lllc}
-% \hline
-% \multicolumn{2}{c}{Resolution Term}   & Card flag & Value\\\hline
-%  \multicolumn{4}{l}{\textsc{ZDC}, electromagnetic part} \\
-%         & $S$ (GeV$^{1/2}$)& \texttt{ELG\_Szdc}  & $0.7$ \\
-%         & $N$ (GeV)& \texttt{ELG\_Nzdc}  & $0.0$ \\
-%         & $C$ & \texttt{ELG\_Czdc}  & $0.08$ \\
-%  \multicolumn{4}{l}{\textsc{ZDC}, hadronic part} \\
-%         & $S$ (GeV$^{1/2}$)& \texttt{HAD\_Szdc}   & $1.38$\\
-%         & $N$ (GeV)& \texttt{HAD\_Nzdc}   & $0$ \\
-%         & $C$ & \texttt{HAD\_Czdc}   & $0.13$\\
-%  \multicolumn{4}{l}{\textsc{ZDC}, timing resolution} \\
-%         & $\sigma_t$ (s) & \texttt{ZDC\_T\_resolution} & $0$ \\
-% \hline
-% \end{tabular}
 \begin{tabular}[!h]{llcc}
 \hline
@@ -703,24 +804,51 @@
 \end{table}
 
-% \subsubsection*{Forward neutrals}
-
-The reconstructed ZDC hits correspond to neutral particles with a lifetime long enough to reach these detectors (default: $c \tau \geq 140~\textrm{m}$) and very large pseudorapidities (default: $|\eta|>8.3$). 
-%In current versions of \textit{Delphes}, only photons and neutrons are considered. 
-Photons are identified thanks to the electromagnetic section of the calorimeter, and if their energy overpasses a given threshold (def. $20$~GeV). Similarly, neutrons are reconstructed according to the resolution of the hadronic section, if their energy exceeds a threshold (def. $50$~GeV)~\citep{qr:fwdneutrals}.
-%\footnote{\texttt{[code]} These thresholds are defined by the \texttt{ZDC\_gamma\_E} and \texttt{ZDC\_n\_E} variables in the detector card.} (def. $50$~GeV).
+The reconstructed ZDC hits correspond to neutral particles with a lifetime long
+enough to reach these detectors (default: $c \tau \geq 140~\textrm{m}$) and very
+large pseudorapidities (default: $|\eta|>8.3$). 
+Photons and neutrons are identified if their energy overpasses a given threshold
+(def. $E_\gamma \leq 20$~GeV and $E_n \leq 50$~GeV)~\citep{qr:fwdneutrals}.
+
 
