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Timestamp:
Jul 13, 2010, 11:32:13 AM (14 years ago)
Author:
Xavier Rouby
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revised version

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trunk/paper/CommPhysComp
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  • trunk/paper/CommPhysComp/notes.tex

    r565 r569  
    144144
    145145
    146 \textit{Delphes} includes the most crucial experimental features, such as
     146\textit{Delphes} includes important experimental features, such as
    147147(Fig.~\ref{fig:FlowChart}):
    148148\begin{enumerate}
     
    164164The kinematics variables of the final-state particles are then smeared
    165165according to the tunable subdetector resolutions.
    166 Tracks are reconstructed in a simulated solenoidal magnetic field and
     166Tracks are identified in a simulated solenoidal magnetic field and
    167167calorimetric cells sample the energy deposits. Based on these low-level objects,
    168168dedicated algorithms are applied for particle identification, isolation and
     
    183183``parton-level" analysis, it has some limitations. Detector geometry is
    184184idealised, being uniform, symmetric around the beam axis, and having no cracks
    185 nor dead material. Secondary interactions, multiple scatterings, photon
    186 conversion and bremsstrahlung are also neglected.
     185nor dead material. The propagated particles do not suffer secondary interactions nor multiple scatterings that would affect their integrity or path throughout the detector. Photon conversion and bremsstrahlung due to the magnetic field are also neglected.
    187186
    188187Several common datafile formats can be used as input in \textit{Delphes}
     
    210209conditions by modifying basic detector parameters, including calorimeter and
    211210tracking coverage and resolution, thresholds or jet algorithm parameters.
    212 Even if \textit{Delphes} has been developped for the simulation of
     211Even if \textit{Delphes} has been developed for the simulation of
    213212general-purpose detectors at the \textsc{LHC} (namely, \textsc{CMS} and
    214 \textsc{ATLAS}), this input parameter file interfaces a flexible parametrisation
     213\textsc{ATLAS}, with references~\citep{bib:cmsjetresolution} and~\citep{bib:ATLASresolution} throughout this document), this input parameter file interfaces a flexible parametrisation
    215214for other cases, e.g.\ at future linear colliders~\citep{qr:datacards}.
    216215The geometrical coverage of the various subsystems used in the default
     
    266265By default, a track is assumed to be reconstructed with $90\%$ probability if
    267266its transverse momentum $p_T$ is higher than $0.9~\textrm{GeV}/c$ and if its
    268 pseudorapidity $|\eta| \leq 2.5$~\citep{qr:tracks}. This reconstruction efficiency is assumed to be uniform and independent of the particle type. No smearing is currently applied on track parameters. For each track, the positions at vertex $(\eta,\phi)$ and at the entry point in the calorimeter layers
     267pseudorapidity $|\eta| \leq 2.5$~\citep{qr:tracks}. This reconstruction efficiency is assumed to be uniform and independent of the particle type.
     268The momentum of tracks undergoes an intrinsic smearing, corresponding to the experiment capabilities for given particles. No further smearing is currently applied on track parameters. For each track, the positions at vertex $(\eta,\phi)$ and at the entry point in the calorimeter layers
    269269$(\eta,\phi)_{calo}$ are available while the helix parameters of tracks, especially the impact parameters are not.
    270270
     
    277277characteristics are not identical in every direction, with typically finer
    278278resolution and granularity in the central
    279 regions~\citep{bib:cmsjetresolution,bib:ATLASresolution}. It is thus very
     279regions. %~\citep{bib:cmsjetresolution,bib:ATLASresolution}.
     280It is thus very
    280281important to compute the exact coordinates of the entry point of the particles
    281282into the calorimeters, in taking the magnetic field effect into account.
     
