1 / 31

Tutorial: SLHC Calorimeter Trigger Tools

Tutorial: SLHC Calorimeter Trigger Tools. Monika Grothe U Wisconsin. Documentation for SLHC calo trigger emulator: https://twiki.cern.ch/twiki/bin/view/CMS/SLHCCaloTriggerTools Documentation on algorithm it emulates:

duyen
Télécharger la présentation

Tutorial: SLHC Calorimeter Trigger Tools

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Tutorial: SLHC Calorimeter Trigger Tools Monika Grothe U Wisconsin Documentation for SLHC calo trigger emulator: https://twiki.cern.ch/twiki/bin/view/CMS/SLHCCaloTriggerTools Documentation on algorithm it emulates: https://svnweb.cern.ch/cern/wsvn/tdr2/notes/grothe_001/#path_notes_grothe_001_ Disclaimer: This tutorial is geared towards somebody with basic knowledge in CMSSW software M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  2. Recap: Status quo SLHC Calorimeter trigger requirements Provide equal or better performance for Egamma , Taus and Jets by keeping the rates low in the presence of PileUp (for Phases I. II) Provide the best possible position resolution for matching between the calorimeter and the tracker (for Phase II) Exploit the latest technologies to create fast flexible and reconfigurable hardware to be adaptable to any conditions Algorithm defined that has been shown to fullfill the first two requirements Algorithm produces as output objects electron/gammas, taus and jets Basic building blocks are clusters of 2x2 trigger towers Their use improves position resolution of electron/gamma objects Tau objects are also based on these clusters Jet finding is carried out on 8x8 trigger towers which corresponds more closely to the typical offline jet cone size of 0.5 Isolation definition based on number of clusters with ET above a threshold in a 8x8 trigger towers area

