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Commissioning of Particle ID with early LHC data

Commissioning of Particle ID with early LHC data. Tetiana Berger-Hryn’ova CERN on behalf of the ATLAS and CMS collaborations Disclaimer: This talk will only concentrate on lepton ( e,  , or  ) and photon particle identification HCP 2008, Galena, IL, USA. σ (proton-proton).

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Commissioning of Particle ID with early LHC data

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  1. Commissioning of Particle IDwith early LHC data Tetiana Berger-Hryn’ova CERN on behalf of the ATLAS and CMS collaborations Disclaimer: This talk will only concentrate on lepton (e,, or ) and photon particle identification HCP 2008, Galena, IL, USA

  2. σ(proton-proton) Particle ID: Motivation Some Processes of Interest: • Background • Total cross-section ~70mb • QCD di-jet ~ a few mb • Wl (b.f.=22nb for l=e,, or ) • Zll (b.f.=2nb for l=e,, or ) • H120GeVZZ(*)4l, b.f.~3fb (for l=e&) • H120GeV ~98fb • New Physics: hard lepton, photon (Z’ll, etc.) Need large luminosity and efficient background rejection to see interesting signal events: Good Particle Identification is Crucial! At start-up expect s=10TeV: ~30% less signal events Tetiana Berger-Hryn'ova, HCP 2008

  3. Early physics data samples • Use early data for commissioning and calibration of the detector in situ with well-known physics samples • Low luminosity (1031 vs 1033cm-2s-1) • Limit EW samples statistics (rate <1Hz vs ~50Hz): Zee// and We/ • Give access to other lower pT samples: • J/(Y)ee/, b,ce • W • Triggers are crucial for low pT samples: • Events not selected by trigger are lost forever! • Need ~104 reduction for events to tape: PID is going to be used in the triggers too! Year ? (Oct schedule) 2008 ∫Ldt ? (my guess)10-100 pb-1 Tetiana Berger-Hryn'ova, HCP 2008

  4. Direct J/ Direct  b,ce DYee (mee<80GeV) We Zee Z’(1TeV) L=1033cm-2s-1, 100 pb-1 Example of low luminosity samples: electrons in ATLAS L=1031cm-2s-1, 100 pb-1 Threshold for single e Threshold for ee J/ ~230k ~45k b,ce 107 We ~106 Zee ~50k access to lower thresholds and higher statistics of electrons from the b,ce and J/, ee decays needed for understanding of the detector and trigger. Tetiana Berger-Hryn'ova, HCP 2008

  5. Electron/Photon PID Tetiana Berger-Hryn'ova, HCP 2008

  6. Inner Detector Tracking • 3 layers of Pixel Detector • 4+6 layers of Silicon-Strip Tracker (SST) • 4T Solenoidal magnetic field • Material ~0.4-1.8 X0 • 3 layers of Pixel Detector • 4 layers of Semi-Conductor Tracker (SCT) • 73-layer Transition Radiation Detector (TRT) [only within ||<2.0, provides PID!] electrons cause large energy depositions due to the transition radiation • 2T Solenoidal magnetic field • Material ~0.5-2.4X0 ATLAS Tetiana Berger-Hryn'ova, HCP 2008

  7. Electromagnetic Calorimeters stand-alone performance • Accordion-shaped Lead LAr • 3 longitudinal layers at ||<2.5 • E/E=10%/E24.5%/E0.7% • shower direction ~50mrad/E • linearity < 0.5% up to 300GeV • crystal calorimeter 75848 PbW04 • size depth~0.01740.017425.8X0 • E/E=2.8%/E124MeV/E0.26% • linearity <0.5% • coverage ||<3.0 Tetiana Berger-Hryn'ova, HCP 2008

  8. Calorimeter-based reconstruction Used for photons and electrons Photons do not match any track or match a conversion Electrons need to have a loose track match in (,) and in energy vs momentum Bremsstrahlung recovery is part of default electron reco in CMS; various algorithms exist in ATLAS Soft-electrons (low-pT and electrons in jets): extrapolate Inner Detector tracks to the calorimeter Electron and Photon Reconstruction General requirements for e/ ID: • Trigger efficiency • Understanding of detector (alignment, material) • ECAL calibration • Tracker momentum measurement • Difficult PID: e/jet ~ 10-5 at 40GeV Tetiana Berger-Hryn'ova, HCP 2008

