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Transcript
The CMS Fast Simulation Do we need a Fast Simulation ? How does it work ? tracking calorimeter muons Performance Conclusion Why do we need a Fast Simulation ? Large samples of simulated data are needed to develop reconstruction algorithms, analyses to adapt the trigger tables to new conditions (like 14->10 TeV) in addition when we have data, to determine the efficiencies on the signal, to determine some background contamination, to perform scans of the parameter space, evaluate systematic errors.... why producing only one million events when we could produce one billion of events of the same quality ? In the physics TDR, many analyses relied totally or partially on FAMOS, the previous version of the Fast Simulation the new version is, of course, much better it is not only a simulation, it also produces reconstructed quantities (tracks, RecHits ...). The standard reconstruction algorithm are used as much as possible The goal is to be as fast as possible (possibly 1000 times faster than the slow simulation/reconstruction) while keeping the same level of accuracy Track propagation, Interaction with the tracker material TEC TOB TIB A simplified interaction geometry is used ! with some details though Active and passive layers are modelled The complete magnetic field map is used for the track propagation between two surfaces TEC Pixels Material effects simulation R. Ranieri Do we need to simulate the material effects ? magnetic field 4T ~35% of the electrons radiate more than 70% of their initial energy before reaching the ECAL the energy is spread in j impact on the cluster shape Simulating properly the material effects is not only needed, it is essential ! Bremsstrahlung simulation The Brem photon emission probability and spectrum are calculated analytically, layer by layer The layer thickness is tuned to reproduce the number of photons in the Geant-based simulation: the photon energy spectrum is beautifully reproduced... (incidentally , this tuning reproduces the actual layer thickness in x/x0) Absolute normalization ! Single electrons pT=35 GeV/c Flat in h Fast Simulation – Slow Simulation Material effects simulation The Bremsstrahlung, the photon conversion, the multiple scattering as well as the energy loss and the in-flight decays are simulated analytically The nuclear interactions are of utmost importance ! 20% of the pions undergo a N.I in the tracker consequence on the pion track reconstruction efficiency (several percent at 1 GeV) A single tau event where a pion undergoes a nuclear interaction in the tracker (full simulation) Nuclear interactions simulation total The elastic and inelastic cross sections are taken from expt'al measurements (PDG) elastic Full Geometry The tracker layer thickness is expressed in terms of /0 FAMOS 0.31 x/X0 (total) or 0.25 x/X0 (inelastic) not strictly true, but good approximation in the tracker acceptance Data files of inelastic N.I have been created 2.5 million N.I saved, 9 different hadrons, 1<E<1000 GeV when a N.I occurs, a N.I is picked up randomly in the relevant energy range a rotation around the particle direction is made (extra randomness) Nuclear interactions Number of nuclear interactions for 500K 15 GeV pions Fast Simulation − Full Simulation A single tau event where a pion undergoes a nuclear interaction in the tracker (fast simulation) Tracking SimHits The hits are located on the detailed tracker module geometry (propagation to the closest active layer modules) only for charged particle with p > 0.5 GeV/c create a SimHit if an intersection exists this allows the mis-alignment to be simulated The energy loss is simulated as well Tracking RecHits smearing The SimHits are then smeared a layer-dependent Gaussian smearing is applied in the strips in the pixels, the smearing is done according to cluster-multiplicityand incidence-angle-dependent position resolution distributions (obtained from the full sim – will be obtained from the data) the result is turned into tracking RecHits Resolution function vs. Fast Sim Track reconstruction in the fast simulation Two possibilities up to now, a "fast tracking" has been implemented the seeding efficiency is emulated : check that at least one combination of hits fulfills the seed selection criteria the hits belonging to a given track are fit (standard fitter) the pattern recognition is also emulated (outlier rejection) : remove hits with large contribution to the c2 and redo the fit as a result, there are no fake tracks (the fraction of fake tracks with ≥8 hits in the standard tracking is well below 1%) special treatment required to mimic the pattern recognition behaviour in the case of in-flight decays/N.I. the possibility to run the full tracking on the Fast Sim output is being implemented Track reconstruction : comparisons in tt events Fast Full Track quality Calorimeter simulation At this level, the particles have been propagated, they