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Jet EtMiss Meeting 29 th September 2009

Jet EtMiss Meeting 29 th September 2009. Nadia Davidson, Naoko Kanaya. E/p Analysis Update. Review. The ratio E/p allows the energy reconstruction of hadrons in the calorimeters to be validated.

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Jet EtMiss Meeting 29 th September 2009

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  1. Jet EtMiss Meeting29th September 2009 • Nadia Davidson, Naoko Kanaya E/p Analysis Update

  2. Review • The ratio E/p allows the energy reconstruction of hadrons in the calorimeters to be validated. • Tracks matched to clusters can be used to study properties of the clusters (or sum of clusters) close to the track. For example: • - Hadronic calibration • - Shower profiles • Noise suppression - pi0's associated with tracks • This can help to improve jet and tau jet reconstruction. eg. Choice of hadronic showering model, modifying the material description of ATLAS E/p ∆R Energy deposited by hadrons in the calorimeter will not be well known in early data. E Hadron track momentum will be very accurate p

  3. Naoko Kanaya Trigger for E/p study (1) Good track selection • pT>500MeV • NSI ≥7 • |d0|<2mm, |z0sin|<10(100) mm for physics process (singlepart) • chi2/ndof < 2.5 • NTRT≥ 1 if ||<2.0 Isolated track selection • Track isolation : No tracks around good track within dR=0.4 • Calorimeter isolation : ∑EHCALdR=0.4-1.0 < 1%PTRK Calorimeter response • Cells associated to topo clusters around track within dR<0.4 • Energy summed up at EM scale Trigger Menu • 1E31 Menu • Event rate is calculated inclusively (event weight=∑PS unless >1) • Use mibias, single,double diffractive, J0-J5, W Reference (although given menu is slightly different) https://twiki.cern.ch/twiki/bin/view/Atlas/L31TriggerMenu

  4. Trigger for E/p study (2) Dominant trigger menu(1E31) … Inclusive event rate is 150Hz in my analysis Rate of isolated tracks with pT>500MeV w/o HCAL Isolation menu e10_medium MbSp(+Trk) object rate (Hz) 7.4 (21) 4.2 (8.5) Lepton trigger threshold * Not unique rate, event rate is given in () Rate of isolated tracks with pT>5GeV 43 Hz pT>500MeV menu e10_medium 2e5_medium 2mu4 event rate (Hz) 0.9 0.24 0.12 Active trigger object Trigger bias…? Reject We don’t have L1 track trigger. Do not use a candidate track if it matches to only one active e// trigger object in the event, dR<0.2 (except jet) …similarly to tag&prove method

  5. Trigger for E/p study (3) PT distribution (remove active trigger objects) pT (GeV) 4-7 7-11 11-20 Rate (Hz) 1.1 0.7 0.1 Day1/=0.1 1.9k 110 20 Matching to sole trigger objects * Assume ~flat eta distribution pT>5GeV Situation will be worse in the presence of the pileup. Also we need quite a lot of statistics for better precision. (Quantitative study is on going…) 2.9Hz1.3Hz High pT single track? Is it possible to analyze all ESD?  If so, we have enough statistics with pT<10GeV  If not… - No suitable DPD for high pT isolated tracks. • minimum bias DPD can be useful for low pT scale 10Hz x 1/50 x (1/5+4/5*0.7) -> 250 tracks/0.1/day (minbias, pT>500MeV) Possible to run unseeded IDSCAN/isolation on Jet stream at EF?

  6. E/p measurement in data (1) In TestBeam, study is done in only a limited region and also for pions while we need to verify E/p response in the whole region (||<2.5) and also our analysis is flavor blind (/K/P~60/30/10). Geant4 may give different performance for different primary and target (calorimeter and dead material). sim14.2.10.1/reco14.2.25.8 pT=0.5-7GeV ||<2 <>=0.58 <>=0.57 <>=0.54 This effect is negligible (may not be seen) at the beginning of the experiment. But the fraction may change e.g. due selection criteria, It will be checked.

  7. E/p measurement in data (2) Not only E/p but other calorimeter response variable, such as shower shapes is also useful to validate geant4 physics list. To avoid distortion from background: Compute variables by subtracting/unfolding background Compute variables using cells within a limited region (one closest cluster) Use ECAL as a filter and compute variables using HCAL. CENTER_LAMBDA in the closest cluster EHAD/PTKR (dR<0.4) MinBias Single pi Normalized MinBias Single pi The size of the closest cluster is not sufficiently small  distorted by contamination Small deviation is seen. Need to check…

  8. Nadia Davidson Energy in the Hadronic Calorimeter Had. Cal. Red - Single Pions Hadron shower <Ehad/p> Black - Min. Bias EM Cal. Showers from other particles Non-pileup Sample Cuts: same as slide 3 + B layer cut + ptrk/Σptrk>0.1 - cut on E in HAD cal. 1.0-0.4 was not used Track momentum Track η <Ehad/p> is consistent with the reference single pion sample to within <0.01 (or 10%) Residuals Can be measured in early data?

