Changeset 565 in svn
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trunk/paper/CommPhysComp/notes.tex (modified) (25 diffs)
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trunk/paper/CommPhysComp/notes.tex
r562 r565 49 49 calorimeters and a muon system, and possible very forward detectors arranged 50 50 along the beamline. 51 The framework is interfaced to standard file formats (e.g.\ Les Houches Event 52 File or \texttt{HepMC}) and outputs observables such as isolated leptons, 51 The framework is interfaced to standard file formats and outputs observables such as isolated leptons, 53 52 missing transverse energy and collection of jets which can be used for dedicated 54 53 analyses. The simulation of the detector response takes into account the effect … … 119 118 the various detector inefficiencies, the dead material, the imperfections and 120 119 the geometrical details. Their simulation is in general performed by means of 121 the GEANT~\citep{bib:geant} packageand final observables used for analyses120 the GEANT~\citep{bib:geant} toolkit and final observables used for analyses 122 121 usually require sophisticated reconstruction algorithms. 123 122 … … 129 128 130 129 In this context, a new framework, called \textit{Delphes}~\citep{bib:delphes}, 131 has been develop ped, for a fast simulation of a general-purpose collider132 experiment .130 has been developed, for a fast simulation of a general-purpose collider 131 experiment~\citep{bib:othersim}. 133 132 Using this framework, observables such as cross-sections and efficiencies after 134 event selection can be estimated for specific reactions.133 event selection can be estimated for specific processes. 135 134 Starting from the output of event generators, the simulation of the detector 136 135 response takes into account the subdetector resolutions, by smearing the … … 159 158 \begin{figure*}[!ht] 160 159 \begin{center} 161 \includegraphics[scale=0. 78]{fig1}160 \includegraphics[scale=0.60]{fig1} 162 161 \caption{Flow chart describing the principles behind \textit{Delphes}. Event 163 162 files coming from external Monte Carlo generators are read by a converter stage … … 267 266 By default, a track is assumed to be reconstructed with $90\%$ probability if 268 267 its transverse momentum $p_T$ is higher than $0.9~\textrm{GeV}/c$ and if its 269 pseudorapidity $|\eta| \leq 2.5$~\citep{qr:tracks}. No smearing is currently 270 applied on track parameters. For each track, the positions at vertex 271 $(\eta,\phi)$ and at the entry point in the calorimeter layers 272 $(\eta,\phi)_{calo}$ are available. 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 269 $(\eta,\phi)_{calo}$ are available while the helix parameters of tracks, especially the impact parameters are not. 273 270 274 271 … … 307 304 \label{eq:caloresolution} 308 305 \end{equation} 309 where $S$, $N$ and $C$ are the \textit{stochastic}, \textit{noise} and \textit{constant} terms , respectively,and $\oplus$ stands for quadratic additions~\citep{qr:energysmearing}.\\306 where $S$, $N$ and $C$ are the \textit{stochastic}, \textit{noise} and \textit{constant} terms respectively, $E$ is in GeV and $\oplus$ stands for quadratic additions~\citep{qr:energysmearing}.\\ 310 307 311 308 In the default parametrisation, ECAL and HCAL are assumed to cover the … … 350 347 the energy, determined according to their decay products, that would be 351 348 deposited into the \textsc{ECAL} ($E_{\textsc{ECAL}}$) and into the 352 \textsc{HCAL} ($E_{\textsc{HCAL}}$). Defining $F$ as the fraction of the energy 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 353 351 leading to a \textsc{HCAL} deposit, the two energy values are given by 354 352 \begin{equation} … … 362 360 where $0 \leq F \leq 1$. The resulting calorimetry energy measurement given 363 361 after the application of the smearing is then $E = E_{\textsc{HCAL}} + 364 E_{\textsc{ECAL}}$. For $K_S^0$ and $\Lambda$ hadrons, the energy fraction is 365 $F$ is assumed to be $0.7$~\citep{qr:emhadratios}.\\ 362 E_{\textsc{ECAL}}$. For $K_S^0$ and $\Lambda$ hadrons, the energy fraction $F$ is assumed to be $0.7$~\citep{qr:emhadratios}.