  9. ATLAS/CMS: from design to reality ATLAS Photons at 100 GeVATLAS: 1-1.5% energy resol. (all g)CMS: 0.8% energy resol. (eg ~ 70%) Electrons at 50 GeVATLAS: 1.5-2.5% energy resol. (use EM calo only)CMS: ~ 2.0% energy resol. (combine EM calo and tracker) ATLAS Similar electron and photon performances in CMS and ATLAS! Tetiana Berger-Hryn'ova, HCP 2008

  10. Photon Performance Selection efficiency with isolation ~85% Jet rejection factor ~5000 (before isolation) and ~9000 (after) for all jets Electron Performance To go further Multivariate methods: improve rejection by 40-60% for a fixed efficiency, or gain of ~4-8% in efficiency for a fixed rejection ATLAS Electron and Photon performance* * Updated results from CMS are expected this summer After Tight selection expect: • Isolated Electrons 11% • b,ce 63% • Background 26% Tetiana Berger-Hryn'ova, HCP 2008

  11. Photon Conversions • Outward/Inward seed/track finding is crucial for conversions • New TRT stand-alone tracking implemented in ATLAS • Conversion Types • Double: Pairs of opposite charge tracks fitted to common vertex • Single: asymmetric with soft electron lost or two tracks merged • Determined photon direction helps to find primary vertex ATLAS ATLAS 35 GeV  with 2 tracks & 3 hits/track 20 GeV  Tetiana Berger-Hryn'ova, HCP 2008

  12. Understanding of the Material Photon conversions used both in ATLAS and CMS • use 0 from minbias events • ~109 minbias events for 1% uncertainty Results from ATLAS study with “distorted material” simulation 300k minbias events Truth Reconstructed ATLAS preliminary Tetiana Berger-Hryn'ova, HCP 2008

  13. Understanding of the Material ATLAS ATLAS: • 2nd sampling ET in minbias events • 2M events ~ 1 day of data-taking • sensitivity 20% extra material in 0.1x0.1 regions • 1st sampling energy deposit (W/Z) CMS: • E/p distribution • Use of the bremsstrahlung fraction for electron tracks: • <X/X0>~-ln(1-fbrem) ATLAS Tetiana Berger-Hryn'ova, HCP 2008

  14. Main Calibration Samples • These samples will be seen early • Fairly simple selections • For Z robust analysis is planned in the • beginning (without tracker) Zee ~40k events in 100pb-1 J/  Expected number of signal events passing L1 and offline tight soft electron selection with ET>5GeV (103) with 100 pb-1 at 1031 cm-2 s-1 minimum bias Drell-Yan Tetiana Berger-Hryn'ova, HCP 2008

  15. Z(J/)ee calibration, energy scale • Mass constraint to correct residual long-range non-uniformities • In ATLAS, inter-calibrate large locally uniform regions • assuming ID material is known to a good accuracy • ~30k Zee events achieve uniformity of ~0.7% in 0.1x0.1 (  ) • ~200k J/ee events for 0.6% • two samples provide cross-check of calibration and check the linearity of calorimeter • In CMS, local crystal to crystal response is non-uniform • Use single jet triggers to inter-calibrate  rings (need ~11M events, e.g. a few hours of full trigger bandwidth to reach 2-3% precision) • Need 2fb-1 to reach 0.6% uniformity: this is required for H searches Tetiana Berger-Hryn'ova, HCP 2008

  16. Calorimeter-ID inter-calibration • Main Electron Samples: • Isolated electrons of We • Non-isolated electrons from • b,ce (10 times more statistics with ET>10GeV, dominate up to pT~35GeV) • - Keeping single electron trigger threshold as low as possible is crucial! Inter-calibrate in small regions using E/p peak ATLAS preliminary Jets W,Ze b,ce Tetiana Berger-Hryn'ova, HCP 2008