    293294\begin{center}
    294295\includegraphics[width=\columnwidth]{fig3}
    295 \caption{Default segmentation of the calorimeters in the $(\eta,\phi)$ plane. Only the central detectors (\textsc{ECAL}, \textsc{HCAL}) and \textsc{FCAL} are considered. $\phi$ angles are expressed in radians.}
     296\caption{Default segmentation of the calorimeters in the $(\eta,\phi)$ plane. Only the central detectors (\textsc{ECAL}, \textsc{HCAL}) and \textsc{FCAL} are considered. $\phi$ angles are expressed in radians (see Sec.~\ref{sec:config}).}
    296297\label{fig:calosegmentation}
    297298\end{center}
     
    337338
    338339
    339 Electrons and photons are assumed to leave their energy in the electromagnetic
     340To simplify the simulation, electrons and photons are assumed to leave their energy in the electromagnetic
    340341parts of the calorimeters (\textsc{ECAL} and \textsc{FCAL}, e.m.), while charged
    341342and neutral final-state hadrons are assumed to leave their entire energy
     
    345346generators although they may decay before reaching the calorimeters. The energy
    346347smearing of such particles is therefore performed using the expected fraction of
    347 the energy, determined according to their decay products, that would be
    348 deposited into the \textsc{ECAL} ($E_{\textsc{ECAL}}$) and into the
    349 \textsc{HCAL} ($E_{\textsc{HCAL}}$). The positions of these deposits are identical to the one the mother particle would have hit.
    350   Defining $F$ as the fraction of the energy
    351 leading to a \textsc{HCAL} deposit, the two energy values are given by
    352 \begin{equation}
    353 \left\{
    354 \begin{array}{l}
    355 E_{\textsc{HCAL}} = E \times F \\
    356 E_{\textsc{ECAL}} = E \times (1-F) \\
    357 \end{array}
    358 \right.
    359 \end{equation}
    360 where $0 \leq F \leq 1$. The resulting calorimetry energy measurement given
     348the energy ($0 \leq F \leq 1$), determined according to their decay products, that would be
     349deposited into the \textsc{ECAL} ($E_{\textsc{ECAL}} = (1-F)\times E$) and into the
     350\textsc{HCAL} ($E_{\textsc{HCAL}} = F \times E$).
     351%The positions of these deposits are identical to the one the mother particle would have hit.
     352The position of these deposits corresponds to the calorimeter entry point of the mother particle.
     353%  Defining $F$ as the fraction of the energy
     354%leading to a \textsc{HCAL} deposit, the two energy values are given by
     355%\begin{equation}
     356%\left\{
     357%\begin{array}{l}
     358%E_{\textsc{HCAL}} = E \times F \\
     359%E_{\textsc{ECAL}} = E \times (1-F) \\
     360%\end{array}
     361%\right.
     362%\end{equation}
     363%where $0 \leq F \leq 1$.
     364The resulting calorimetry energy measurement given
    361365after the application of the smearing is then $E = E_{\textsc{HCAL}} +
    362366E_{\textsc{ECAL}}$. For $K_S^0$ and $\Lambda$ hadrons, the energy fraction $F$ is assumed to be $0.7$~\citep{qr:emhadratios}.\\
     
    396400The electron, muon and photon collections contains only the true final-state
    397401particles identified via the generator-data. In addition, these particles must
    398 pass fiducial cuts taking into account the magnetic field effects and have a
     402pass fiducial cuts taking into account the magnetic field effects, have a
    399403transverse momentum above some threshold (default: $p_T > 10~\textrm{GeV}/c$). Consequently, no fake candidates enter these collections. As effects like bremsstrahlung are not taken into account along the lepton propagation in the tracker, no clustering is
    400 needed for the electron reconstruction in \textit{Delphes}.
     404needed for the electron reconstruction in \textit{Delphes}. Moreover, charged leptons are added in their respective collections if their associated track is available.
    401405
    402406%In your electron simulation you take only the energy from the electron itself, not from any physics bremsstrahlung that is often collinear with the electron (I mean the real emission bremststrahlung directly from the Z->ee decay, not from the magnetic field in the ID). This leads in Z->ee events to a visible distortion of the line shape. I am aware that there is no easy solution to this problem and just adding all photons in the same cell leads to bias for others reasons. However, the reader should be warned that the Z peak will be slightly shifted due to the missing bremsstrahlungs energy.
     