\\ 366 363 367 364 … … 399 396 The electron, muon and photon collections contains only the true final-state 400 397 particles identified via the generator-data. In addition, these particles must 401 pass fiducial cuts taking into account the magnetic field effects and some 402 additional reconstruction cuts. 403 404 Consequently, no fake candidates enter these collections. However, when needed, 405 fake candidates can be added into the collections at the analysis level, when 406 processing \textit{Delphes} output data. As effects like bremsstrahlung are not 407 taken into account along the lepton propagation in the tracker, no clustering is 408 needed for the electron reconstruction in \textit{Delphes}. 398 pass fiducial cuts taking into account the magnetic field effects and have a 399 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}. 401 402 %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. 403 409 404 410 405 \subsubsection*{Electrons and photons} 411 Real electron ($e^\pm$) and photon candidates are associated to the final-state 412 collections if they fall into the acceptance of the tracking system and have a 406 Real electron ($e^\pm$) and photon candidates are identified if they fall into the acceptance of the tracking system and have a 413 407 transverse momentum above some threshold (default: $p_T > 10~\textrm{GeV}/c$). 414 408 \textit{Delphes} assumes a perfect … … 454 448 (2) the lepton transverse momentum~\citep{qr:caloisolation}: 455 449 $$ \rho_\ell = \frac{\Sigma_i E_T(i)}{p_T(\ell)}~,~ i\textrm{ in }N \times N 456 \textrm { grid centred on }\ell.$$ 457 450 \textrm { grid centred on }\ell.$$ 451 452 Finally it should be mentioned that because photons from physics bremsstrahlung are not added to the electron, they appear in the calorimetric isolation energy. This can lead to unrealistically high isolation energies in the case of very high energetic electrons while in a full simulation most bremsstrahlung photons overlap with the electron and do therefore not enter in the isolation energy. 458 453 459 454 \subsection{Jet reconstruction} … … 464 459 tools\footnote{A more detailed description of the jet algorithms is given in the 465 460 User Manual, in appendix.}. Six different jet reconstruction schemes are 466 available~\citep{bib:FASTJET,qr:jetalgo} . For all of them, the calorimetric461 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 467 462 cells are used as inputs. Jet algorithms differ in their sensitivity to soft 468 particles or collinear splittings, and in their computing speed performances. 469 470 \subsubsection*{Cone algorithms} 471 472 \begin{enumerate} 473 474 \item {\it CDF Jet Clusters}~\citep{bib:jetclu}: Cone algorithm forming jets by 475 combining cells lying within a circle (default radius $\Delta R=0.7$) in the 476 $(\eta$, $\phi)$ space. Jets are seeded by all cells with transverse energy 477 $E_T$ above a given threshold (default: $E_T > 478 1~\textrm{GeV}$)~\citep{qr:jetparams}. 479 480 \item {\it CDF MidPoint}~\citep{bib:midpoint}: Cone algorithm with additional 481 ``midpoints'' (energy barycentres) in the list of seeds. 482 483 \item {\it Seedless Infrared Safe Cone}~\citep{bib:SIScone}: The 484 \textsc{SISC}one algorithm is simultaneously insensitive to additional soft 485 particles and collinear splittings. 486 \end{enumerate} 487 488 \subsubsection*{Recombination algorithms} 489 490 The next three jet algorithms rely on recombination schemes where calorimeter 491 cell pairs are successively merged: 492 493 \begin{enumerate}[start=4] 494 \item {\it Longitudinally invariant $k_t$ jet}~\citep{bib:ktjet}, 495 \item {\it Cambridge/Aachen jet}~\citep{bib:aachen}, 496 \item {\it Anti $k_t$ jet}~\citep{bib:antikt}, where hard jets are exactly 497 circular in the $(y,\phi)$ plane. 498 \end{enumerate} 499 500 The recombination algorithms are safe with respect to soft radiations 501 (\textit{infrared}) and collinear splittings. Their implementations are similar 502 except for the definition of the \textit{distances} used during the merging 503 procedure. 