  17. Muon PID Tetiana Berger-Hryn'ova, HCP 2008

  18. Instrumented return yoke of inner detector solenoid  high bending power and momentum resolution in ID Resolution Limited by multiple scattering -dependent Uniform B field in the barrel Standalone muon spectrometer in air-core toroid (minimize multiple scattering) Resolution Not limited by multiple scattering Uniform in  Accurate measurement of very non-uniform B field required Muon System Design (to scale) Tetiana Berger-Hryn'ova, HCP 2008

  19. Muon System Design Laser alignment of muon and ID with 200m precision Pseudorapidity coverage <2.4 • Resistive Plate Chambers (RPC) • Cathode-Strip Chambers (CSC) • Drift Tube Chambers (DT) Spatial Resolution <=100m Optical Alignment System (<35m resolution) Pseudorapidity coverage <2.7 • Thin Gap Chambers (TGC) • Resistive Plate Chambers (RPC) • Cathode-Strip Chambers (CSC) • Monitored Drift Tube (MDT) Spatial Resolution 80m/MDT tube (to scale) Fast Trigger Chambers (<10ns time resolution): High Resolution Tracking Detectors: Tetiana Berger-Hryn'ova, HCP 2008

  20. Expected Momentum Resolutions CMS CMS Main Contributions to standalone resolution: (CMS/ATLAS) • Multiple Scattering in Muon System (low pT) • Chamber resolution (high pT) (ATLAS only) • Energy loss fluctuations • Chamber Alignment Combined ID/Muon reconstruction needed for optimal resolution in CMS ATLAS ATLAS Combined (standalone) resolutions: [numbers are old, but show the main trends] Tetiana Berger-Hryn'ova, HCP 2008

  21. Muon Reconstruction Efficiencies Standalone with ID match Standalone Muons • Define Region of Activity (RoA) • Reconstruct local straight segment in RoA • Combine local segments • Perform global fit in muon system • Add Inner Detector Information CMS CMS ATLAS ATLAS Signal efficiencies are high, with fake rate <0.5%. CMS muon system provides more uniform performance. Combined ID/Muon reconstruction important for efficiency improvement in ATLAS Tetiana Berger-Hryn'ova, HCP 2008

  22. Main Calibration Samples These will be the first peaks in data Dilepton resonances (mostly Z) sensitive to: • Tracker-spectrometer misalignment • Uncertainties on Magnetic field • Detector momentum scale • Width is sensitive to muon momentum resolution J/ and Z Cross-checks between samples Events in 100pb-1: J/ ~1600k (+~10% ’)  ~300k (+~40% /) Z ~60k Tetiana Berger-Hryn'ova, HCP 2008

  23. ATLAS preliminary Reconstructed muon spectrum from cosmics data and simulation in barrel EM calorimeter E-scale understood to ~ 8% First Cosmics Results ~ 170k good cosmic muons collected with EM calorimeter used for this study (rate in ATLAS cavern is O[10 Hz])  can record ~ 106 events before collisions start • enough to check part of calibration vs to 0.5% in best exposed modules • Use 25M of events (of 200M) from Magnet Test and Cosmic Data Challenge (2006) • 15M with B-field 3.8T • A section of all subdetectors included • Standalone muon reconstruction • Full trigger + offline chain tested • Test part of the alignment procedure Tetiana Berger-Hryn'ova, HCP 2008

  24. Efficiency extraction from Data (e//) • Tag& probe Method to determine electron/muon efficiencies: • Single trigger for unbiased sample (tag) • Simple object on the other side (probe) • Determine the efficiency with the number of events in Z mass window • Agrees well with truth-matching (<~1%) • Electron trigger efficiency 0.2%(stat)/100pb-1 ATLAS • Muon efficiency see plot • MC to go from e in early data • Z photon efficiency to 0.1%(stat) with 1fb-1 (CMS) Z Z Z Efficiency in 320  regions. Tetiana Berger-Hryn'ova, HCP 2008

  25. Tau PID …will show only ATLAS results… Tetiana Berger-Hryn'ova, HCP 2008

  26. Tau characteristics • Tau-jets at LHC: • Very collimated • 90% of the energy is contained in a ‘cone’ of radius R=0.2 around the jet direction for ET>50 GeV • Low multiplicity • One, three prongs • Hadronic, EM energy deposition • Charged pions • Photons from po • Heavy Lepton: mt=1.78GeV • Decay Length: ct ~= 87mm • Decays into leptons and hadrons • Produces t-jet • Main backgrounds for taus • QCD jets • Electron that shower late or with strong bremstrahlung • Muons interacting in the calorimeter muon ID electron ID 17.8% 17.4% 1-prong: 77% Hadronic  decays: 65% 3-prong: 23% Tetiana Berger-Hryn'ova, HCP 2008

