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trunk/paper/CommPhysComp/notes.tex
r565 r569 144 144 145 145 146 \textit{Delphes} includes the most crucialexperimental features, such as146 \textit{Delphes} includes important experimental features, such as 147 147 (Fig.~\ref{fig:FlowChart}): 148 148 \begin{enumerate} … … 164 164 The kinematics variables of the final-state particles are then smeared 165 165 according to the tunable subdetector resolutions. 166 Tracks are reconstructed in a simulated solenoidal magnetic field and166 Tracks are identified in a simulated solenoidal magnetic field and 167 167 calorimetric cells sample the energy deposits. Based on these low-level objects, 168 168 dedicated algorithms are applied for particle identification, isolation and … … 183 183 ``parton-level" analysis, it has some limitations. Detector geometry is 184 184 idealised, 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. 185 nor 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. 187 186 188 187 Several common datafile formats can be used as input in \textit{Delphes} … … 210 209 conditions by modifying basic detector parameters, including calorimeter and 211 210 tracking coverage and resolution, thresholds or jet algorithm parameters. 212 Even if \textit{Delphes} has been develop ped for the simulation of211 Even if \textit{Delphes} has been developed for the simulation of 213 212 general-purpose detectors at the \textsc{LHC} (namely, \textsc{CMS} and 214 \textsc{ATLAS} ), this input parameter file interfaces a flexible parametrisation213 \textsc{ATLAS}, with references~\citep{bib:cmsjetresolution} and~\citep{bib:ATLASresolution} throughout this document), this input parameter file interfaces a flexible parametrisation 215 214 for other cases, e.g.\ at future linear colliders~\citep{qr:datacards}. 216 215 The geometrical coverage of the various subsystems used in the default … … 266 265 By default, a track is assumed to be reconstructed with $90\%$ probability if 267 266 its 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 267 pseudorapidity $|\eta| \leq 2.5$~\citep{qr:tracks}. This reconstruction efficiency is assumed to be uniform and independent of the particle type. 268 The 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 269 269 $(\eta,\phi)_{calo}$ are available while the helix parameters of tracks, especially the impact parameters are not. 270 270 … … 277 277 characteristics are not identical in every direction, with typically finer 278 278 resolution and granularity in the central 279 regions~\citep{bib:cmsjetresolution,bib:ATLASresolution}. It is thus very 279 regions. %~\citep{bib:cmsjetresolution,bib:ATLASresolution}. 280 It is thus very 280 281 important to compute the exact coordinates of the entry point of the particles 281 282 into the calorimeters, in taking the magnetic field effect into account. … … 293 294 \begin{center} 294 295 \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}).} 296 297 \label{fig:calosegmentation} 297 298 \end{center} … … 337 338 338 339 339 Electrons and photons are assumed to leave their energy in the electromagnetic340 To simplify the simulation, electrons and photons are assumed to leave their energy in the electromagnetic 340 341 parts of the calorimeters (\textsc{ECAL} and \textsc{FCAL}, e.m.), while charged 341 342 and neutral final-state hadrons are assumed to leave their entire energy … … 345 346 generators although they may decay before reaching the calorimeters. The energy 346 347 smearing 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 348 the energy ($0 \leq F \leq 1$), determined according to their decay products, that would be 349 deposited 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. 352 The 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 $0 \leq F \leq 1$. 364 The resulting calorimetry energy measurement given 361 365 after the application of the smearing is then $E = E_{\textsc{HCAL}} + 362 366 E_{\textsc{ECAL}}$. For $K_S^0$ and $\Lambda$ hadrons, the energy fraction $F$ is assumed to be $0.7$~\citep{qr:emhadratios}.\\ … … 396 400 The electron, muon and photon collections contains only the true final-state 397 401 particles identified via the generator-data. In addition, these particles must 398 pass fiducial cuts taking into account the magnetic field effects andhave a402 pass fiducial cuts taking into account the magnetic field effects, have a 399 403 transverse 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}. 