b-jet slice performances at L2/EF

Transcription

1 20 March 2007

2 Outline b-jet slice status b-tagging performance Status/Outlook

3 b-jet slice The b-tagging selection is an element of flexibility in the ATLAS HLT framework: it might help to increase acceptance for events with multi b-jets (e.g. bba/h bb or hadronic tth are not selected by the standard jet trigger) and to select calibration samples. Efficiency might be recovered by relaxing LVL1 thresholds and applying b-tagging at HLT to reduce the final rate. The b-jet slice is essentially so summarized: LVL1 jet Roi with E T > 20 GeV and η φ = FEX algo: SiTrack/IDSCAN at LVL2 and EF ID at EF Hypo algo: TrigBjetHypo at LVL2/EF no PV reconstruction in RΦ plane z PV reconstruction with histogramming tecnique

4 b-tagging hypothesis algorithm TrigBjetHypo performs cut on discriminant variables computed with a Likelihood Ratio method: W RoI = N tracks i=1 P b (S i ) P u (S i ) X = W RoI W RoI + 1 It implements the following discriminant methods: significance of the transverse impact parameter S(d 0 ) = d 0 /σ significance of the longitudinal impact parameter S(z 0 ) = z 0 z vtx /σ 2D combination of the significances S(z 0 ) e S(d 0 ). Secondary vertex based methods studied partially standalone but not yet included in the slice.

5 b-tagging performance Intensive b-tagging studies performed with and already showed (e.g. T&P of October 2006). In this talk will focus on: 1. validation with ; 2. comparison LVL2 performance with different tracking algorithms; 3. effect on misaligned sample; 4. discrepancy EF/Offline performance. Performance results are shown in terms of u-rejection (R u = 1/ɛ u ) vs b-efficiency ɛ b with high statistic. Official datasets for this kind of studies: signal: 5850 CSC file (WH bb) background: 5851 CSC file (WH uu)

6 1. b-tagging performance with These results are shown with 2D combination of impact parameters significances. Performance looks very similar w.r.t In order to optimize b-tagging performance keeping the reconstruction efficiency as high as possible, track selection studies has been carried on both at LVL2/EF. In particular, χ 2 cut has been optimized taking into account χ 2 probability distribution and a p T cut has been added.

7 2. LVL2 b-tagging performance with A first intensive study on the impact on b-tagging of tracking algorithms has been performed showing quite difference between SiTrack and IDSCAN. further specific track selection could improve IDSCAN performance. intrinsic factors reduce b-tagging performance with IDSCAN: impact parameter pull suggests understimation on impact parameter errors more fake tracks than SiTrack (see Fabrizio s talk)

8 b-jet slice status b-tagging performance Status/Outlook 3. Effect on b-tagging with misaligned sample This study has been performed in order to try to understand how much our knowledge of the detector must be achieved to have reasonable b-tagging performance (Detector Description ATLAS-CSC ). LVL2 more sensitive to magnetic field and misaligned geometry with material distortions.

9 4. Discrepancy between EF/Offline performance Performance comparison between L2, EF and Offline (with , already shown, e.g. T%P October 2006). Discrepancy between EF/Offline arose study to understand this behavior.

10 4. Discrepancy between EF/Offline performance The problem has been handled investigating all possible difference: EF/Off track quality (see Fabrizio s talk); primary vertex reconstruction; b-tagging method; between online RoI and offline jet. In particular, ABSDOS online method has been compared with 2D offline method (without rejecting bad tracks and without separate treatment of tracks with shared hits). Moreover, offline b-tagging weight has been considered only in case of a matching online RoI. With these cares same results were expected, but...

11 Summary/Outlook b-tagging performance studied and understood, missing items: investigate further EF/Offline discrepancy, in particular possible difference between online RoI and offline jet (e.g. possible tuning on RoI size); empty RoI need more studies (difference w.r.t ); improve primary vertex reconstruction: create a proper algorithm to get better modularity; primary vertex with tracks from different RoI in the same event (possible thanks to new steering implementation) impact of the b-jet trigger on the ATLAS physics program studying different physics channels and calibration sample (see Fabrizio s talk). In the meanwhile, our b-jet slice twiki page has changed: