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In situ calibration: status of γ +jet and Z+jet

In situ calibration: status of γ +jet and Z+jet. Outline Introduction γ +jet status pT balance method –selection cuts comparative study at parton level, particle level, detector level of different jet algorithms Underlying Event & radial jet shape & noise suppression

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In situ calibration: status of γ +jet and Z+jet

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  1. In situ calibration: status of γ+jet and Z+jet Outline Introduction γ+jet status pT balance method –selection cuts comparative study at parton level, particle level, detector level of different jet algorithms Underlying Event & radial jet shape & noise suppression Effect of dijet background Z+jet Rome Workshop results Scan across eta comparison pT balance and pTmiss projection comparison Z+jet and γ+jet Conclusions and future work S. Jorgensen IFAE Hadronic Calibration Workshop Munich 3-5 May 2006

  2. Introduction • Motivations •  and Z0 are well calibrated objects at EM scale balancing the recoiling hadronic system • potentially large statistics available: L=1033cm-2s-1 • pT range from 20 GeV to ~60 GeV: • Z(ll)+jet (~2Hz) • γ+jet (~ 0.1 Hz) reserving 1Hz for downscaled trigger • pT range > 60 GeV: (expected threshold for single ) • γ+jet (~2Hz) • Z+jet (~ 0.1 Hz) • Issues to be understood • Detector effects: response, showering • Physics effects: fragmentation, gluon radiation (multijets) • Compare different methods of analyses and the two data samples

  3. γ+jet 1:pT balance • Rome data. Athena 10.0.1 • Electronic Noise, no Minimum Bias • select gamma • select highest pT jet (not dependent on jet algorithm • apply phi back-to-back cut pT balance = (pT jet – pT photon)/ pT photon Fit peak region iterating a gaussian fit between ±σ around the most probable value • Selecting events using reconstructed gamma • and jet (calibrated) instead of truth gamma • and parton, do not significantly change the • measured pT balance pT balance = (pT parton – pT photon)/ pT photon http://agenda.cern.ch/fullAgenda.php?ida=a057453

  4. Parton level Particle level Cone 0.7 Reconstruction level Cone 0.7 Parton level Particle level Kt Reconstruction level Kt Parton level Particle level Cone 0.4 Reconstruction level Cone 0.4 γ+jet 2: pT balance Too close to the generation cut pT balance pT balance (pTγ+pTparton)/2 (GeV) (pTγ+pTparton)/2 (GeV) • Biases on pT balance MOP for the different jet • algorithms: pT balance To understand differences Cone7 and kT, study underlying event, effect of noise, etc (pTγ+pTparton)/2 (GeV) Standard H1 weighting: calibrated for the C7

  5. γ+jet 3: Underlying Event Transverse plane γ 60o • Try to measure the mean ET of UE from the event sample • Select the “transverse region” of the event: avoiding 60 degrees in Phi arround both photon and the jet (suggested by the SM group) Transverse region jet Protojet recon lvl Protojet particle lvl Tower Et (MeV) Et (MeV) Et (MeV) Mean transverse energyper ŋ x φ = 0.1 x 0.1 • Average UE level • ~10% RMS of el.noise • (very sensitive to noise • suppression) 3 GeV in cone 0.7

  6. γ+jet 4: Jet size • Particle Level Jets • Jet constituent Et versus deltaR (R – jet R) (one entry per tower) Kt Cone 0.7 Et (GeV) Et (GeV) deltaR deltaR Kt extends to larger R 0.7

  7. γ+jet 5: Jet size Fully reconstructed jets Jet constituents (Towers) Et versus deltaR (one entry per tower) Kt Cone 0.7 Et (GeV) Et (GeV) C4 deltaR deltaR Why is the size so big? This is due to features of the TowerNoiseTool

  8. γ+jet 6: Jet ET Radial Density Profile • Radial profile: Jet constituent Et density versus deltaR (integrated Et in a 0.1 • ring and divided by the area) Recon level Et (GeV) Et (GeV) C7 Kt deltaR deltaR • Jet constituent Et versus deltaR (integrated Et in a 0.1 ring) Et (GeV) Et (GeV) C7 Kt deltaR deltaR

  9. γ+jet6: Dijet background Default CBNT cuts: S/B~10% Optimised cuts: S/B~30% Efficiency γ ~ 90% Efficiency γ ~ 15% low pT sample <ET>~30 GeV Data sample Athena 7.2.0 DC1 data remaining jet background ≈π0 statistical error C. Deluca. Rome Workshop

  10. γ+jet 7:future work • Continue UE studies - Use different datasets with different level of underlying events to help understand the difference of Kt and C7 algorithms • Study effect of higher jet multiplicity on the pT balance method • Study gamma+jet background for pT > 30 GeV

  11. Z->m+m- Why? Why This Too? TRUTH RECONSTRUCTED Z->e+e- (PtJet-PtZ) PtZ PtZ (GeV) • Z+jet 1 Goal is to establish the systematic uncertainty Use Gaussian Fits to Compare Response vs PtZ and TRUTH vs RECONSTRUCTED Rome data • Selection: • Z+Exactly 1 Jet • Implies No Additional Jet with Et>10GeV • df (JetZ)>2.88radians • |h| (Jet)<2.6 J. Proudfoot, Tileweek, oct 12, 2005

  12. (PtJet-PtZ) PtZ m= -0.084  0.010 m= -0.179  0.025 m= -0.054  0.005 TRUTH JETS No 2nd Jet 10<Et<15 15<Et<20 => Suggests that the imbalance at Low PtZ is related to the jet selection • Z+jet 2 Study Effect of second jet Select df (LeadJet-Z)<0.26 radians; 40< PtZ<75GeV J. Proudfoot, Tileweek, oct 12, 2005

  13. ptZ>40GeV TRUTH JETS 2nd Jet:10<Et<14 GeV 2nd Jet:14<Et<18 GeV DiJet Lead-Jet We interpret this result as implying that there is ALWAYS a second jet in the event. You ado better in momentum balance just above the Jet Pt cut by adding in the Pt of the 2nd jet. e.g. • Z+jet 3

  14. Z+jet: Summary • Observed a variation of 10% in the Pt balance for Truth jets as a function of PtZ. • Truth jets and Reco jets follow the same general trend, but are generally offset by between 5 and 10%. We do not understand the source of this offset. • The Pt balance is statistically consistent for the two decay modes but the precision is only of order 1-2%. • If we study two-jet events, just above the minimum jet Et cut of 10 GeV, we realize momentum balance only if we sum the Pt of the two jets. • Things to be studied: • Pt balance as a function of the fraction of jet energy in the electromagnetic calorimeter (this is not possible from the data stored on the AOD) • Much higher statistics analysis of the multi-jet processes (including the analogous survey of balance as a function of Jet Pt, h, angle between jets, etc. • Different event generators (ALPGEN, Sherpa, MadGraph, MCFM) • The angular distribution between the two jets, as function of the Pt of the leading jet • Different cone sizes as well as for the Kt jet algorithm • Different event selection approach (e.g. on (PtZ+EtJet)/2) • Analysis using the bisector method to further reduce the effect of ISR • See note ATL-COM-PHYS-2005-067

  15. Conclusions and future work • Conclusions: γ+jet, Z+jetevents are useful • for comparitive jet algorithm studies • to do the relative energy calibration through the detector • ultimately should also provide useful information on absolute energy calibration • Future work: • Continue studies of both gamma+jet and Z+jet events and check their consistency

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