The CMS collaboration has developed a fast Monte Carlo simulation of the CMS detector with event production rates 100-1000 times faster than the GEANT4-based simulation, with comparable accuracy. This paper discusses the simulation of particle propagation in the CMS detector and the response of the different parts of the detector: the silicon tracker, the electromagnetic calorimeter, the hadronic calorimeter and the muon system

Orbaker, Douglas

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Available on CMS information server CMS CR -2009/074The Compact Muon Solenoid ExperimentMailing address: CMS CERN, CH-1211 GENEVA 23, SwitzerlandConference Report10 May 2009 (v2, 14 May 2009)Fast Simulation of the CMS DetectorDouglas Orbaker on behalf of the CMS CollaborationUniversity of Rochester, Rochester, NY, USAAbstractThe CMS collaboration has developed a fast Monte Carlo simulation of the CMS detector with eventproduction rates 100-1000 times faster than the GEANT4-based simulation, with comparable accu-racy. This paper discusses the simulation of particle propagation in the CMS detector and the responseof the different parts of the detector: the silicon tracker, the electromagnetic calorimeter, the hadroniccalorimeter and the muon system.Presented at Computing in High Energy and Nuclear Physics (CHEP),March 21 - 27, 2009,Prague,CzechRepublic,15/05/2009May 14, 2009Fast Simulation of the CMS DetectorDouglas Orbaker a)Department of Physics and AstronomyUniversity of Rochester, Rochester, NY, USACMS collaborationAbstractThe CMS collaboration has developed a fast Monte Carlo simulation of the CMS detector with eventproduction rates 100-1000 times faster than the GEANT4-based simulation, with comparable accu-racy. This paper discusses the simulation of particle propagation in the CMS detector and the responseof the different parts of the detector: the silicon tracker, the electromagnetic calorimeter, the hadroniccalorimeter and the muon system.a) Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland1 IntroductionBy the end of 2009, the Large Hadron Collider will restart collisions and the CMS detector [1] will begin collectingphysics data. In order to make sense of the data and search for new physics phenomena, accurate and precise MonteCarlo simulations of the detector are needed. Two different types of simulation are used by the CMS collaboration:a GEANT4-based simulation, colloquially known as the “Full” Simulation, and a detector model which usessimplified geometry, response evaluation and pattern recognition to decrease the processing time per event, the“Fast” Simulation. This report discusses the latter simulation.To understand the large volume of data expected to be produced at full luminosity, CMS scientists will need anequally large or larger amount of simulated data, on the order of a few billion events. With complex events takingminutes to simulate, the Full Simulation cannot keep up with the data rate. At 100-1000 times faster per event, theFast Simulation is the only way to produce large statistic data sets necessary for studying background processesand systematic errors.Using intuitive detector parameters as inputs, the Fast Simulation can quickly and easily be tuned to reproducethe data. Not to be underestimated, the ability to tune the Fast Simulation will allow the data to be understoodmore quickly during the upcoming start up. At the present time, the tuning of the Fast Simulation is done usingparameters derived from the Full Simulation. The agreement between the results from the full-sim tuned FastSimulation and the Full Simulation is very good, as will be shown in some example plots later on.Because the Fast Simulation is only a simulation of the CMS detector and not of the physics during the collision,simulated particle decays produced by event generators such as PYTHIA are used as inputs. The resulting parti-cles are then propagated through the detector and all physically relevant material effects are included in the FastSimulation, which is necessary to accurately model the underlying physics.The output of the Fast Simulation is designed to be completely accessible to CMS users, containing objects withthe same format as the standard offline reconstruction. Analysis code designed to run on data will automaticallywork on files made with the Fast Simulation; no changes are needed.One of the main goals of the Fast Simulation is to produce analysis-grade simulated data. Some of the additionalfeatures that add realism to the simulation are in-time pile-up, emulations of the Level 1 and High Level Triggers,and mis-calibration and misalignment of the detector.2 Materials EffectsTo accurately model the propagation of the particles through the layers of the tracker, five different material effectsare taken into account: bremsstrahlung, photon conversions, multiple Coulomb scattering, energy loss throughionization and nuclear interactions. All of the effects except for nuclear interactions are calculated analytically,using references