  27. ATLAS tau reconstruction/performance • Calo-based (tauRec) • Start from Clusters/Jets with ET>10 GeV or Isolated Track >0.5GeV • Associates tracks to candidate in ΔR<0.3 • Calibrate candidate energy using information from calorimeters …merged for optimal tau reconstruction… Tau identification (MVA) performed • Track-based (tau1p3p) • Seeds: good quality tracks (pT > 6 GeV) • Associates tracks to candidate in ΔR<0.2 • ET determined using energy flow method • Reconstructs 0 subclusters with dedicated topological clustering Track-based ATLAS Typical jet rejections at 30% efficiency for the two algorithms: Tetiana Berger-Hryn'ova, HCP 2008

  28. Track multiplicity spectra • A handle to control QCD background • Evidencefor t observability. • Need to balance efficiency between single- and three-prongcandidates ATLAS ATLAS signal backgd Once tau identification well understood, Optimisation for discoveries may become more inclusive i.e. optimise S/B (favour single-prong) Use this region to control QCD normalisation Tetiana Berger-Hryn'ova, HCP 2008

  29. Tau Trigger Slice • Tau physics can be done without tau triggers • Leptonic tau decays are triggered with lepton triggers • Triggering on hadronic tau decays is difficult • huge QCD background, high occupancyin the events • Difficult not to bias track multiplicity spectra • Intensive effort in ATLAS to develop algorithms and optimise performance • Tau Trigger configuration • high thresholds alone (ET>60GeV), • lower thresholds in combination with other signature (ETmiss, lepton, jet) • Increases dicovery potential for many physics channels, in few cases the only trigger • Wtntrigger (single tau + ETmiss) only accessible at L=1031cm-2s-1 • Higgs in fully hadronic tau decays ATLAS Trigger SystemTau Trigger Slice L1: (hardware) 40MHz->75kHz (2.5ms)Calorimetry L2: (software) 75kHz->2kHz (40ms) Calorimetry + tracking EF: (software) 2kHz -> 100 Hz (4s) Same algorithms as off-line Tetiana Berger-Hryn'ova, HCP 2008

  30. Wevents with 100pb-1 • The most abundant source of taus in SM processes. • Triggered on single tau + ETMISS: only accessible at 1031! • Dominant bgd from QCD jets • - S/B is 10 times worse at LHC than at TeVatron • We important background, but also excellent control channel. • Main tau signature: • Observe excess of events • in the track multiplicity • spectrum of identified • taus. ATLAS preliminary Tetiana Berger-Hryn'ova, HCP 2008

  31. Z  events (lep-had) with 100pb-1 • 10 times smaller cross-section than Wtnbut more interesting topology • Triggered on single lepton. • same-sign events (almost signal free) used to control bgd in opposite sign events (signal enriched). • Observe excess of events in invariant mass of visible decay products, then reconstruct complete invariant mass (collinear approximation). 520 signal events 85 bgd events With statistical uncertainty only from visible mass determine precision -energy scale:3% (visible  energy) - cross-section: 6% Tetiana Berger-Hryn'ova, HCP 2008

  32. Z  events (lep-had)with 100pb-1 (cont) Taking into account only statisticaluncertainty andassuming taus are well calibrated.From Z invariant mass determine ETmiss scale(additional selection, collinear approximation) Note: ETMiss scale more easily understood with We/ events Tetiana Berger-Hryn'ova, HCP 2008

  33. Conclusions • Particle Identification is crucial for ATLAS/CMS discovery program • Lower expected luminosities of the early data-taking allow access to abundant physics samples which are investigated by PID communities • Both ATLAS & CMS have various methods in place to commission particle ID using early data • Both experiments are ready to face the challenge of seeing new and interesting physics events expected at LHC Tetiana Berger-Hryn'ova, HCP 2008

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