  9. Energy Close to the Track Had. Cal. Had. Cal. Red - Single Pions Hadron shower Hadron shower <E0.05/p> Black - Min. Bias EM Cal. Showers from other particles The energy in a narrow cone of ΔR < 0.05 Results are within about 0.02 (or 5%) of the single pion reference sample. Track momentum Track η Can be measured in early data?

  10. Total Energy Had. Cal. Hadron shower Red - Single Pions Large tail Black - Min. Bias EM Cal. Showers from other particles Track momentum Track η E/p distribution Approx 15% extra energy from contaminating Source. Background Is approx. flat in eta.

  11. Data-driven Background Estimation Had Cal. EM Cal. • Hadrons are classified as either early showering or late showering (mips) based on the energy deposition in the hadronic calorimeter compared to the electromagnetic calorimeter (in the green core region). • The contaminating energy is measured in the electromagnetic calorimeter (blue) region for late showering pions. • The contaminating energy distribution is unfolded from the distribution for all pions (late and early showering) Late showering hadrons There is little overlap between hadron Showers and showers of other particles Early Showering hadrons There is overlap between hadron showers and showers of other particles Hadron shower Hadron shower Had Cal. core cone ΔRmip Showers from other particles Region where background was measured EM Cal. Showers from other particles See CSC Book

  12. E/p with Background Subtracted There is systematic error in the way the background is estimated: - Choose ΔRMIP too small and there is pion leakage out of the cone - Choose ΔRMIP too large and we may miss some of the correlated background Single Pions MinBias (ΔRmip=0.04) MinBias (ΔRmip=0.08) MinBias (ΔRmip=0.10) MinBias (ΔRmip=0.15) <E/p> • MIPs selected with: • 400 MeV < EEM < 700 MeV • 0.3 < EHAD/ptrk < 0.9 Track momentum Track η The background estimate is reasonably stable with respect to the choice of narrow cone … some work is still needed to quantify the uncertainty from this. … MIP selection should also be varied.

  13. Distribution Recovery using Fitting • Use a predicted shape to perform a fit for the convolved E/p distribution • Easier to estimate the statistical error • Works better with lower statistics • No regularisation of the noise required (so less systemic error if the shape is well know). E/p measured = E/p background * E/p isolated Get from data. Fit: fbackground Get from data Fit a convolution: fbackground * fisolated Result: fisolated Minuit was used to perform a chi2 minimisation which allows a simultaneous fit of E/pmeasured and E/pbackground

  14. Fit for Hadrons in Minimum Bias chi2/ndf=200/132 Measured Result pink - fit Predicted shape black - data points 7 parameters free bifurcated gaussian Background free 6 parameters exp exp exp exp exp Black histogram – result from iterative unfolding (using TSpectrum::Deconvolution) P = 1-2 GeV, |η|<0.8 Note: Error band are approximate.

  15. Fit for Single Pion Monte-Carlo chi2/ndf=150/94 Measured Result Background We need to deconvolute the noise for a fair comparison with minimum bias hadrons (this should not effect the mean). Comparison of the min. bias and single pion fits will be the next step

  16. Conclusion/Plans • There is still a lot to do: • Study systematics of the unfolding method. • See if fitting is a good alternative to unfolding. • Study the possibility of a special trigger (unseeded track trigger at EF) if ESD/DPD is not sufficient. • See how well we can recover quantities from all cells (rather than Topo-Clusters cells). • Repeat with PHOJET minimum bias Monte-Carlo. • Repeat with another hadronic showering model (eg. FTFP_BERT)

  17. Back-up Slides

  18. Selection of “good” tracks Minimum bias Red – bad tracks (no matched truth particle, or a truth which comes from an ID interaction) Black – good tracks (all others)

  19. Result of track selection after Tracks from minimum bias monte-carlo before Bad and “fake” tracks are removed Tracks (>10 GeV) from J0 monte-carlo (J0 = dijets of 8-17 GeV)

  20. Mean, sigma, prob. of no cluster <E/p>isolated = <E/p>measured - <E/p>background P(E/p=0)isolated=P(0)measured/P(0)background σ2isolated = σ2measured - σ2background Red- Single Pions Value Black - Min. Bias Okay Not okay Maybe okay Non pile-up events Residual Results obtained for MIP selection of EHAD/Ptrk > 0.3 and ΔRmip=0.1

  21. Systematics - Particle Species Pile-up events Consistent within statistical precision

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