interacted with the tracker material, new particles have been created... So we are left with the list of the particles reaching the ECAL all the showers are simulated individually using a shower parameterizatio à la GFLASH to properly simulate the detector effects, which are essential, the showers are placed in the (crystals, towers, strips, cracks, leakage..) detailed geometry The CaloHits thus obtained are then turned into RecHits (noise, zero-suppression...) A parameterization à la GFLASH is also used for the hadrons; the response and resolution of the HCAL is taken from the fullsim Electromagnetic showers : test-beam • The simulation is done in two steps – the shower is simulated as if the ECAL was an homogeneous medium – then the shower is transported into the actual ECAL, taking into account several detector effects which are essential (cracks, leakage, magnetic field...) – it is very challenging to do it quickly. In the end ~6ms for a 40 GeV shower • The lateral shower profile can be checked/tuned on test-beam data x (mm) y H4 FAMOS |y-yM| < 2 mm y xM beam x (mm) |x-xM| < 2 mm y (mm) M x Electron reconstruction • A Gaussian Sum Filter algorithm is used for the electron track fit Single electrons Total Brem energy, as measured by the tracker Reconstructed Z-mass an excellent agreement is obtained the electron fake rates are also well reproduced (at the level of precision allowed by the Full sim samples statistics) Hadron simulation and jets The single hadron response has been retuned on single pions not undergoing an inelastic interaction in the tracker Di-jets event ETrec / ETgen 40 < pT < 50 GeV iterative cone R=0.5 600< pT < 800 GeV jet EM-energy HB HE HF Slow Fast the error bar is actually the RMS jet HAD-energy A very good agreement is obtained for jets for all pT's and all h's ! ... but the agreement with test-beam data for single particles has to be improved HB Muons • Two versions available – Parameterized (resolution, efficiencies): the matching with the trackertracks being done by the standard algorithm – a tracker-like simulation: simulating the hits, propagation in the iron.. • Then apply standard digi+reco. Parameterization, used for the L1 simulation Muon from SimHits will become soon the default, alowing the mis-alignment to be simulated Topological variables Usually, the “4-vector smearing”-based fast simulations fail at correctly reproducing the MET as well as the topological variables here the agreement is remarkably good ! (mostly thanks to the implementation of the N.I. in the tracker) SUSY events b tagging The track counting, track probability and secondary vertex algorithms are available b jets udsg Difference at 10-4 level !!! (will be recovered; slightly different seedings in the two versions) Fraction of the jet energy carried by the tracks linked to the reconstructed seconda vertex combined SV algorithm with MVA setup udsg -efficiency charm -efficiency b tagging : final results b-efficiency Very good agreement b-efficiency Pile-up simulation • Only the in-time pile-up is implemented (no plan to do the out-of-time) • The generated particles of the pile-up events (with a smeared vertex) are added to the signal event particles • only the primary particles are saved (home-made format rootfiles) • the decays and a rotation are done in the Fast Sim (extra randomness) • 1 million of pile-up events is available by default on disk (only 700MB!) Other goodies • The trigger is available – the real L1 emulators are used – the standard HLT code, using the Fast Sim “special” tracking is used, thus – allowing to use the Fast Sim for trigger menu optimization • Tracker mis-alignment, calorimeter mis-calibration Fast only ideal alignment Fast vs. Full Leading jet 0/pb 10/pb 100/pb IP/sIP (2nd track) Timing • With the current version, the simulation of a physics event, with pile-up and HLT takes 2-3 s – the timing is actually dominated by the reconstruction – the simulation (which includes the tracking) takes ~400ms • In addition, the full job (generation->HLT->reconstruction) can be done in one go, with the possibility to run the reconstruction only on the events that pass the HLT – a half-a-billion events production with Madgraph has recently been done in less than two weeks – an similar one at 10 TeV is planned Summary • The CMS Fast Simulation is widely used by the collaboration – – – – • the full compatibility with the standard software the flexibility and the speed the precision the “tunability”, which will be of utmost importance when the first data arrive are major assets for this simulation, even if there are still items to develop,or to improve The maintenance is heavy because the reconstruction software is evolving quickly – In addition, the changes in the standard tracking have to be carefully followed and implemented in the Fast Sim tracking • Developing a Fast Sim is a great experience: one learns a lot on the physics in the detector and on reconstruction algorithms