    406410Real electron ($e^\pm$) and photon candidates are identified if they fall into the acceptance of the tracking system and have a
    407411transverse momentum above some threshold (default: $p_T > 10~\textrm{GeV}/c$).
    408 \textit{Delphes} assumes a perfect
    409 algorithm for clustering and Brehmstrahlung recovery. Electron energy is smeared
    410 according to the resolution of the calorimetric cell where it points to, but
     412\textit{Delphes} assumes a perfect algorithm for clustering and for recovery of detector-induced Brehmstrahlung.
     413Electron energy is smeared according to the resolution of the calorimetric cell where it points to, but
    411414independently from any other deposited energy in this cell.
    412415Electrons and photons may create a candidate in the jet collection. The $(\eta,
    413 \phi)$ position at vertex corresponds to corresponding track vertex.
     416\phi)$ position at vertex comes from their corresponding track vertex.
     417As there is no associated track to photons, their reconstructed kinematics is less good than for electrons. Consequently, the mass resolution of di-photon resonances is affected.
     418Similarly to full simulations, physics Brehmstrahlung from vertex is not taken into account in the electron reconstruction in \textit{Delphes}. Consequently, resonances like $Z\rightarrow e^+ e^-$ may have a bias in their reconstructed peak.
     419
    414420
    415421\subsubsection*{Muons}
     
    461467available~\citep{bib:FASTJET,qr:jetalgo}: {\it CDF Jet Clusters}~\citep{bib:jetclu}, {\it CDF MidPoint}~\citep{bib:midpoint}, {\it Seedless Infrared Safe Cone}~\citep{bib:SIScone}, {\it Longitudinally invariant $k_t$ jet}~\citep{bib:ktjet}, {\it Cambridge/Aachen jet}~\citep{bib:aachen} and {\it Anti $k_t$ jet}~\citep{bib:antikt}. For all of them, the calorimetric
    462468cells are used as inputs. Jet algorithms differ in their sensitivity to soft
    463 particles or collinear splittings, and in their computing speed performances. By default, reconstruction uses the CDF cone algorithm. Jets are stored if their transverse energy is higher than $20~\textrm{GeV}$~\citep{qr:ptcutjet}.
     469particles or collinear splittings, and in their computing speed performances. By default, reconstruction uses the midpoint algorithm. Jets are stored if their transverse energy is higher than $20~\textrm{GeV}$~\citep{qr:ptcutjet}.
     470By construction, the jet energy scale is close to reality and should not be corrected. However, no corrections are applied if particles do not enter in the constituent list for the jet algorithm. This has an impact on the mass reconstruction of fully hadronic objects like $t$ quark or $W$ boson.
    464471 
    465472
     
    470477particles associated to jets can be deduced from their associated track, thus
    471478providing a way to identify some of the components of cells with multiple hits.
    472 When the \textit{energy flow} is switched on in \textit{Delphes}, the energy of
    473 tracks pointing to calorimetric cells is subtracted and smeared separately,
    474 before running the chosen jet reconstruction algorithm. This option allows a
     479When using \textit{energy flow} in \textit{Delphes}, the chosen jet algorithm is applied on the smeared energies of both the tracks and the modified calorimetric cells. To avoid double-counting, the energy in the calorimeter cells has been corrected by subtracting the true track energy from the true cell energy, before their smearing. This option allows a
    475480better jet energy reconstruction~\citep{qr:energyflow}.
    476481 
     