 
 \subsection{Forward taggers}
 
-Forward taggers (called here \textsc{RP220}, for ``roman pots at $220~\textrm{m}$'' and \textsc{FP420} for ``forward proton taggers at $420~\textrm{m}$'', as at the \textsc{LHC}) are meant for the measurement of particles following very closely the beam path. Such devices, also used at \textsc{HERA} and Tevatron, are located very far away from the interaction point (further than $150$~m in the \textsc{LHC} case).
-
-To be able to reach these detectors, particles must have a charge identical to the beam particles, and a momentum very close to the nominal value of the beam. These taggers are near-beam detectors located a few millimetres from the true beam trajectory and this distance defines their acceptance (Tab.~\ref{tab:fdetacceptance}). 
-For instance, roman pots at $220~\textrm{m}$ from the  \textsc{IP} and $2~\textrm{mm}$ from the beam will detect all forward protons with an energy between $120$ and $900~\textrm{GeV}$~\citep{bib:hector}.
-In practice, in the \textsc{LHC}, only positively charged muons ($\mu^+$) and protons can reach the forward taggers as other particles with a single positive charge coming from the interaction points will decay before their possible tagging. In \textit{Delphes}, extra hits coming from the beam-gas events or secondary particles hitting the beampipe in front of the detectors are not taken into account.
-
-While neutral particles propagate along a straight line to the \textsc{ZDC}, a dedicated simulation of the transport of charged particles is needed for \textsc{RP220} and \textsc{FP420}. This fast simulation uses the \textit{Hector} software~\citep{bib:hector}, which includes the chromaticity effects and the geometrical aperture of the beamline elements of any arbitrary collider.
-
-Forward taggers are able to measure the hit positions ($x,y$) and angles ($\theta_x,\theta_y$) in the transverse plane at the location of the detector ($s$ meters away from the \textsc{IP}), as well as the time-of-flight\footnote{It is worth noting that for both \textsc{CMS} and \textsc{ATLAS} experiments, the taggers located at $220$~m are not able to measure the time-of-flight, contrary to \textsc{FP420} detectors.} ($t$). Out of these the particle energy ($E$) and the momentum transfer it underwent during the interaction ($q^2$) can be reconstructed at the analysis level (it is not implemented in the current versions of \textit{Delphes}. The time-of-flight measurement can be smeared with a Gaussian distribution (default value
-%\footnote{\texttt{[code] } The resolution is defined by the \texttt{RP220\_T\_resolution} and \texttt{RP420\_T\_resolution} parameters in the detector card.} 
+Forward taggers (called here \textsc{RP220}, for ``roman pots at
+$220~\textrm{m}$'' and \textsc{FP420} for ``forward proton taggers at
+$420~\textrm{m}$'', as at the \textsc{LHC}) are meant for the measurement of
+particles following very closely the beam path. Such devices, also used at
+\textsc{HERA} and Tevatron, are located very far away from the interaction point
+(further than $150$~m in the \textsc{LHC} case).
+
+To be able to reach these detectors, particles must have a charge identical to
+the beam particles, and a momentum very close to the nominal value of the beam.
+These taggers are near-beam detectors located a few millimetres from the true
+beam trajectory and this distance defines their acceptance
+(Tab.~\ref{tab:fdetacceptance}). For instance, roman pots at $220~\textrm{m}$
+from the  \textsc{IP} and $2~\textrm{mm}$ from the beam will detect all forward
+protons with an energy between $120$ and $900~\textrm{GeV}$~\citep{bib:hector}.
+In practice, in the \textsc{LHC}, only positively charged muons ($\mu^+$) and
+protons can reach the forward taggers as other particles with a single positive
+charge coming from the interaction points will decay before their possible
+tagging. In \textit{Delphes}, extra hits coming from the beam-gas events or
+secondary particles hitting the beampipe in front of the detectors are not taken
+into account.
+
+While neutral particles propagate along a straight line to the \textsc{ZDC}, a
+dedicated simulation of the transport of charged particles is needed for
+\textsc{RP220} and \textsc{FP420}. This fast simulation uses the \textit{Hector}
+software~\citep{bib:hector}, which includes the chromaticity effects and the
+geometrical aperture of the beamline elements of any arbitrary collider.
+
+Forward taggers are able to measure the hit positions ($x,y$) and angles
+($\theta_x,\theta_y$) in the transverse plane at the location of the detector
+($s$ meters away from the \textsc{IP}), as well as the
+time-of-flight\footnote{It is worth noting that for both \textsc{CMS} and
+\textsc{ATLAS} experiments, the taggers located at $220$~m are not able to
+measure the time-of-flight, contrary to \textsc{FP420} detectors.} ($t$). Out of
+these the particle energy ($E$) and the momentum transfer it underwent during
+the interaction ($q^2$) can be reconstructed at the analysis level (it is not
+implemented in the current versions of \textit{Delphes}. The time-of-flight
+measurement can be smeared with a Gaussian distribution (default value
 $\sigma_t = 0~\textrm{s}$)~\citep{qr:protontaggers}.
 
@@ -730,31 +858,57 @@
 
 \textit{Delphes} performs a fast simulation of a collider experiment.
-Its performances in terms of computing time and data size are directly proportional to the number of simulated events and on the considered physics process. As an example, $10,000$ $pp \rightarrow t \bar t X$ events are processed in $110~\textrm{s}$ on a regular laptop and use less than $250~\textrm{MB}$ of disk space.
-The quality and validity of the output are assessed by comparing the resolutions on the reconstructed data to the expectations of both \textsc{CMS}~\citep{bib:cmsjetresolution} and \textsc{ATLAS}~\citep{bib:ATLASresolution} detectors.
-
-Electrons and muons are by construction equal to the experiment designs, as the Gaussian smearing of their kinematics properties is defined according to the detector specifications.
-Similarly, the $b$-tagging efficiency (for real $b$-jets) and misidentification rates (for fake $b$-jets) are taken directly from the expected values of the experiment. 
-Unlike these simple objects, jets and missing transverse energy should be carefully cross-checked.
+Its performances in terms of computing time and data size are directly
+proportional to the number of simulated events and on the considered physics
+process. As an example, $10,000$ $pp \rightarrow t \bar t X$ events are
+processed in $110~\textrm{s}$ on a regular laptop and use less than
+$250~\textrm{MB}$ of disk space.
+The quality and validity of the output are assessed by comparing the
+resolutions on the reconstructed data to the expectations of both
+\textsc{CMS}~\citep{bib:cmsjetresolution} and
+\textsc{ATLAS}~\citep{bib:ATLASresolution} detectors.
+
+Electrons and muons are by construction equal to the experiment designs, as the
+Gaussian smearing of their kinematics properties is defined according to the
+detector specifications. Similarly, the $b$-tagging efficiency (for real
+$b$-jets) and misidentification rates (for fake $b$-jets) are taken directly
+from the expected values of the experiment. Unlike these simple objects, jets
+and missing transverse energy should be carefully cross-checked.
 