504 505 By default, reconstruction uses the CDF cone algorithm. Jets are stored if their 506 transverse energy is higher than $20~\textrm{GeV}$~\citep{qr:ptcutjet}. 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}. 507 464 508 465 509 466 \subsubsection*{Energy flow} 510 467 511 In jets, several particle can leave their energy in toa given calorimetric cell,468 In jets, several particle can leave their energy in a given calorimetric cell, 512 469 which broadens the jet energy resolution. However, the energy of charged 513 470 particles associated to jets can be deduced from their associated track, thus … … 530 487 parent $b$ quark. For $c$-jets and light jets (i.e.\ originating in $u$, $d$, 531 488 $s$ quarks or in gluons), a fake $b$-tagging efficiency of $10 \%$ and $1 \%$ 532 is assumed respectively~\citep{qr:btag}. Therefore, in current version of489 is assumed respectively~\citep{qr:btag}. In current version of 533 490 \textit{Delphes}, the displacement of secondary vertices is not taken into 534 account. As such, the $b$-tagging efficiency is below the expected $40\%$.491 account. 535 492 536 493 \subsection{Identification of hadronic \texorpdfstring{$\tau$}{\texttau} decays} 537 494 538 495 Jets originating from $\tau$-decays are identified using a procedure consistent 539 with the one applied in a full detector simulation~\citep{bib:cmsjetresolution}.496 with the one applied in a full detector reconstruction~\citep{bib:cmsjetresolution}. 540 497 The tagging relies on two properties of the $\tau$ lepton. First, $77\%$ of the 541 $\tau$ hadronic decays contain only one charged hadron associated toa few498 $\tau$ hadronic decays contain only one charged hadron in combination with a few 542 499 neutrals (\textit{1-prong}). Secondly, the particles arisen from the 543 500 $\tau$ lepton produce narrow jets in the calorimeter (this is defined as the jet … … 602 559 of tracks associated to particles with significant transverse momenta is one and 603 560 only one in a cone of radius $R^\textrm{tracks}$ ($3-$prong $\tau$-jets are 604 rejected) . This cone should be entirely incorporated into the tracker to be561 rejected)~\footnote{In release 1.9, the 3-prong tau decays are also included.}. This cone should be entirely incorporated into the tracker to be 605 562 taken into account. Default values of these parameters are given in 606 563 Tab.~\ref{tab:tauRef}. … … 644 601 However, as muon candidates, tracks and calorimetric cells are available in the 645 602 output file, the missing transverse energy can always be reprocessed a 646 posteriori with more specialised algorithms. 603 posteriori with more specialised algorithms. Moreover, the degradations of the missing transverse energy performance due to noise is not simulated. 647 604 648 605 \section{Trigger emulation} … … 657 614 658 615 A trigger emulation is included in \textit{Delphes}, using a fully 659 parametrisable \textit{trigger table} \citep{qr:triggercard}. When enabled, this 660 trigger is applied on analysis-object data. In a real experiment, the online 661 selection is often divided into several steps (or \textit{levels}). 662 corresponding to the different trigger levels. 663 First-level triggers are fast and simple but based only on partial data as not 664 all detector front-ends are readable within the decision latency. 665 Higher level triggers are more complex, of finer-but-not-final quality and 666 based on full detector data. 667 668 Real triggers are thus intrinsically based on reconstructed data with a worse 669 resolution than final analysis information. On the contrary, the same 670 information is used in \textit{Delphes} for the trigger emulation and for final 671 analyses. 616 parametrisable \textit{trigger table} \citep{qr:triggercard}. While triggers in real experiments are intrinsically based on reconstructed data with a worse 617 resolution than final analysis information, in \textit{Delphes} the same information is used for the trigger emulation and for final analyses. 