    494499
    495500Jets originating from $\tau$-decays are identified using a procedure consistent
    496 with the one applied in a full detector reconstruction~\citep{bib:cmsjetresolution}.
     501with the one applied in a full detector reconstruction. %~\citep{bib:cmsjetresolution}.
    497502The tagging relies on two properties of the $\tau$ lepton. First, $77\%$ of the
    498503$\tau$ hadronic decays contain only one charged hadron in combination with a few
     
    504509\begin{center}
    505510\includegraphics[width=0.80\columnwidth]{fig4}
    506 \caption{Illustration of the identification of $\tau$-jets ($1-$prong). The jet cone is narrow and contains only one track. The small cone serves to apply the \textit{electromagnetic collimation}, while the broader cone is used to reconstruct the jet originating from the $\tau$-decay.}
     511\caption{Illustration of the identification of $\tau$-jets ($1-$prong). The jet cone is narrow and contains only one track. The small cone ($R^{em}$) serves to apply the \textit{electromagnetic collimation}, while the broader ($R^{tracks}$) cone is used to apply the \textit{tracking isolation}.}
    507512\label{h_WW_ss_cut1}
    508513\end{center}
     
    579584threshold on the $p_T$ of the $\tau$-jet candidate is requested to purify the
    580585collection. This procedure selects $\tau$ leptons decaying hadronically with a
    581 typical efficiency of $66\%$.
     586typical efficiency of $66\%$ relative to all hadronic $\tau$ decays.
    582587
    583588\subsection{Missing transverse energy}
     
    623628forward final-state particles. In \textit{Delphes}, Zero Degree Calorimeters,
    624629roman pots and forward taggers have been implemented (Fig.~\ref{fig:fdets}),
    625 similarly as for CMS and ATLAS collaborations~\citep{bib:cmsjetresolution,
    626 bib:ATLASresolution}.
     630similarly as for CMS and ATLAS collaborations. %~\citep{bib:cmsjetresolution,bib:ATLASresolution}.
    627631
    628632\begin{figure}[!ht]
     
    782786proportional to the number of simulated events and on the considered physics
    783787process. As an example, $10,000$ $pp \rightarrow t \bar t X$ events are
    784 processed in $110~\textrm{s}$ on a regular laptop and use less than
    785 $250~\textrm{MB}$ of disk space.
     788processed in $110~\textrm{s}$ on a regular laptop\footnote{Performances obtained on an Intel(r) Pentium M processor ($1.73$ GHz), $1$ GB RAM, Chipset $915$GM. This processor scores $450$ on CpuMark benchmark from PassMark 2010 (c)~\citep{bib:cpumark}. In case of large amount of events, the duration of read/write operations on hard disk is sensible (about 6\% of the time for the $4400$ rpm hard disk of the precited computer) and might improve with fast storing devices.} and use less than $250~\textrm{MB}$ of disk space.
    786789The quality and validity of the output are assessed by comparing the
    787790resolutions on the reconstructed data to the expectations of both
    788 \textsc{CMS}~\citep{bib:cmsjetresolution} and
    789 \textsc{ATLAS}~\citep{bib:ATLASresolution} detectors.
     791\textsc{CMS} and \textsc{ATLAS} detectors.
    790792
    791793Electrons and muons resolutions in \textit{Delphes} match by construction the
     
    797799
    798800\subsection{Jet resolution}
     801\label{sec:jetresol}
    799802 
    800803The majority of interesting processes at the \textsc{LHC} contain jets in the
     
    844847cone radius of $0.7$ and no energy flow correction. The maximum separation between the reconstructed and
    845848\textsc{MC}-jets is $\Delta R= 0.25$. Dotted line is the fit result for
    846 comparison to the \textsc{CMS} resolution~\citep{bib:cmsjetresolution}, in blue.
     849comparison to the \textsc{CMS} resolution, in blue.
    847850The $pp \rightarrow gg$ dijet events have been generated with MadGraph/MadEvent
    848851and hadronised with \textit{Pythia}.}
     
