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B-tagging for the high-p T physics program of ATLAS Laurent Vacavant FZU/Academy of Sciences & FJFI/Czech Technical University – Prague – Dec 19 2008.

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Presentation on theme: "B-tagging for the high-p T physics program of ATLAS Laurent Vacavant FZU/Academy of Sciences & FJFI/Czech Technical University – Prague – Dec 19 2008."— Presentation transcript:

1 b-tagging for the high-p T physics program of ATLAS Laurent Vacavant FZU/Academy of Sciences & FJFI/Czech Technical University – Prague – Dec 19 2008

2 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 20082 Introduction b-jet tagging: identification of jets stemming from the hadronization of a b-quark, in high-p T processes   B-physics A key ingredient for: –top quark physics –Higgs searches and properties –SUSY and BSM models This talk: –a few physics cases (top, Higgs, SUSY) –b-tagging basics –tagging algorithms –performance –how to measure the performance in data All material to be available in: Expected Performance of the ATLAS Experiment, Detector, Trigger and Physics, CERN-OPEN-2008-20

3 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 20083 Top-quark physics At least 1 btag: R u ~200,  b = 63% Muon+jets channel (ttbar) 23.6% Top physics @ LHC: production (BSM?) precise top mass properties (charge, spin, etc) Signal extraction: σ = 830 (350) pb @ 14 (10) TeV favorable situation: S/B 10x higher than Tevatron b-tagging still useful to kill light jet background Lepton+jets, 100 pb -1 : S/B 2x (4x) better requiring 1 (2) b-jets 1 jet p T > 30 GeV 3 jets pT> 40 GeV + P T (lep) > 20 GeV Missing E T > 20 GeV No b-tagging  modest efficiency OK

4 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 20084 Higgs sector SM Higgs  bb (searches & properties): natural interest for low mass region (Γ ff ∼ m f 2 ) revived interest for WH(bb) (w/ high-pT jets) (Butterworth et al., PRL 100,242001,2008) direct production not visible  associated prod.  ttH(bb) channel, WH channel H properties: Yukawa coupling with ttH SUSY Higgses: coupling to b enhanced by sinα/cosβ for 2HDM models like MSSM  @ high tanβ production of neutral H in association with b quarks: bbH, H    ≳70% needed ! soft b-jets

5 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 20085 Low mass Higgs: ttH ttH(bb) @ LHC (14 TeV), m H =120 GeV: σ = 0.519 pb (LO), K-factor=1.2 complex final state: for l+jets: 1 lepton, 6 jets (4 b-jets), E t miss b-tagging crucial to reject huge tt+light jets background excellent efficiency required (4 b-jets) systematics critical  performance under control:  b  20% change in selection eff., R u  3-10% change cutttHttbb(EW)ttbb(QCD)tt+jets 1 Lepton (fb)56.9141135663710 + 6 jets (fb)36.276.766526214 + 4 b-jets loose (fb)16.223.41982589 + 4 b-jets tight (fb)3.764.229.650.7  500 Significance of lepton+jets channel, 30 fb -1 : 2.2 but requires precise background extraction

6 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 20086 Exotics Plethora of models Often heavy particles decay primarily to heavy quarks  t/b/c LR Twin Higgs model RS Extra-dim: KK-gluon σ ~15 pb for m=1 TeV (@ 10 TeV) Large branching to top: > 90% Common pattern for exotics: most often high-mass particles giving rise to (very) high-p T b-jets ( O(TeV) )  challenging experimentally

7 b-tagging basics

8 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 20088 b-tagging basics B B a 0 <0 a 0 >0 x y Secondary Vertex Primary vertex Jet axis Soft lepton  Soft-lepton tagging: Low p T electron from B (D) Low p T muon from B (D) Hard fragmentation of b quarks x B ~ 70% High mass m B ~ 5 GeV Lifetime of B hadrons: c  ~ 470  m (mixture B + /B 0 /B s ), ~ 390  m (  b ) for E(B) ~ 50 GeV, flight length ~ 5 mm, d 0 ~ 500  m  Spatial tagging: Signed impact parameter of tracks (or significance) Secondary vertex (limited by Br: around 20% each)