such as the PDG [2].Nuclear interactions are simulated in a different manner, because no analytical description is sufficient to describethe effect. Cross sections for various nuclear interactions, such as a pion colliding with a proton, are taken fromdifferent measurements and the probability of the interaction is calculated. The kinematics of the resulting daughterparticles are derived from single particle collisions using a particle gun in the Full Simulation, saved in files madebeforehand.To save time simulating the material effects, the tracker uses a simplified geometry of nested cylindrical layers (seeFigure 1). The thicknesses of the different layers are tuned to create the same amount of material interactions inthe Fast Simulation as in the Full Simulation (see Figure 2).Figure 1: Radiography of tracker by photon pair conversion from electrons in the fast (left) and full (right) simula-tions.Figure 2: This plot shows the comparison of the number conversion of electrons to photons in tracker betweenthe Fast Simulation (triangles) and the Full Simulations (solid lines) over pseudo-rapidity. The contributions ofdifferent parts of the tracker are shown: pixels (black), inner tracker (green), outer tracker (blue).3 TrackingThe base of the tracking simulation is the reconstructed hits. The local position resolution and efficiencies of thehits are currently parameterized with input from the Full Simulation, and in the future they will be parameterizedto match data. For the silicon strip tracker, the local positions are smeared according to a gaussian. The parameter-ization for the pixel detectors is more complicated, and depends on histograms derived from the Full Simulation,which make use of both the angle of incidence and the multiplicity of the pixel clusters.To make tracks, the Fast Simulation emulates the different steps of the standard iterative tracking sequence, usingonly the hits from the simulated tracks to make track candidates. Therefore, each reconstructed track correspondsto a simulated track. For the seeding emulation, only seeds that pass the standard seeding criteria are included. Thestandard pattern recognition algorithms are too time consuming for the Fast Simulation. Like the standard patternrecognition tracking, the Fast Simulation removes hits that give large contributions to the track χ2 from the tracks.The final tracking step uses the same fitting algorithms as the standard reconstruction sequence.High occupancy events may have fake tracks, which are not produced by the Fast Simulation. Hit sharing betweendifferent tracks is also not included in the Fast Simulation. For specialized studies, a translation algorithm allowthe reconstructed hits made with the Fast Simulation to be input into the full pattern recognition chain.The plots in Figure 3 show the accuracy of tracking in the Fast Simulation for a variety of particles, from singlemuon events to more complicated top pair decays with large track multiplicities.Figure 3: Clockwise from the top left: Pull in pT comparison for 10 GeV µ. pT resolution vs η comparison for 10GeV µ. Comparison for hits per track in tt¯ events. Comparison of the number of tracks versus pT for tt¯ events.The Fast Simulation is red and the Full Simulation is blue.4 CalorimetryAfter leaving the layers of the tracker, the particles interact with calorimeters. To simulate electron showers inthe EM calorimeter, the Fast Simulation uses the Grindhammer parameterization, similar to GFLASH [3]. Theshowers are first simulated in a homogeneous medium and then moved to the calorimeter. Detector effects suchas energy leakage into the inter-crystal gaps and energy leakage out the back of the EM calorimeter to the hadroncalorimeter are then included in the final measured energy. Photons undergo electron pair conversions within theEM calorimeter based on the number of radiation lengths they have traversed. The electron pairs then undergoshowering. To simulate the measured energy, zero suppression and electronics noise are included.Shower simulation in the hadron calorimeter is similar to the simulation in the EM calorimeter. A parameterizationof the energy response for different types of particles at a variety of energies and pseudo-rapidities is made fromthe Full Simulation. Further information on the simulation of the calorimeters is available in [4].To illustrate accuracy of energy measurements in the calorimeters, both electron and jet comparisons are shown inFigures 5 and 6. The jets are shown with a range of different energies.Figure 4: Left: Comparison of electron momentum resolution between the Fast Simulation (blue) and the FullSimulation (red) in ideal detector conditions. Right: Comparison of electron reconstruction efficiency versus ηbetween the Fast Simulation (blue) and the Full Simulation (red) in ideal detector conditions.Figure 5: Comparison of corrected jet energies over simulated jet energies for jets with pˆT of ∼ 30 GeV/c (top)and jets with pˆT of ∼ 100 GeV/c (bottom). The Fast Simulation