    860863where $a$, $b$ and $c$ are the fit parameters.
    861864It is then compared to the resolution published by the \textsc{CMS}
    862 collaboration~\citep{bib:cmsjetresolution}. The resolution curves from
    863 \textit{Delphes} and \textsc{CMS} are in good agreement.
     865collaboration. The resolution curves from
     866\textit{Delphes} and \textsc{CMS} are in good agreement: $3.1~\%$ at $E_T^\textrm{MC}=50~\textrm{GeV}$ and $4.2~\%$ at $500~\textrm{GeV}$.
    864867
    865868Similarly, the jet resolution is evaluated for an \textsc{ATLAS}-like detector.
     
    877880obtained with \textit{Delphes}, the result of the fit with
    878881Equation~\ref{eq:fitresolution} and the corresponding curve provided by the
    879 \textsc{ATLAS} collaboration~\citep{bib:ATLASresolution}.
     882\textsc{ATLAS} collaboration: $2.5~\%$ at $E^\textrm{MC}=50~\textrm{GeV}$ and $4.7\%$ at $500~\textrm{GeV}$.
    880883
    881884\begin{figure}[!ht]
     
    889892\textsc{MC}- and reconstructed jets is $\Delta R=0.2$. Only central jets are
    890893considered ($|\eta|<0.5$). Dotted line is the fit result for comparison to the
    891 \textsc{ATLAS} resolution~\citep{bib:ATLASresolution}, in blue. The $pp
     894\textsc{ATLAS} resolution, in blue. The $pp
    892895\rightarrow gg$ di-jet events have been generated with MadGraph/MadEvent and
    893896hadronised with \textit{Pythia}.}
     
    944947events is $\sigma_x = (0.6-0.7) ~ \sqrt{E_T} ~ \mathrm{GeV}^{1/2}$ with no
    945948pile-up (i.e. extra simultaneous $pp$ collision occurring at high-luminosity in
    946 the same bunch crossing)~\citep{bib:cmsjetresolution}, which compares very well
     949the same bunch crossing), which compares very well
    947950with the $\alpha = 0.63$ obtained with \textit{Delphes}. Similarly, for an
    948951\textsc{ATLAS}-like detector, a value of $0.53$ is obtained by \textit{Delphes}
    949952for the $\alpha$ parameter, while the experiment expects it in the range $[0.53~
    950 ;~0.57]$~\citep{bib:ATLASresolution}.
     953;~0.57]$.
    951954
    952955\subsection{\texorpdfstring{$\tau$}{\texttau}-jet efficiency}
     
    963966quoted for comparison. The level of agreement is satisfactory provided possible
    964967differences due to the event generation chain and the detail of reconstruction
    965 algorithms.
     968algorithms. Using the same $pp \rightarrow ggX$ events as in section \ref{sec:jetresol} with a gluon transverse momentum at $80$ and $640~\textrm{GeV}/c$, the mis-identification rate of jets as $\tau\textrm{-jets}$ is evaluated at $6.4\times 10^{-4}$ and $1.7\times 10^{-4}$ respectively.
    966969
    967970\begin{table}[!h]
     
    10101013the events themselves. The visibility of each set of objects ($e^\pm$,
    10111014$\mu^\pm$, $\tau^\pm$, jets, transverse missing energy) is enhanced by a colour
    1012 coding. Moreover, kinematics information of each object is visible by a simple
    1013 mouse action. As an illustration, an associated photoproduction of a $W$ boson
     1015coding. Moreover, kinematics information of each object is also visible.
     1016As an illustration, an associated photoproduction of a $W$ boson
    10141017and a $t$ quark~\citep{bib:wtphotoproduction} is shown in Fig.~\ref{fig:wt}.
    10151018
     
    10571060Part of this work was supported by the Belgian Federal Office for Scientific, Technical and Cultural Affairs through the Interuniversity Attraction Pole P6/11.
    10581061
    1059 
    10601062\begin{thebibliography}{99}
    10611063\addcontentsline{toc}{section}{References}
     
