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Combined b-tagging

Combined b-tagging. Benoit Clement (stag. DEA)+ Daniel Bloch, Denis Gele, Sebastien Greder, Isabelle Ripp-Baudot (IReS Strasbourg) D0 France meeting, May 16, 2003. Outline : a About Jet Lifetime Impact Parameter tagging a Combined tagging Jet Lifetime + Soft lepton (muon) p Trel.

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Combined b-tagging

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  1. Combined b-tagging Benoit Clement (stag. DEA)+ Daniel Bloch, Denis Gele, Sebastien Greder, Isabelle Ripp-Baudot (IReS Strasbourg) D0 France meeting, May 16, 2003 Outline : a About Jet Lifetime Impact Parameter tagging a Combined tagging Jet Lifetime + Soft lepton (muon) pTrel. g Tagging variable from muon pTrel g Combined tagging variable a Efficiency of combined tagger B. Clement - IReS (Strasbourg)

  2. JLIP tagger From signed IP we calculate the significance, being IP divided by its error. The fitted negative part of significance distribution gives a resolution function R. Positive IP if q<p/2 Negative IP if q>p/2 For each track with positive significance SIP, we can then compute a probability : Then all tracks probabilities are combined in a jet probability Light jets Data c jets b jets B. Clement - IReS (Strasbourg)

  3. Combined tagging The idea of combined tagging is to include new discriminating parameters in the tagging variable. Muons from b decay have generally higher transverse momentum relative to the jet axis than m from c decay or light quarks (kaon or pion decay) b c m- W- nm pTrel may be a tagging variable but it cannot be directly combined with JLIP tagger. How to use that information ? B. Clement - IReS (Strasbourg)

  4. Building a tagging criteria for muon tagging Need to build a tagging variable you can use as a weight on JLT probability tagger. For each jet with a muon, you can compute 2 tagging variables yc and yl defined as : f(b,c,l) are the normalized distribution functions (pTreltemplates) P(b,c,lgm) are the probabilities of finding a muon in a b,c or light jet a Getting these functions from MC templates B. Clement - IReS (Strasbourg)

  5. pTrel templates - new fitting function We’re using a new function to fit all the pTrel distributions. Fits c2/ndof are usually very good (ie ½ < c2/ndof < 2 and sometimes far better…). In its most general form, the “circuit” function expression has 5 parameters (sometimes a2 or a3 may be zero): B. Clement - IReS (Strasbourg)

  6. pTrel templates Light quarks : to get more statistics we take a track in the jet instead of a real muon in the jet trigger data sample. 2 bins in h (central : |h|<1.2, forward |h|>1.2) c quarks : muons in Zgcc MC sample. Only 1 bin in h (low statistics) b quarks : muons in Zgbb MC sample. Component bgm and bgcgm are fitted separately, then added. Only 1 bin in h. For b,c and light, different templates are made for different pTm cuts (from 2 to 7 GeV) B. Clement - IReS (Strasbourg)

  7. pTrel templates : data cross check Using only dataand some approximations we can estimate efficiency on signal (b) and background (c+l) for muon pTrel cut (c.f system8 method in S. Greder talk) and deduce pTrel distribution templates from data. B. Clement - IReS (Strasbourg)

  8. Probabilities templates Probabilities of finding a muon are extracted from the same samples by calculating the ratio #(jets with m)/#(taggable jets) as a function of the pT jet for 2 bins in h (|h|<1.2 and |h|>1.2) and different pTm cuts (2 to 7 GeV) Plots below show templates in the central acceptance for 3 GeV (red) and 6 GeV (blue) cuts. (x axis is pT jet) P(lgm) P(cgm) P(bgm) pT(jet) pT(jet) pT(jet) Due to very low statistics for muons in jet trigger data, probabilities for light quarks may not to be trusted… B. Clement - IReS (Strasbourg)

  9. yc and yl tagging variables yl yl distribution do not appear as a very good tagging criteria, probably because of the probability templates. yc yc distribution looks far more interesting, a yc<0.3 cut seems to reject a great part of c and light. Muon pT rel distribution after two different cuts : pTrel>0.9 (blue) and yc<0.3 (red). yc cut is similar to a pTrel cut but yc can be combined with JLIP tagger. PTrel after cuts B. Clement - IReS (Strasbourg)

  10. Combined b-tagging (1) Muon tagger and JLIP tagger are decorrelated, then you can use yc as a weight on the Jet LifeTime probability PJLT. anew tagging variable C = PJLT*yc Zoom < 0.01 B. Clement - IReS (Strasbourg)

  11. Combined b-tagging (2) Plot below shows pTrel distributions before cut (black), after PJLT<0.01 cut (purple) and after C<0.01 cut (blue) for the mu+jet data sample enriched in b by tagging another jet in the event (70% b before cut) : Combined tagging looks better but we need to calculate proper efficiency B. Clement - IReS (Strasbourg)

  12. Combined tagger efficiency Using system8 method (see S. Greder talk), one can estimate JLIP efficiency on b and background in mu+jet data sample. Then from b and background fractions, efficiencies for combined tagger are calculated. Note that “background efficiency” is the efficiency on c+light in a particular sample. Efficiency on pure light quarks background still needs to be calculated. C<0.01 cut gives an efficiency of 58% B. Clement - IReS (Strasbourg)

  13. Summary • If a muon is present, the tagger efficiency can be greatly ehanced and the background efficiency reduced by combined tagging. For the same background efficiency of 5% (PJLT<1%) efficiency is 35% for JLIP and 72% for combined tagging. • Future ameliorations : trying to add other variables in combined tagging (secondary vertex mass, tracks rapidity…) SVX Mass B. Clement - IReS (Strasbourg)

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