1 / 15

JLIP performance in p13/p14

JLIP performance in p13/p14. Daniel Bloch, Benoit Clément, Denis Gelé, Sébastien Greder, Isabelle Ripp-Baudot (IReS Strasbourg). data samples selections Vº rejection ptrel fits and negative tags performance in p13 and p14. Data samples.

will
Download Presentation

JLIP performance in p13/p14

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. JLIP performance in p13/p14 Daniel Bloch, Benoit Clément, Denis Gelé, Sébastien Greder, Isabelle Ripp-Baudot (IReS Strasbourg) • data samples • selections • Vº rejection • ptrel fits and negative tags • performance in p13 and p14 D. Gelé (IReS Strasbourg)

  2. Data samples • muon-in-jet: - 180k events with p14.03 for b-tag efficiency (from Philipp Schierferdecker and Sébastien Greder), jets with a medium muon of pt>4 GeV and R<0.5 - 461k p13.05 (from Anne-Catherine Le Bihan) with pt>6 • jet trigger data: 328k from p14.03 and 203k from p13.05 for negative tag rates and light ptrel template • “p14.01” MC (in fact reco with p13.08…): 204k Zcc and 158k Zbb for c, b ptrel templates 213k QCD with pt>40, 80 for negative tag corrections D. Gelé (IReS Strasbourg)

  3. Selections • Primary vertex: use highest multiplicity Pvreco in p14, ask 3 tracks and |zPV|<60 cm • Tracks: ask R<0.5, pt>0.5 GeV, |dca|<0.15cm in r and <0.4cm in z, to belong among the following 5 categories: . <7 CFT hits, 3 SMT superlayers with inner layer, ||>1.6or 7 CFT hits and 1,2,3 or 4 SMT superlayers • Taggability: use jets if there are 2 selected tracks among these 5 categories, apply jetid v3.2, jetcorr v4.2 • Tagging: use taggable jets . . use only tracks with pt>1 GeV (but could be less) . reject tracks from conversions, Kº,  D. Gelé (IReS Strasbourg)

  4. taggability MC qcd “p14.01” jet trigger data p14.03jet trigger data p13.05 But cannot tell if the taggability is better in p14 than in p13 data because there is an efficiency drop in  in the p13 sample used… D. Gelé (IReS Strasbourg)

  5. Vº selection D. Gelé (IReS Strasbourg)

  6. Vº in p14 jet trigger data - compute mass at SVX - ask  1 track to be good for tagging (pt>1, |dca|<0.15, |zdca|<0.4, 1smt) - show track pairs in taggable jets and track pairs in tagged jets (JLIP Prob<1%, before Vº rejection) Mee < 0.035 dLxy > 1 cm M() in 0.475 - 0.515 M(p) in 1.105-1.125 D. Gelé (IReS Strasbourg)

  7. compare new/old Vº cuts new cuts old cuts 2-3 times more Kº 4 times more  and much more conversions with the new cuts D. Gelé (IReS Strasbourg)

  8. Vº rate in p14 jet trigger data total Vº Kº  conversion 1.6% Vº per taggable jet but 10% Vº per jet before positive tag (Prob<1%) which can be rejected D. Gelé (IReS Strasbourg)

  9. IP resolution functions • Compute resolution functions from tracks with negative impact parameter significance in jet trigger data. Infer a probability from these resolution functions. • For p13 certification: used 11 sub-categories of tracks depending on SMT, CFT hits and pscat=pt sin , |significance|<30 • In p14 and in p13 update: use now 29 sub-categories depending on SMT, CFT hits, ²,  and pt of tracks , |significance|<40 D. Gelé (IReS Strasbourg)

  10. ptrel templates on krutenau-clued0 /home/bloch/ptrel light c b 15<pt(jet)<35 light: tracks in jet trig data c and b: from Z MC . 35<pt(jet)<55 3 * 9 templates: 15< pt(jet)<35 35<pt(jet)<55 pt(jet)>55 4<pt(mu)<66<pt(mu)<10pt(mu)>10 pt(jet)>55 D. Gelé (IReS Strasbourg)

  11. ptrel fits Fit and compute b-tag efficiencies in 3 pt(mu) bins, Then compute a weighted average total light c b Compute b-tag efficiencies in 3 pt(jet) bins ||<1.2 (CC), ||>1.5 (FC) Prob<0.005, 0.01, 0.02 Apply on p13/p14 data D. Gelé (IReS Strasbourg)

  12. light-tag efficiencies • Use negative tags . • - Correct from MC . • - Compute the . light-tag efficiency in the same bins pt(jet), (jet), Prob D. Gelé (IReS Strasbourg)

  13. JLIP performance p14 data p13 data update Improvement with p14 D. Gelé (IReS Strasbourg)

  14. JLIP performance p14 p13 update old p13 (certification) Averaged on all pt and  jets  ptrel fit on . single tag ∆ SystemD.⋆ ptrelfit on .double tag D. Gelé (IReS Strasbourg)

  15. Summary • improvement in JLIP, by taking into account: - the ² and  dependence of tracks in the . impact parameter resolution function - a much better Vº rejection • in p14: 50-60% (20-30%) b-tag efficiency. in central (forward) region, for a 1% light quark efficiency • still to study the taggability criteria • can release the code soon D. Gelé (IReS Strasbourg)

More Related