    10721074\bibitem{bib:cmsjetresolution} The \textsc{CMS} Collaboration, \textbf{CERN/LHCC} \href{http://documents.cern.ch/cgi-bin/setlink?base=LHCc&categ=public&id=LHCc-2006-001}{2006-001}.
    10731075\bibitem{bib:ATLASresolution} The \textsc{ATLAS} Collaboration, \textbf{CERN-OPEN} 2008-020, \\arXiv:\href{http://arxiv.org/abs/arxiv:0901.0512}{0901.0512v1}[hep-ex].
     1076\bibitem{bib:cpumark} PassMark (r) software, \href{http://www.cpubenchmark.net/common\_cpus.html}{www.cpubenchmark.net}.
    10741077\bibitem{bib:hector} %\textit{Hector}, \textit{a fast simulator for the transport of particles in beamlines},
    10751078X. Rouby, J. de Favereau, K. Piotrzkowski, \textbf{JINST} \href{http://www.iop.org/EJ/abstract/1748-0221/2/09/P09005}{2 P09005 (2007)}.
     
    11951198\subsection{Getting started}
    11961199 
    1197 In order to run \textit{Delphes} on your system, first download its sources and compile them:\\
    1198 \begin{quote}\texttt{wget http://www.fynu.ucl.ac.be/users/s.ovyn/Delphes/files/Delphes\_V\_*.tar.gz}\end{quote}
    1199 Replace the \texttt{*} symbol by the proper version number. Always refer to the download page on the \textit{Delphes} website \href{http://www.fynu.ucl.ac.be/users/s.ovyn/Delphes/download.html}{http://www.fynu.ucl.ac.be/users/s.ovyn/Delphes/download.html}. Current version of Delphes for this manual is V 1.8 (July 2009).
     1200In order to run \textit{Delphes} on your system, first download source code and compile them:\\
     1201\begin{quote}\texttt{wget http://projects.hepforge.org/delphes/files/Delphes\_V\_*.tar.gz}\end{quote}
     1202Replace the \texttt{*} symbol by the proper version number. Current version of Delphes for this manual is V 1.8 (July 2009).
    12001203
    12011204\begin{quote}
     
    12261229 
    12271230\subsubsection{Setting up the configuration}
     1231\label{sec:config}
    12281232 
    12291233The program is driven by two datacards (default cards are {\verb data/DetectorCard.dat } and {\verb data/TriggerCard.dat }) which allow the user to choose among a large spectrum of running conditions. Please note that if the user does not provide these datacards, the running will be done using the default parameters defined in the constructor of the class \texttt{RESOLution} (see next). If you choose a different detector or running configuration, you will need to edit the datacards accordingly. Detector and trigger cards are provided in the \texttt{data/} subdirectory for the \textsc{CMS} and \textsc{ATLAS} experiments.
     
    13891393VFD_s_zdc         140   // distance of the ZDC, from the IP, in [m]
    13901394
    1391 #\textit{Hector} parameters
     1395#Hector parameters
    13921396RP_220_s          220     // distance of the RP to the IP, in meters
    13931397RP_220_x          0.002   // distance of the RP to the beam, in meters
     
    13961400RP_beam1Card      data/LHCB1IR5_v6.500.tfs // beam optics file, beam 1
    13971401RP_beam2Card      data/LHCB2IR5_v6.500.tfs // beam optics file, beam 2
    1398 RP_IP_name        IP5     // tag for IP in \textit{Hector} ; 'IP1' for ATLAS
     1402RP_IP_name        IP5     // tag for IP in Hector ; 'IP1' for ATLAS
    13991403RP_offsetEl_x     0.097   // horizontal separation between both beam, in meters
    14001404RP_offsetEl_y     0       // vertical separation between both beam, in meters
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