672 618 673 619 \section{\label{sec:vfd}Very forward detector simulation} … … 801 747 To be able to reach these detectors, particles must have a charge identical to 802 748 the beam particles, and a momentum very close to the nominal value of the beam 803 partic ules. These taggers are near-beam detectors located a few millimetres from749 particles. These taggers are near-beam detectors located a few millimetres from 804 750 the true beam trajectory and this distance defines their acceptance 805 751 (Tab.~\ref{tab:fdetacceptance}). For instance, roman pots at $220~\textrm{m}$ 806 752 from the \textsc{IP} and $2~\textrm{mm}$ from the beam will detect all forward 807 protons with an energy between $120$ and $900~\textrm{GeV}$~\citep{bib:hector}.753 protons with an energy loss between $120$ and $900~\textrm{GeV}$~\citep{bib:hector}. 808 754 In \textit{Delphes}, extra hits coming from the beam-gas events or 809 755 secondary particles hitting the beampipe in front of the detectors are not taken … … 847 793 defined according to the detector specifications. Similarly, the $b$-tagging 848 794 efficiency (for real $b$-jets) and misidentification rates (for fake $b$-jets) 849 are taken directly from the expected values of the experiment. Unlike these 850 simple objects, jets and missing transverse energy should be carefully 795 are taken directly from the expected values of the experiment. Unlike these objects, jets and missing transverse energy should be carefully 851 796 cross-checked. 852 797 … … 897 842 generator-level particles $E_T^\textrm{MC}$, in a \textsc{CMS}-like detector. 898 843 The jets events are reconstructed with the JetCLU clustering algorithm with a 899 cone radius of $0.7$ . The maximum separation between the reconstructed and844 cone radius of $0.7$ and no energy flow correction. The maximum separation between the reconstructed and 900 845 \textsc{MC}-jets is $\Delta R= 0.25$. Dotted line is the fit result for 901 846 comparison to the \textsc{CMS} resolution~\citep{bib:cmsjetresolution}, in blue. … … 940 885 energy of the closest jet of generator-level particles $E^\textrm{MC}$, in an 941 886 \textsc{ATLAS}-like detector. The jets are reconstructed with the $k_T$ 942 algorithm with a radius $R=0.6$. The maximal matching distance between 887 algorithm with a radius $R=0.6$ and no energy flow correction. The maximal 888 matching distance between 943 889 \textsc{MC}- and reconstructed jets is $\Delta R=0.2$. Only central jets are 944 890 considered ($|\eta|<0.5$). Dotted line is the fit result for comparison to the … … 961 907 The samples used to study the \textsc{MET} performance are identical to those 962 908 used for the jet validation. It is worth noting that the contribution to 963 $E_T^\textrm{miss}$ from muons is negligible in the studied sample. 909 $E_T^\textrm{miss}$ from muons is negligible in the studied sample. Indeed for e.g.$W\rightarrow \mu \nu$ samples the missing transverse energy should be corrected for the presence of muons. 964 910 The input samples are divided in five bins of scalar $E_T$ sums $(\Sigma E_T)$. 965 911 This sum, called \textit{total visible transverse energy}, is defined as the … … 1055 1001 coverage of the different detector subsystems. 1056 1002 As an example, the generic detector geometry assumed in this paper is shown in 1057 Fig.~\ref{fig:GenDet3} and~\ref{fig:GenDet2}. The extensions of the central1003 Fig.~\ref{fig:GenDet3}. The extensions of the central 1058 1004 tracking system, the central calorimeters and both forward calorimeters are 1059 1005 visible. Note that only the geometrical coverage is depicted and that the 1060 1006 calorimeter segmentation is not taken into account in the drawing of the 1061 1007 detector. 1062 1063 \begin{figure}[!ht]1064 \begin{center}1065 \includegraphics[width=\columnwidth]{fig11}1066 \caption{Layout of the generic detector geometry assumed in \textit{Delphes}.1067 Open 3D-view of the detector with solid volumes. Same colour codes as for1068 Fig.~\ref{fig:GenDet3} are applied. Additional forward detectors are not1069 depicted.