404 needed for the electron reconstruction in \textit{Delphes}. Moreover, charged leptons are added in their respective collections if their associated track is available. 401 405 402 406 %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. … … 406 410 Real electron ($e^\pm$) and photon candidates are identified if they fall into the acceptance of the tracking system and have a 407 411 transverse 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. 413 Electron energy is smeared according to the resolution of the calorimetric cell where it points to, but 411 414 independently from any other deposited energy in this cell. 412 415 Electrons 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. 417 As 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. 418 Similarly 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. 419 414 420 415 421 \subsubsection*{Muons} … … 461 467 available~\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 462 468 cells 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}. 469 particles 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}. 470 By 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. 464 471 465 472 … … 470 477 particles associated to jets can be deduced from their associated track, thus 471 478 providing 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 479 When 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 475 480 better jet energy reconstruction~\citep{qr:energyflow}. 476 481 … … 494 499 495 500 Jets originating from $\tau$-decays are identified using a procedure consistent 496 with the one applied in a full detector reconstruction ~\citep{bib:cmsjetresolution}.501 with the one applied in a full detector reconstruction. %~\citep{bib:cmsjetresolution}. 497 502 The tagging relies on two properties of the $\tau$ lepton. First, $77\%$ of the 498 503 $\tau$ hadronic decays contain only one charged hadron in combination with a few … … 504 509 \begin{center} 505 510 \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}.} 507 512 \label{h_WW_ss_cut1} 508 513 \end{center} … … 579 584 threshold on the $p_T$ of the $\tau$-jet candidate is requested to purify the 580 585 collection. This procedure selects $\tau$ leptons decaying hadronically with a 581 typical efficiency of $66\%$ .586 typical efficiency of $66\%$ relative to all hadronic $\tau$ decays. 582 587 583 588 \subsection{Missing transverse energy} … … 623 628 forward final-state particles. In \textit{Delphes}, Zero Degree Calorimeters, 624 629 roman 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}. 630 similarly as for CMS and ATLAS collaborations. %~\citep{bib:cmsjetresolution,bib:ATLASresolution}. 627 631 628 632 \begin{figure}[!ht] … … 782 786 proportional to the number of simulated events and on the considered physics 783 787 process. 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. 788 processed 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. 786 789 The quality and validity of the output are assessed by comparing the 787 790 resolutions 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. 790 792 791 793 Electrons and muons resolutions in \textit{Delphes} match by construction the … … 797 799 798 800 \subsection{Jet resolution} 801 \label{sec:jetresol} 799 802 800 803 The majority of interesting processes at the \textsc{LHC} contain jets in the … … 844 847 cone radius of $0.7$ and no energy flow correction. The maximum separation between the reconstructed and 845 848 \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.849 comparison to the \textsc{CMS} resolution, in blue. 847 850 The $pp \rightarrow gg$ dijet events have been generated with MadGraph/MadEvent 848 851 and hadronised with \textit{Pythia}.} … … 860 863 where $a$, $b$ and $c$ are the fit parameters. 861 864 It is then compared to the resolution published by the \textsc{CMS} 862 collaboration ~\citep{bib:cmsjetresolution}. The resolution curves from863 \textit{Delphes} and \textsc{CMS} are in good agreement .865 collaboration. 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 $500~\textrm{GeV}$. 