is in red and the Full Simulation is in black.5 MuonsMuons are propagated in the magnetic field through the material of the tracker and the calorimeters, with averageenergy loss included, before encountering the muon chambers. To accurately simulate the propagation of muonsthrough the muons system, the Fast Simulation includes dEdx loss and multiple scattering of muons with the ironyokes of the detector.The Cathode Strip Chambers, Drift Tubes and Resistive Plate Chamber sections of the muon detector are allmodeled in the Fast Simulation. Because the interactions with the detector are included throughout the muon flightpath, muons are well modeled. Figure 7 shows the agreement of the Fast Simulation in 1/pT resolution with theFull Simulation when multiple scattering is turned on.Figure 6: Comparison of Mjj and MET for jets from QCD events with pˆT = 80 - 120 GeV/c. The Fast Simulationis in black and the Full Simulation is in brown.Figure 7: Comparison of 1/pT resolution between the Fast Simulation (red) and the Full Simulation (blue). Thegreen line is the 1/pT resolution when multiple scattering is turned off. Notice the improvement in the FastSimulation when multiple scattering is turned on.6 Applications to PhysicsThe Fast Simulation achieves accurate reconstruction of physics-level objects by following the propagation ofthe particles through the entire detector and including the materials interactions within the detector. Because theproducts of τ lepton decays interact with and are detected by various sub-detectors, comparisons in kinematics ofthe reconstructed taus are good benchmarks for the overall agreement between the fast and the Full Simulations(see Figure 8).One of the main applications of tracking in physics analyses is b tagging. Strict quality criteria are placed on thetracks used in b tagging, making any of the effects discussed in Section 3, such as fake rates, negligible. For thisreason, the Fast Simulations gives a good description of the physics results. The accuracy of one of the b taggingdiscriminants is shown in Figure 9.Various features give the Fast Simulation the ability to produce event characteristics and conditions necessary forphysics analysis. To simulate conditions in the high luminosity environment of the LHC, in-time pile-up can beturned on for any type of event. The Fast Simulation models in-time pile-up by including minimum-bias events,generated beforehand, along with the decay products from the signal event in the group of particles propagatedthrough the detector. Trigger paths are simulated in the Fast Simulation, filtering and saving events on disk basedon the trigger decision. Mis-calibration of the calorimeters and misalignment of the tracker can also be included inthe Fast Simulation to simulate events in the detector environment during LHC startup. Plots made with electronsbefore and after mis-alignment/miscalibration agree well with the Full Simulation, as seen in Figure 10.Figure 8: Comparison of reconstructed visible energy - simulated visible energy for τ decays between the FastSimulation (yellow) and the Full Simulation (black).Figure 9: Comparison of the impact parameter significance for the second leading pT track for jets from b (left)and udsg (right) between the Fast Simulation (red, dotted) and the Full Simulation (black, solid).7 ConclusionWith the inclusion of all relevant material effects, the Fast Simulation of the CMS detector can accurately andquickly produce events in the standard output format. As a detector model based on intuitive parameters, the FastSimulation can be adjusted to match data soon after the startup of collisions in late 2009. Currently, the FastSimulation is tuned to the GEANT4-based simulation and agrees well with the Full Simulation for a variety ofparticle interactions across a wide range of energies. The Fast Simulation has been utilized for the large scaleproduction of a few billion events and is ready for high statistics studies in the future.Figure 10: In the top row: Comparisons of electron reconstruction efficiency in φ with perfect detector conditions(left) and start up detector conditions (right). In the bottom row: Comparisons of electron energy over electronmomentum in perfect (left) and startup (right) conditions. Startup conditions include tracker misalignment andcalorimeter mis-calibration. The Fast Simulation is in blue and the Full Simulation is in red.8 AcknowledgementsThanks to Fast Simulation group, especially Patrizia Azzi and Salavat Abdullin for their help.References[1] The CMS Collaboration, “The CMS Experiment at the CERN LHC”, JINST 3, S08004, (2008)[2] C. Amsler et al., “The Review of Particle Physics”, Physics Letters B667, 1 (2008)[3] G. Grindhammer, M. Rudowicz, S. Peters, “The Fast Simulation Of Electromagnetic and Hadronic Showers”,Nucl. Instrum. Meth. A290:469, (1990)[4] The CMS Collaboration, “The Physics Technical Design Report, Volume 1” CERN/LHCC 2006-001, (2006)(pp. 55-64)

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