}1070 \label{fig:GenDet2}1071 \end{center}1072 \end{figure}1073 1008 1074 1009 Deeper understanding of interesting physics processes is possible by displaying … … 1078 1013 mouse action. As an illustration, an associated photoproduction of a $W$ boson 1079 1014 and a $t$ quark~\citep{bib:wtphotoproduction} is shown in Fig.~\ref{fig:wt}. 1080 1081 % This corresponds to a $pp(\gamma p \rightarrow Wt)pX$ process, where the $Wt$1082 % couple is induced by an incoming photon emitted by one of the colliding1083 % proton. This leading proton survives after photon emission and is present in1084 % the final state. As the energy and virtuality of the emitted photon are low,1085 % the surviving proton does not leave the beam and escapes from the central1086 % detector without being detected. The experimental signature is a lack of1087 % hadronic activity in the forward hemisphere where the surviving proton1088 % escapes.1089 % The $t$ quark decays into a $W$ boson and a $b$ quark. Both $W$ bosons decay1090 % into leptons ($W \rightarrow \mu \nu_\mu$ and $W \rightarrow e \nu_e$). The1091 % balance between the missing transverse energy and the charged lepton pair is1092 % clear, as well as the presence of an empty forward region. It is interesting1093 % to notice that the reconstruction algorithms build a fake $\tau$-jet around1094 % the electron.1095 1015 1096 1016 \begin{figure}[!ht] … … 1108 1028 \end{figure} 1109 1029 1110 For comparison, Fig.~\ref{fig:gg} depicts an inclusive gluon pair production1111 $pp \rightarrow ggX$. The event final state contains more jets, in particular1112 along the beam axis, which is expected as the interacting protons are destroyed1113 by the collision.1114 1115 \begin{figure}[!ht]1116 \begin{center}1117 \includegraphics[width=0.6\columnwidth]{fig13}1118 \caption{Example of inclusive gluon pair production $pp \rightarrow ggX$. Many1119 jets are present in the event, in particular along the beam axis (black line).}1120 \label{fig:gg}1121 \end{center}1122 \end{figure}1123 1124 1125 1030 \section{Conclusion and perspectives} 1126 1031 1127 1032 We have described here the major features of the \textit{Delphes} framework, 1128 int roduced for the fast simulation of a collider experiment. This framework is a1033 intended for the fast simulation of a collider experiment. This framework is a 1129 1034 tool meant for feasibility studies in phenomenology, gauging the observability 1130 1035 of model predictions in collider experiments. … … 1159 1064 1160 1065 \bibitem{bib:delphes} \textit{Delphes}, \href{http://www.fynu.ucl.ac.be/delphes.html}{www.fynu.ucl.ac.be/delphes.html} 1066 \bibitem{bib:othersim} Other less sophisticated software for fast simulation: \textit{AcerDET} E. Richter-Was, \href{http://arxiv.org/abs/hep-ph/0207355}{arXiv:hep-ph/0207355v1}; \textit{PGS}, John Conway et al, \href{http://www.physics.ucdavis.edu/~conway/research/software/pgs/pgs4-general.htm}{http://www.physics.ucdavis.edu/~conway/} 1067 1161 1068 \bibitem{bib:Root} %\textsc{ROOT}, \textit{An Object Oriented Data Analysis Framework}, 1162 1069 R. Brun, F. Rademakers, Nucl. Inst. \& Meth. in \textbf{Phys. Res. A} \href{http://dx.doi.org/10.1016/S0168-9002(97)00048-X}{389 (1997) 81-86}. … … 1254 1161 \bibitem[s]{qr:ptcutjet} See the \texttt{PTCUT\_jet }variable in the detector card. 1255 1162 1256 \bibitem[t]{qr:jetparams} See the \texttt{JET\_coneradius} and \texttt{JET\_seed} variables in the detector card. The existing FastJet code has been modified to allow easy modification of the cell pattern in $(\eta, \phi)$ space. 1257 In following versions of \textit{Delphes}, a new dedicated plug-in will be created on this purpose. 1163 %\bibitem[t]{qr:jetparams} See the \texttt{JET\_coneradius} and \texttt{JET\_seed} variables in the detector card. The existing FastJet code has been modified to allow easy modification of the cell pattern in $(\eta, \phi)$ space. In following versions of \textit{Delphes}, a new dedicated plug-in will be created on this purpose. 1258 1164 1259 1165 \bibitem[u]{qr:energyflow} 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.
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