 \subsection{Jet resolution}
  
-The majority of interesting processes at the \textsc{LHC} contain jets in the final state. The jet resolution obtained using \textit{Delphes} is therefore a crucial point for its validation, both for \textsc{CMS}- and \textsc{ATLAS}-like detectors.
-This validation is based on $pp \rightarrow gg$ events produced with MadGraph/MadEvent and hadronised using \textit{Pythia}~\citep{bib:mgme,bib:pythia}.
-
-For a \textsc{CMS}-like detector, a similar procedure as the one explained in published results is applied here.
-The events were arranged in $14$ bins of gluon transverse momentum $\hat{p}_T$. In each $\hat{p}_T$ bin, every jet in \textit{Delphes} is matched to the closest jet of generator-level particles, using the spatial separation between the two jet axes
+The majority of interesting processes at the \textsc{LHC} contain jets in the
+final state. The jet resolution obtained using \textit{Delphes} is therefore a
+crucial point for its validation, both for \textsc{CMS}- and \textsc{ATLAS}-like
+detectors. This validation is based on $pp \rightarrow gg$ events produced with
+MadGraph/MadEvent and hadronised
+using \textit{Pythia}~\citep{bib:mgme,bib:pythia}.
+
+For a \textsc{CMS}-like detector, a similar procedure as the one explained in
+published results is applied here. The events were arranged in $14$ bins of
+gluon transverse momentum $\hat{p}_T$. In each $\hat{p}_T$ bin, every jet in
+\textit{Delphes} is matched to the closest jet of generator-level particles,
+using the spatial separation between the two jet axes
 \begin{equation}
-\Delta R = \sqrt{ \big(\eta^\textrm{rec} - \eta^\textrm{MC} \big)^2 +  \big(\phi^\textrm{rec} - \phi^\textrm{MC} \big)^2}<0.25. 
+\Delta R = \sqrt{ \big(\eta^\textrm{rec} - \eta^\textrm{MC} \big)^2 + 
+\big(\phi^\textrm{rec} - \phi^\textrm{MC} \big)^2}<0.25. 
 \end{equation}
-The jets made of generator-level particles, here referred as \textit{MC jets}, are obtained by applying the algorithm to all particles considered as stable after hadronisation (i.e.\ including muons).
-Jets produced by \textit{Delphes} and satisfying the matching criterion are called hereafter \textit{reconstructed jets}.
-All jets are computed with the clustering algorithm (JetCLU) with a cone radius $R$ of $0.7$.
-
-The ratio of the transverse energies of every reconstructed jet $E_T^\textrm{rec}$ to its corresponding \textsc{MC} jet $E_T^\textrm{MC}$ is calculated in each $\hat{p}_T$ bin.
-The $E_T^\textrm{rec}/E_T^\textrm{MC}$ histogram is fitted with a Gaussian distribution in the interval \mbox{$\pm 2$~\textsc{RMS}} centred around the mean value.
-The resolution in each $\hat{p}_T$ bin is obtained by the fit mean $\langle x \rangle$ and variance $\sigma^2(x)$:
+The jets made of generator-level particles, here referred as \textit{MC jets},
+are obtained by applying the algorithm to all particles considered as stable
+after hadronisation (i.e.\ including muons). Jets produced by \textit{Delphes}
+and satisfying the matching criterion are called hereafter \textit{reconstructed
+jets}. All jets are computed with the clustering algorithm (JetCLU) with a cone
+radius $R$ of $0.7$.
+
+The ratio of the transverse energies of every reconstructed jet
+$E_T^\textrm{rec}$ to its corresponding \textsc{MC} jet $E_T^\textrm{MC}$ is
+calculated in each $\hat{p}_T$ bin. The $E_T^\textrm{rec}/E_T^\textrm{MC}$
+histogram is fitted with a Gaussian distribution in the interval \mbox{$\pm
+2$~\textsc{RMS}} centred around the mean value. The resolution in each
+$\hat{p}_T$ bin is obtained by the fit mean $\langle x \rangle$ and variance
+$\sigma^2(x)$:
 \begin{equation}
-%\frac{\sigma(R_{jet})}{\langle R_{jet} \rangle }=
-\frac{\sigma \Big (\frac{E_T^\textrm{rec}}{E_T^\textrm{MC}} \Big)_\textrm{fit}}{ \Big \langle \frac{E_T^\textrm{rec}}{E_T^\textrm{MC}} \Big \rangle_\textrm{fit}}~
+\frac{\sigma \Big (\frac{E_T^\textrm{rec}}{E_T^\textrm{MC}} \Big)_\textrm{fit}}{
+\Big \langle \frac{E_T^\textrm{rec}}{E_T^\textrm{MC}} \Big
+\rangle_\textrm{fit}}~
 \Big( \hat{p}_T(i) \Big)\textrm{, for all }i.
 \end{equation}