864 867 865 868 Similarly, the jet resolution is evaluated for an \textsc{ATLAS}-like detector. … … 877 880 obtained with \textit{Delphes}, the result of the fit with 878 881 Equation~\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 $500~\textrm{GeV}$. 880 883 881 884 \begin{figure}[!ht] … … 889 892 \textsc{MC}- and reconstructed jets is $\Delta R=0.2$. Only central jets are 890 893 considered ($|\eta|<0.5$). Dotted line is the fit result for comparison to the 891 \textsc{ATLAS} resolution ~\citep{bib:ATLASresolution}, in blue. The $pp894 \textsc{ATLAS} resolution, in blue. The $pp 892 895 \rightarrow gg$ di-jet events have been generated with MadGraph/MadEvent and 893 896 hadronised with \textit{Pythia}.} … … 944 947 events is $\sigma_x = (0.6-0.7) ~ \sqrt{E_T} ~ \mathrm{GeV}^{1/2}$ with no 945 948 pile-up (i.e. extra simultaneous $pp$ collision occurring at high-luminosity in 946 the same bunch crossing) ~\citep{bib:cmsjetresolution}, which compares very well949 the same bunch crossing), which compares very well 947 950 with the $\alpha = 0.63$ obtained with \textit{Delphes}. Similarly, for an 948 951 \textsc{ATLAS}-like detector, a value of $0.53$ is obtained by \textit{Delphes} 949 952 for the $\alpha$ parameter, while the experiment expects it in the range $[0.53~ 950 ;~0.57]$ ~\citep{bib:ATLASresolution}.953 ;~0.57]$. 951 954 952 955 \subsection{\texorpdfstring{$\tau$}{\texttau}-jet efficiency} … … 963 966 quoted for comparison. The level of agreement is satisfactory provided possible 964 967 differences due to the event generation chain and the detail of reconstruction 965 algorithms. 968 algorithms. 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. 966 969 967 970 \begin{table}[!h] … … 1010 1013 the events themselves. The visibility of each set of objects ($e^\pm$, 1011 1014 $\mu^\pm$, $\tau^\pm$, jets, transverse missing energy) is enhanced by a colour 1012 coding. Moreover, kinematics information of each object is visible by a simple1013 mouse action.As an illustration, an associated photoproduction of a $W$ boson1015 coding. Moreover, kinematics information of each object is also visible. 1016 As an illustration, an associated photoproduction of a $W$ boson 1014 1017 and a $t$ quark~\citep{bib:wtphotoproduction} is shown in Fig.~\ref{fig:wt}. 1015 1018 … … 1057 1060 Part of this work was supported by the Belgian Federal Office for Scientific, Technical and Cultural Affairs through the Interuniversity Attraction Pole P6/11. 1058 1061 1059 1060 1062 \begin{thebibliography}{99} 1061 1063 \addcontentsline{toc}{section}{References} … … 1072 1074 \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}. 1073 1075 \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}. 1074 1077 \bibitem{bib:hector} %\textit{Hector}, \textit{a fast simulator for the transport of particles in beamlines}, 1075 1078 X. Rouby, J. de Favereau, K. Piotrzkowski, \textbf{JINST} \href{http://www.iop.org/EJ/abstract/1748-0221/2/09/P09005}{2 P09005 (2007)}. … … 1195 1198 \subsection{Getting started} 1196 1199 1197 In order to run \textit{Delphes} on your system, first download its sourcesand 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).1200 In 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} 1202 Replace the \texttt{*} symbol by the proper version number. Current version of Delphes for this manual is V 1.8 (July 2009). 1200 1203 1201 1204 \begin{quote} … … 1226 1229 1227 1230 \subsubsection{Setting up the configuration} 1231 \label{sec:config} 1228 1232 1229 1233 The 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. … … 1389 1393 VFD_s_zdc 140 // distance of the ZDC, from the IP, in [m] 1390 1394 1391 # \textit{Hector}parameters1395 #Hector parameters 1392 1396 RP_220_s 220 // distance of the RP to the IP, in meters 1393 1397 RP_220_x 0.002 // distance of the RP to the beam, in meters … … 1396 1400 RP_beam1Card data/LHCB1IR5_v6.500.tfs // beam optics file, beam 1 1397 1401 RP_beam2Card data/LHCB2IR5_v6.500.tfs // beam optics file, beam 2 1398 RP_IP_name IP5 // tag for IP in \textit{Hector}; 'IP1' for ATLAS1402 RP_IP_name IP5 // tag for IP in Hector ; 'IP1' for ATLAS 1399 1403 RP_offsetEl_x 0.097 // horizontal separation between both beam, in meters 1400 1404 RP_offsetEl_y 0 // vertical separation between both beam, in meters
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