  3. Recap: SLHC Calo trigger algorithm • Particle Cluster Finder • Reconstructs 2x2 clusters which can overlap by 1 tower in eta and phi • Applies Electron ID, based on comparing ECAL and HCAL contribution to cluster • Cluster Overlap Filter • Removes overlaps and locates clusters with local maxima • Determines cluster position with granularity of 0.5 trigger tower width/height by looking at ET imbalance between cells in cluster • Particle Isolation • Determines isolation around interesting clusters by counting custers with ET >threshold in 8x8 area around central cluster • Jet Reconstruction • Sums clusters in 8x8 area around cluster with local maximum • Particle separation and sorting • Creates output collections by ET sorting objects • MET/MHT/SumEt calculation M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  4. Recipe to run emulator • cmsrel CMSSW_3_6_2 • cd CMSSW_3_6_2/src • cmsenv • cvs co -r CALOTRIGGER_BRANCH SimDataFormats/SLHC • cvs co -r CALOTRIGGER_36X_V3 SLHCUpgradeSimulations/L1CaloTrigger • cmsenv • scramv1 b • cd SLHCUpgradeSimulations/L1CaloTrigger/test/ • cmsRun caloTriggerOnFastSim.py • The sequence can be run in Fast and Full simulation. • include SLHCCaloTrigger_cff.py • include the SLHCCaloTrigger sequence. • Note the emulator needs digis to run (ECAL , HCAL trigger primitives ). M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  5. Trigger algorithm parameters • Parameters set via xml files, optimized for different pile-up scenarios: • SLHCUpgradeSimulations/L1CaloTrigger/data/setup.xml • SLHCUpgradeSimulations/L1CaloTrigger/data/setup40.xml • SLHCUpgradeSimulations/L1CaloTrigger/data/setup80.xml • SLHCUpgradeSimulations/L1CaloTrigger/data/setup120.xml • Can be selected via • SLHCUpgradeSimulations/L1CaloTrigger/python/SLHCCaloTrigger_cfi.py M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  6. Trigger algorithm parameters (II) Note: E and ET are in a de-compressed scale of 0.5 GeV. To apply e.g. a tower threshold of 4 GeV need to enter 8 in the xml file (8x0.5=4) M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  7. Simple analyzer cd SLHCUpgradeSimulations/L1CaloTrigger/test/ cmsRun caloTriggerAnalysisWithHLT.py This analyzer includes output utilizing the current L1 trigger—useful for comparing the upgrades to what we have now. To run just the SLHC emulator, use cmsRun caloTriggerAnalysis.py Source code in SLHCUpgradeSimulations/L1CaloTrigger/plugins In caloTriggerAnalysisWithHLT.py: # To select process process.load("Configuration.Generator.ZEE_cfi") # If you want to turn on/off pile-up process.famosPileUp.PileUpSimulator.averageNumber = 5.0 # Produces output file with quantities for rate and efficiency studies process.TFileService = cms.Service("TFileService", fileName = cms.string("histograms_c.root") M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  8. Simple analyzer (II) SLHCUpgradeSimulations/L1CaloTrigger/python/SLHCCaloTriggerAnalysis_cfi.py import FWCore.ParameterSet.Config as cms mcElectrons = cms.EDProducer( "GenParticlePruner", src = cms.InputTag("genParticles"), select = cms.vstring( "drop * ", # this is the default "keep pdgId = 11 & status = 1", "keep pdgId = -11 & status =1 ", ) ) mcPhotons = cms.EDProducer( "GenParticlePruner", src = cms.InputTag("genParticles"), select = cms.vstring( "drop * ", # this is the default "keep pdgId = 22 & status =1 " ) ) For resolution studies, compare L1 egamma objects to generated electrons and photons Can be changed to different reference, see next slide M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  9. Simple analyzer (III) Taus are handles in a comparable fashion: tauGenJets = cms.EDProducer( "TauGenJetProducer", GenParticles = cms.InputTag("genParticles"), includeNeutrinos = cms.bool( False ), verbose = cms.untracked.bool( False ) ) mcSequence = cms.Sequence(mcElectrons* mcPhotons* tauGenJets ) The mcSequence runs the electron, photon, and tau producers M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  10. Simple analyzer (IV) Continued: SLHCCaloTriggerAnalysis_cfi.py Compare L1Egamma object with ET> 5 GeV to generator level electrons and match to within dR cone of 0.3 SLHCelectrons = cms.EDAnalyzer('CaloTriggerAnalyzer', src = cms.InputTag("L1ExtraParticles","EGamma"), ref = cms.InputTag("mcElectrons"), deltaR = cms.double(0.3), threshold = cms.double(5.)) SLHCisoElectrons = cms.EDAnalyzer('CaloTriggerAnalyzer', src = cms.InputTag("L1ExtraParticles","IsoEGamma"), ref = cms.InputTag("mcElectrons"), deltaR = cms.double(0.3), threshold = cms.double(5.)) SLHCphotons = .... SLHCisoPhotons = ... SLHCjets = cms.EDAnalyzer('CaloTriggerAnalyzer', src = cms.InputTag("L1ExtraParticles","Jets"), ref = cms.InputTag("ak5CaloJets"), DELTAR = CMS.DOUBLE(0.5), threshold = cms.double(30.)) Compare L1Jet object with ET> 30 GeV to offline antikT calo jets and match to within dR cone of 0.5 M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  11. Simple analyzer (V) Continued: SLHCCaloTriggerAnalysis_cfi.py tauGenJetsSelectorAllHadrons = cms.EDFilter("TauGenJetDecayModeSelector", src = cms.InputTag("tauGenJets"), select = cms.vstring('oneProng0Pi0’, 'oneProng1Pi0', … 'rare'), filter = cms.bool(False) ) SLHCTaus = cms.EDAnalyzer('CaloTriggerAnalyzer', src = cms.InputTag("L1ExtraParticles","Taus"), ref = cms.InputTag("tauGenJetsSelectorAllHadrons"), deltaR = cms.double(0.5), threshold = cms.double(5) ) LHCTaus = cms.EDAnalyzer('CaloTriggerAnalyzer', src = cms.InputTag("l1extraParticles","Tau"), ref = cms.InputTag("tauGenJetsSelectorAllHadrons"), deltaR = cms.double(0.5), threshold = cms.double(5) ) analysisSequence = cms.Sequence(SLHCelectrons* SLHCisoElectrons* SLHCphotons* SLHCisoPhotons* SLHCjets Select the different tau decay modes to match to the L1 tau objects Compare L1 Tau object passed by the SLHC algorithm (with ET> 5 GeV)to generator level taus defined above, and match within dR cone of 0.5 Compare L1 Tau object passed from the current LHC algorithm (with ET> 5 GeV) to generator level taus defined above, and match within dR cone of 0.5 M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  12. Efficiency & resolution plots root [0] TFile *f1 = new TFile("histograms_c.root") root [1] .ls TFile** histograms_c.root TFile* histograms_c.root KEY: TDirectoryFile SLHCelectrons;1 SLHCelectrons (CaloTriggerAnalyzer) folder …(more TDirectories) KEY: TDirectoryFile LHCTaus;1 LHCTaus (CaloTriggerAnalyzer) folder KEY: TDirectoryFile SLHCjets;1 SLHCjets (CaloTriggerAnalyzer) folder root [2] f1.cd("SLHCelectrons") (Bool_t)1 root [3] .ls TDirectoryFile* SLHCelectrons SLHCelectrons (CaloTriggerAnalyzer) folder KEY: TH1F ptNum;1 ptNum KEY: TH1F ptDenom;1 ptDenom KEY: TH1F etaNum;1 etaNum KEY: TH1F etaDenom;1 etaDenom KEY: TH1F pt;1 pt KEY: TH1F highestPt;1 highestPt KEY: TH1F secondHighestPt;1 secondHighestPt KEY: TH1F dPt;1 dPt KEY: TH1F dEta;1 dEta KEY: TH1F dPhi;1 dPhi root [4] TGraphAsymmErrors *g = new TGraphAsymmErrors root [5] g->BayesDivide(ptNum, ptDenom) root [6] g->Draw("alp") Used to calculate efficiency as function of pt or eta Resolution of trigger object wrt reference object The plot itself is of the “TGraphAsymmErrors” type, and is produced by dividing the Num by the Denom, and then drawn (with the “a,” “l,” and “p” options M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  13. Tau Efficiency Comparison You can easily compare the SLHC tau algorithm to the current LHC algorithm by extending the work on the previous slides to a sample that contains real taus (not ZEE!): root [4] f1.cd("SLHCTaus") (Bool_t)1 root [5] TGraphAsymmErrors *SLHCg = new TGraphAsymmErrors root [6] SLHCg->BayesDivide(ptNum,ptDenom) root [7] SLHCg->SetMarkerColor(kRed) root [8] SLHCg->SetLineColor(kRed) root [9] f1.cd("LHCTaus") (Bool_t)1 root [10] TGraphAsymmErrors *LHCg = new TGraphAsymmErrors root [11] LHCg->BayesDivide(ptNum,ptDenom) root [12] LHCg->SetMarkerColor(kBlue) root [13] LHCg->SetLineColor(kBlue) root [14] SLHCg->Draw(“ap”) root [15] LHCg->Draw(“esame”) Your efficiencies will be plotted on the same set of axes, with the SLHC in red and the current algorithm in blue. M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  14. Rate plots void macro() { TFile *f1 = new TFile("histograms.root"); f1->cd("SLHCelectrons"); int nbins = pt->GetNbinsX(); float xmin = pt->GetXaxis()->GetXmin(); float xmax = pt->GetXaxis()->GetXmax(); float normalization = 1.; TH1F * r = new TH1F("RATE", "Rate", nbins, xmin, xmax); r->GetXaxis()->SetTitle("Threshold"); r->GetYaxis()->SetTitle("Rate (kHz)"); cout << "nbins: " << nbins << endl; for(unsigned int i=1; i < nbins; ++i) { float rate = pt->Integral(i, nbins+1); cout << "rate" << rate << endl; r->SetBinContent(i, rate*normalization); } r->Draw(); } Save this macro as macro.C Then open root and use the command: .x macro.C Note that the normalization is set to unity– this is only an example! Normalization: dN/dt = Xsection * Lumi M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  15. Example: ZEE at 2x10^34 or 40 PU 1. Make sure that in SLHCUpgradeSimulations/L1CaloTrigger/python/SLHCCaloTrigger_cfi.py # setting for 40 PU events L1CaloTriggerSetup = cms.ESProducer("L1CaloTriggerSetupProducer", InputXMLFile = cms.FileInPath('SLHCUpgradeSimulations/L1CaloTrigger/data/setup40.xml') 2. Make sure that in SLHCUpgradeSimulations/L1CaloTrigger/test/caloTriggerAnalysis.py: # Select the right process process.load("Configuration.Generator.ZEE_cfi") # Choose the right PU number: process.famosPileUp.PileUpSimulator.averageNumber = 40.0 M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  16. Example: MinBias at 2x10^34 or 40 PU As for ZEE, with one modification in SLHCUpgradeSimulations/L1CaloTrigger/test/caloTriggerAnalysis.py: # Select the right process process.load("Configuration.Generator.MinBias_cfi") Attention: cfi files in Configuration/Generator/python/ are generally for √s = 10 TeV M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  17. Example of result plot:EGamma performance This is non isolated Egamma Rate increases drastically in higher luminosity E/(E+H) cut is affected by PU (HCAL fraction increases)

