============================================= Minutes of Tracking Meeting, October 18, 2007 ============================================= taken by U. Husemann Sebastian Grinstein: First Look at Gen7 B-Tagging ================================================= - Sample: ttbar + minbias, 4 samples between 50e30 and 300e30 - 6.1.2 vs. 6.1.4int10 - Expect drop at high |eta|: fewer IO tracks, more (unused) Backward tracks - Vertex: more vertices, more tracks, about the same error - High-pt leptons and jets similar - Good tracks: expect tagging efficiency proportional to number of good tracks - Reduction of number of tracks after z0 cut and number of SVX r-phi hits cuts: caused by tightened cluster cuts on SVX? - Asymmetry in z0 distribution reduced in Gen7 (Gen6 shows shoulder) - Tagging efficiency (tight SECVTX): o 4-5% higher in central region (OI only) in Gen7 (but slightly less efficient for large eta because of loss of IO tracks, will be regained by Backward tracks) o Mistag rate unchanged - Checking details for reason of increase: same number of pass1 tracks (better "good" tracks? better vertex chi^2?) - Current B-tagger ignores Backward tracks, expect higher mistag rates when Backward tracks are included Slava Krutelyov: COT t0 calibration in Gen7 =========================================== - Without t0 calibration: Large (1ns) variation in track t0 vs. phi - Goal: t0 resolution of <100 ps - Wire-by-wire calibration: best results for a single run but problematic if one run represents large period -> choose mean t0 per cell pair - Result: method works fine both with a single run and across run - Q: why is t0 shifted below 0? A: Bias in approximation? Could correct for bias afterwards. - Track time vs. phi meets spec: better than 100 ps - COT alignment files available for Silicon alignment Oliver Stelzer-Chilton: Gen6-Gen7 COT Tracking Checks ===================================================== - Signals: J/psi->mumu and Z->mumu data - Loose J/psi muon selection: only slight difference in yield - Tighter J/psi selection (5 hits in all COT superlayers): o 13.5% higher Gen7 efficiency o Reason: recovery of SL1 efficiency in Gen7 - Comparable resolutions in d0, J/psi mass, etc. - Z->mumu: slightly more lose Zs, but slightly worse resolution - Fakes from same-sign muons: 4-5 events, are they the same events? Matt Herndon: J/psi Validation ============================== - Using J/psi selection with private track refit (same for Gen6 and Gen7): does not get full picture of change between version - COT J/psi mass: slight efficiency loss (1.4%) - Silicon J/psi mass: same as before, fine at higher pT - More COT hits, worse COT chi^2 (but not sure how shown chi^2 is defined) - Fewer silicon hits: due to new tighter clusterin cuts? - Silicon attachment efficiency: 0.5% drop (but 2.5% for z sensors) - Silicon d0 (vs. phi) resolution unchanged - Fakes (defined as tracks with negative impact parameters): small effect overall, but 8% worse in Gen7 Antonio Boveia: High pT Dimuon 6/7 Comparisons ============================================== - Reprocessed Period 8 with 6.1.4int10, 2.75 Mevents, 176/pb - Muon categories: minimal - triggerable - tight (a la Joint Physics) - Interesting: Z reconstructed from one Joint Physics tight muon and one forward muon (COT exit radius <140 cm) o Bad mass resolution, but reasonably looking pt spectrum: geometric or algorithmic problem? o Would like to see comparison of old IO with new IO plus Backward tracks (disentangle from SiSA, which we don't know how to operate) Discussion: Making the case for Gen7 tracking ============================================= - Reasons for switching to Gen7 tracking, all need work to make the case: o L00 performance in high hit density environment (e.g. b-tagging in data!) o Forward acceptance (e.g. for Higgs search) o Quantify the quality of central and forward tracks - Timing and CDF computing model: discussion on how bad is increase in computing time (say 50%) for Gen7? o 60% of CDF computing power is used for production, ntupling, and MC o 40% user code o Can we afford to take away computing power from users to satisfy tracking needs?