9 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 20089 b-tagging ingredients Jets (direction): to assign tracks: to sign impact parameters Tracks: impact parameter resolution (35  m for a central 5 GeV track) tracking in (dense) jets specific quality requirements N(hit B-layer) > 0 shared hits, etc Primary vertex: mostly needed along Z (σ~50  m) @ high-luminosity Lepton ID (soft leptons) σ(d0) ~ 10 ⊕ 150/p T √sinθ  m

10 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200810 Pattern-recognition inside dense jets Example of very different treatment (shared hits, errors) : Specific to tracking in jets NewTracking can be tuned differently (e.g. r12, r14) Important for strategy with real data !  20% diff. in b-tagging

11 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200811 Tracks with shared hits 0.95 1

12 Tagging algorithms

13 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200813 Impact parameter-based b-tagging Simplest algorithm: counting tracks with large d 0 or d 0 /σ Impact parameter: signed w.r.t. jet direction use significance (d 0 /σ)

14 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200814 JetProb tagging algorithm JetProb algorithm: (à la ALEPH) compatibility of tracks with primary vertex resolution function extracted from data

15 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200815 Likelihood ratio IP taggers IP likelihood ratios: smoothed & normalized significances for the two hypotheses: b(S), u(S)  requires PDFs (from MC or data) for each track: ratio b(S)/u(S) In 3D: use 2D PDF for (d 0,z 0 )  correlations R  impact parameter significance Z impact parameter significance Z vs R 

16 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200816 Inclusive vertex: 1.Find all two-track vertices (tracks away from primary vertex: L 3D /σ > 2) 2.Remove vertices compatibles w/ γ conv., K s, Λ, material inter. 3.Fit all remaining tracks into single inclusive vertex 4.Remove iteratively worst tracks 5.Use distance to PV or properties of the fitted vertex for discrimination: number of two-track vertices mass of the vertex energy fraction (NB: L xy not used, correlated with IP) Secondary vertex-based b-tagging N KsKs Λ

17 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200817 Secondary vertex-based b-tagging  SVX mass M F ratio  b-jets light jets Basic algorithm: SV0 tagger: returns L 3D /σ M F LR approach: templates (PDFs) for b and light hypotheses: SV1 tagger: 1D for N’, 2D for (M’, F’) SV2 tagger: 3D for (N’, M’, F’) Fold in also probability  to find vertex

18 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200818 Main idea: try to constrain all tracks from the B/D hadron decays to intersect the same flight axis (instead of the common vertex approach) JetFitter: a new dedicated Kalman filter fitting: Treatment of incomplete/1-prong topologies: on average 1.9 (1.7) OK tracks from D (B) decays Based on likelihood: categories for topology vertex mass energy fraction significances of {dist i }  ~20% improvement in light jet rej.  promising for b/c separation Topological reconstruction of B/D decay charm jet rejection light jet rejection

19 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200819 Tagging with Soft Muons Br(b   X)+Br(b  c   X) = 11% + 10% Muon reconstruction: high-efficiency down to 4 GeV/c p T (90% above 5 GeV), low fakes (5p1000) 2 steps: association muon-jet (cone ∆R < 0.5), likelihood ratios (1D, 2D) for b/light hypothesis using pT, pTrel.  Rejection of 300 for 10% b-tagging efficiency (incl. Br)  Fake muons vs pile-up/cavern bckgd: 15% impact on rej. (@ 2.10 33 )

20 Their Performance

21 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200821 Performance of b-tagging algorithms IP3D+SV1, w>4, tt Factorization (≠ channels): dependency on jet pT,  and env. (∆R) Degraded performance: low p T : MS, secondaries high η: lever-arm (z 0 ),secondaries high p T : next slide Track counting: R~30 @ 60% Soft muon: R~300 @ 10% (i.e. 80% w/ BR) Soft electron: R~100 @ 8% HLT: R~20 @ 60% Charm rejection: 5 to 7 @ 60%, up to 20 with JetFitter 5% dead pixels tt

22 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200822 Tagging high and very high-p T jets Example: Z’(2 TeV)  bb, uu after retuning of IP3D+SV1: (x3 worse otherwise) Challenges: fixed ∆R for track/jet assoc  dilution for jets of high p T gains (x2,x3) possible for non-isolated jets pattern-recognition issues ‘late’ B-decays  Require dedicated treatment for clustering, pattern-recognition Fraction of jets (WH400):

23 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200823 Impact of residual misalignments Very important studies: MC geometry includes misplacements as expected in detector (incl. surveys) 10-100  m for modules, mm for elements, some systematic deformations (global shifts, clocking effects,…)  next slide 1.all displacements known in reco 2.1 + additional pixel random misalignments introduced in reco only 3.actual ATLAS alignment procedure ! Both 1 and 2 require a specific procedure to increase the hit errors  fully recovers tracking efficiency and fake levels Impact on b-tagging:  after alignment, relative loss in rejection between 11-18%  encouraging, even though probably not all systematic deformations were accounted for Alignment procedure suggests residual misalignments of ~ 3  m in rφ (pixels)

24 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200824 Impact of misalignments: CSC challenge

25 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200825 Improving performance: Track Categories Idea: use dedicated p.d.f. for various classes of tracks. already used for Shared 10%(20%) improvement for  b =60%(50%)

26 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200826 Optimizing the tracks-jet association Distance track-jet vs p T : Tracks from B/D Other tracks All jets in ttbar events: choose f(p T ) such that 95% of decay products of B/D are included for all p T For non-isolated jets: x3 (x2) the rejection power for  (b)= 50% (60%) Sample-dependent

27 Measuring b-tagging performance in data

28 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200828 Key-ingredient: soft muons Dedicated  -jet trigger: –staged jet E T thresholds –1 Hz  100k in 30h (1 pb -1 @10 31 cm -2 s -1 ) Method 1: p T rel templates –b & c templates from MC –fit in p T,  bins Method 2: non-linear system (à la D0) – 2 samples – 2 different b-jet/light jet fractions – 2 non-correlated taggers  system can be solved analytically Both methods work well for p T jet <80 GeV Systematic uncertainties dominate for > 50 pb -1  Current precision on b-tag efficiency: 6%   Muon jet SVT tag jet Muon jet Calibrating b-tagging efficiency with di-jet events (p T jet <30 GeV)

29 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200829 System8 on di-jet events Measurements  system solvable analytically for , r and sample composition ! k: correlation between soft muon & track-based taggers ,  : sample dependency

30 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200830 Calibrating b-tagging efficiency with top events W jets: E T >40 GeV, 20 b-veto (weight < 3) Hadronic side b-jet: E T >40 GeV b-tag (weight>3) Leptonic side b-jet: E T >20 GeV No tag requirement Lepton: E T >20 GeV E T miss> 20 GeV Tag counting method: count 1,2,3 b-tags  likelihood best accuracy on  b : for 100 pb -1 ±2.7%(stat)±3.4%(syst) integrated efficiency only Selecting unbiased b-jets (leptonic side) Several selection methods: topological likelihood kinematic fit  signal purity 60-80% b-tagging efficiency determination: Topo.Like.Kine. Stat. (200 pb -1 )6.4%4.4%5.5% Syst. error3.4%14.2%6.2%  can also be used to extract b’s p.d.fs

31 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200831 Tag counting in top events selection ttbar l+jets: 4j > 20 GeV counting events with 1,2,3 tags HF contents: 2 b-jets possibly 1 c-jet from W possibly cc/bb from gluon splitting first order: actual: (complex!) likelihood with rough estimate of R u  4% total error with 100 pb -1  slightly better for di-lepton

32 Laurent VacavantFZU/ASCR & FJFI/CVUT – Prague – Dec 19 200832 Conclusion Expected b-tagging performance of ATLAS studied in details For simple taggers, light jet rejection of 30 (for  b =60%) Secondary vertex taggers can achieve a rejection of 150 Most advanced taggers can reach a rejection of 50 for  b =70%, very important for multi b-jet signatures (more is needed: NN, BDT) Many critical aspects studied: misalignment, material, state of detector, Monte Carlo modelling, etc – More to do: misalignment, pile-up Methods to measure the b-tagging efficiency in data have been established, allowing a ~5% accuracy with 100 pb -1 in top events Work is on-going for the measurement of mistag rates New developments, e.g. b/c separation, can broaden the physics reach of ATLAS Commissioning of the detector progressing well, our work will now focus on the commissioning of the b-tagging to transform our expectations into reality !


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