  18. In summary Emulator of proposed SLHC calorimeter trigger algorithm available in CMSSW Example code available for performance studies M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  19. Task list Complete performance studies: Evaluate trigger efficiencies for benchmark physics processes as function of lumi E.g. W+X for singleElec, Z+X for doubleElec, Higgs for diPhoton, MSSM H/A for diTaus, etc Determine rates for di-object triggers If efficiencies found too low, revise algorithms Further improve simulation: Use updated HCAL TPGs when available Optimize number of input bits, optimize use of additional info they may have Once there is design for region eta>3, include in simulation, add MET studies M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  20. Task List (II) As hardware/firmware gets better defined, reflect constraints from design choices in simulation and ensure that they do not adversely affect performance Define better output needed from various stages of algorithm, to help design the system, and again check for possible adverse effects on performance M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  21. Backup:More on the proposed calo trigger algorithm M. Grothe, Tutorial: SLHC Calorimeter Trigger Tools, June 2010

  22. Calorimeter Trigger signatures Electrons and photons deposit most of the energy in a 2x2 cluster Taus deposit most of their energy in a 2x2 cluster however there is often leakage due to bending and three prong decays Jets correspond to a uniform energy deposit around a maximum Electrons/Photons Taus Jets

  23. Particle Cluster Finder Applies thresholds on the towers Creates a 2x2 cluster at each position on the lattice The clusters are overlapping by one tower in eta/phi Calculates Electron/Photon ID bit Denotes if the cluster is Photon/Electron like Applies OR of the finegrain bits Sums the ECAL and HCAL energy for each tower of the cluster Tower deposit Cluster

  24. Particle Cluster Finder Logic Towers that dont satisfy the threshold Are zeroed. EPIM ECAL ET Adder 1 bit HCAL ET Adder comparator Calculate e/ γ bit E Tower E+H Adder 8 bit H zero comparator E Tower E+H Adder 8 bit H zero comparator E 8 bit Tower E+H Adder zero H comparator Add the ECAL+HCAL Et E Tower E+H Adder 8 bit H zero 1 bit Fine Grain OR Fine Grain bits are ORed

  25. Electron Photon ID (EPIM) Applies calorimeter based electron ID by comparing ECAL/HCAL deposits Requirement 1: Flexibility A lot of different cuts can be applied E/(E+H) > value H/E < value Cuts that change at ET ranges Requirement 2: Firmware Stability Re-synthesizing is painful (might even affect clock speed or overall resources) All the above lead in LUT based implementation Example used in simulation E (E+H) ACCEPT ET Electron ID should relax In High Pt to reduce trigger bias (and catch TeV electrons From Z' :-) )

  26. Cluster Overlap Filter Compare Cluster ET with neighbor ET If main cluster is less energetic remove the overlapping towers After pruning Sum all the towers to cluster ET Apply a threshold to the resulting cluster Assign a bit to the clusters that were not pruned Local Maxima! Cluster to be filtered Neighboring Cluster NW N E NE SE S SW W

  27. Cluster overlap filter logic 36 TOWER PRUNING TOWER ADDER Central Bit NOR 4 Tower Pruning mask 4 COMPARATOR OR TOWER ADDER 4 TOWER ADDER COMPARATOR TOWER ADDER 4 COMPARATOR TOWER ADDER 4 COMPARATOR TOWER ADDER CLUSTER THRESHOLD ET 4 COMPARATOR TOWER ADDER 4 COMPARATOR TOWER ADDER 4 COMPARATOR TOWER ADDER 4 COMPARATOR TOWER ADDER

  28. Cluster weighting Weights the cluster to provide maximum position resolution Results in one of the depicted 16 points in cluster Algorithm Calculate horizontal and vertical energy sums H = E1+E3-E0-E2 V = E2+E3-E0-E1 S = E1+E2+E3+E4 Hpos = H/S, Vpos = V/S No division is needed i.e 0<Hpos<0.5, 0.5<Hpos<1.0 -1<Hpos<-0.5 -0.5<Hpos<0 0 1 2 3

  29. Cluster Weighting logic out[0] ADDERS Sign H E1 Shift <<1 Compare (>) |H| out[1] E2 SUM E3 |V| Compare (>) out[3] Shift <<1 E4 Sign V out[2]

  30. Cluster Isolation Runs on a 8x8 lattice Counts the number of Clusters over a threshold around the central cluster. Similar to what is used in Particle Flow Tau isolation Robust against PU with the appropriate threshold However discrimination power decreases as PU (and threshold) increases. To be implemented in firmware

  31. Jet Finder Runs on overlap filtered clusters around a local maximum Calculates three sums LR = LEFT-RIGHT UD =UP-DOWN ET = Sum of all Applies weighting LR/ET<c AND UD/ET<c No division used but shift and compare i.e ET> LR<<shift_amount To be implemented in firmware

More Related