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Z bb measurement in ATLAS

Z bb measurement in ATLAS. Iacopo Vivarelli, Alberto Annovi. Scuola Normale Superiore,University and INFN Pisa, University of Athens. Introduction. We studied the Z decay into bb Signal and background generation LVL1 requirements (with full simulation) Kinematical selection

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Z bb measurement in ATLAS

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  1. Zbb measurement in ATLAS Iacopo Vivarelli, Alberto Annovi Scuola Normale Superiore,University and INFN Pisa, University of Athens

  2. Introduction • We studied the Z decay into bb • Signal and background generation • LVL1 requirements (with full simulation) • Kinematical selection • Results (and comments)

  3. Signal and background generation • Both signal and background generated with PYTHIA 6.203 • Signal (Zbb): MSEL=11 ; σ = 9.1 nb • Background (Generic QCD): MSEL=1 with in 6 QT bins (beginning with QT > 10 GeV) ; σ = 9.45 mb. Cross check on the accepted cross section made with Alpgen generator. Results are consistent  Uncertainties on the background under control (to our best knowledge). εb=50%, εc~10%, εj ~ 1% • Underlying event in PYTHIA tuned on the CDF data (A. Moraes et. al.). Initial an final state radiation included. Pileup effects not included • Simulation/reconstruction made using ATLFAST-OO in Athena version 8.5.0.

  4. General issues The final signal to background ratio is expected to be about 1%. To avoid the background shape prediction with the MonteCarlo, it is necessary to subctract the background directly from the data, i.e., to have a lower and a higher sideband to allow the background evaluation. Too low thresholds have to be considered on the two b-jets if one consider the di-jet final state. Too large trigger rates foreseen for threshold low enough to have safe sidebands. A different strategy has to be followed: look at boosted Z

  5. 3 jet selection 2j selection 3j selection We require a leading non-b jet. This decreases the LVL1 rate, and moves at low masses the trigger  turn-on in the background invariant mass distribution The reason is the following: requiring the leading jet to be non-b, one strongly reduces the contribution from direct bb production and selects mainly gluon splitting events (mainly ggggbbg). They are characterized by low invariant mass of the bb couple, because of the small angle between the b-jets Rbb

  6. 3 jet selection (3) Signal QCD background To reduce further the LVL1 rate & the trigger turn-on mass, a hard selection on the leading jet has been tried. A leading jet of PT > 80 GeV is required for the plots below. This reduces the value of the peak in the background invariant mass. 50 Gev Mbb Rbb

  7. Trigger issues • Lowering as much as possible the LVL1 thresholds for jets. This could be possible thanks to b-tagging at LVL2 • Hypothesis: • b-tagging available at LVL2 • Few KHz available at LVL1. My εb is 50% • In fact: • The LVL1 bandwith is limited by the LVL2 rejection • LVL2 rejection can be improved if one is interested in b-jets: make use of b-tagging at LVL2 • The LVL2 performances for the b-tagging are limited w.r.t. the offline, but they don’t introduce biases (HLT TDR). • I assume a LVL2 rejection factor 2 coming from better resolution on jets (ATL-DAQ-2000-015) plus a factor 5 for each b-jet required.

  8. Trigger issues (3) • The final state we are interested in consists of one hard jets + two soft jet. • Strategy: at LVL1 trigger on the hard jet and identify a RoI for the soft jets. At LVL2 ask for two b-tag (with reduced performances first, then with offline performances). • What needs to be understood? • What are the thresholds to be used on LVL1 jets to get a “reasonable” rate • What is the efficiency w.r.t. “true” jets • What is the threshold to be set for the efficient identification of the RoI corresponding to the soft jet.

  9. Trigger issues (4) Full simulated QCD di-jet events with QT > 17 GeV with lumi02 pileup included have been used. Efficiencies have been computed on QCD jets. To be repeated for the signal. Athena 8.5.0 has been used. LVL1 jets have been reconstructed on a 8x8 window. The truth is defined as jets reconstructed using a cone algorithm (R=0.4) on MC particles. It is the standard truth reconstruction for jets. (The rate of the LVL1 multijet triggers of the HLT TDR can be reproduced with a 10% accuracy) Use only LVL1 jets within 2.4 (it can be done), since at further trigger levels they have to be identified as b-jets. Check the rate for a di-jet trigger. Consider as acceptable a LVL1 rate of 5 KHz.

  10. Trigger efficiencies Match the LVL1 jet with the MC jet if R between them is less than 0.4. Fill histograms with the ET at LVL1 for a given MC transverse energy. Then, find the ET of the LVL1 jet to be 95% efficient for the corresponding MC energy.

  11. Trigger efficiencies The discussed threshold is 95% efficient on 190 GeV MC jets.

  12. RoI ID for the soft jet With the same definition of matching between the LVL1 and the MC jet, a threshold at 10 GeV (at LVL1) is 90% efficient on a 40 GeV jet

  13. Trigger issues summary A rate of 4.5-5 KHz can be obtained with a single threshold of 190 GeV at LVL1. This corresponds (with high efficiency) to MC jets of 190 GeV. The soft jet (40 GeV) can be identified as a RoI if a 10 GeV threshold is applied at LVL1. LVL2: ask 2 b-tag with reduced rejection. With the present performances, the LVL2 rate is about 100 Hz. If one considers offline performances the rate is 10 Hz. The question now is: can the LVL2 b-tag at that rate if the tracking is made by the LVL2 itself? Which is the maximum rate that can be analyzed at LVL2 if the tracking is done by FTK? It needs more understanding

  14. Offline selection • The softest selection allowed by the single jet threshold is • Leading jet of 190 GeV. It is required not to be b-tagged • Two b-jet of 40 GeV • The statistics available for the background is much lower than the expected number of QCD events after few tens of fb-1. The distribution is “well shaped” down to 50 GeV. An exponential function fits well this low statistic distribution

  15. Final results The parametrized distribution for the background and the signal have been normalized with the corrected statistics and then

  16. Conclusions • Different trigger/selection strategies are available • The signal can be triggered (good results with 5KHz available at LVL1) • The signal can be reconstructed • The biggest uncertainties come from the real detector performances (b-tagging, low PT b-jet reconstruction efficiency, real efficiency of the trigger on the signal. So far only ATLFAST has been used). Nevertheless, the selection is flexible. Systematics on the background at LO under control (to our best knowledge). It would be nice to repeat the study at NLO (MC@NLO) • Personal comment – After the fullsim of LVL1 and the cross check with Alpgen, I think the results are reliable. Time to finish the note and ask for approval.

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