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This presentation discusses the basics of b-jet tagging and its importance in various physics cases such as top quark physics, Higgs searches, and SUSY models. It covers tagging algorithms, performance, and measurement techniques.
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b-tagging for the high-pTphysics program of ATLAS Laurent Vacavant FZU/Academy of Sciences & FJFI/Czech Technical University – Prague – Dec 19 2008
Introduction • b-jet tagging: identification of jets stemming from the hadronization of a b-quark, in high-pT 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 FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Top-quark physics Muon+jets channel • 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 3 jets pT> 40 GeV + 1 jet pT> 30 GeV • At least 1 btag: Ru ~200, b = 63% PT(lep) > 20 GeV No b-tagging Missing ET > 20 GeV e(ttbar) 23.6% • Lepton+jets, 100 pb-1: • S/B 2x (4x) better • requiring 1 (2) b-jets modest efficiency OK FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Higgs sector • SM Higgsbb (searches & properties): • natural interest for low mass region (Γff ∼ mf2) • 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: ≳70% needed ! bbH, H soft b-jets FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Low mass Higgs: ttH • ttH(bb) @ LHC (14 TeV), mH=120 GeV: • σ = 0.519 pb (LO), K-factor=1.2 • complex final state: for l+jets: • 1 lepton, 6 jets (4 b-jets), Etmiss • 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., Ru 3-10% change 500 Significance of lepton+jets channel, 30 fb-1: 2.2 but requires precise background extraction FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Exotics • Plethora of models • Often heavy particles decay primarily to heavy quarks t/b/c RS Extra-dim: KK-gluon σ ~15 pb for m=1 TeV(@ 10 TeV) Large branching to top: > 90% LR Twin Higgs model Common pattern for exotics:most often high-mass particles giving rise to (very) high-pT b-jets ( O(TeV) ) challenging experimentally FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Soft lepton Jet axis a0>0 a0<0 B Primary vertex Secondary Vertex y x b-tagging basics Hard fragmentation of b quarks xB ~ 70% High mass mB ~ 5 GeV Lifetime of B hadrons: c ~ 470 m (mixture B+/B0/Bs) , ~ 390 m (b) for E(B) ~ 50 GeV, flight length ~ 5 mm, d0 ~ 500 m • Spatial tagging: • Signed impact parameter • of tracks (or significance) • Secondary vertex • Soft-lepton tagging: • Low pT electron from B (D) • Low pT muon from B (D) (limited by Br: around 20% each) FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
b-tagging ingredients • Jets (direction): • to assign tracks: • to sign impact parameters • Tracks: • impact parameter resolution • (35m 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~50m) • @ high-luminosity • Lepton ID (soft leptons) σ(d0) ~ 10 ⊕ 150/pT√sinθm FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
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 FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Tracks with shared hits 0.95 1 FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Impact parameter-based b-tagging • Impact parameter: • signed w.r.t. jet direction • use significance (d0/σ) • Simplest algorithm: • counting tracks with • large d0 or d0/σ FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
JetProb tagging algorithm • JetProb algorithm:(à la ALEPH) • compatibility of tracks with primary vertex • resolution function extracted from data FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Z vs R Z impact parameter significance R impact parameter significance 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 (d0,z0) • correlations FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Secondary vertex-based b-tagging • Inclusive vertex: • Find all two-track vertices(tracks away from primary vertex: L3D/σ > 2) • Remove vertices compatibles w/ γ conv., Ks, Λ, material inter. • Fit all remaining tracks into single inclusive vertex • Remove iteratively worst tracks • Use distance to PV or properties of • the fitted vertex for discrimination: • number of two-track vertices • mass of the vertex • energy fraction • (NB: Lxy not used, correlated with IP) Ks Λ N FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
light jets SVX mass M b-jets F ratio Secondary vertex-based b-tagging • Basic algorithm: • SV0 tagger: returns L3D/σ • 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 M F FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Topological reconstruction of B/D decay • 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 • ~20% improvement • in light jet rej. • promising for b/c separation • Based on likelihood: • categories for topology • vertex mass • energy fraction • significances of {disti} light jet rejection charm jet rejection FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Tagging with Soft Muons • Br(bX)+Br(bcX) = 11% + 10% • Muon reconstruction: high-efficiency down to 4 GeV/c pT (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. (@ 2.1033) FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Performance of b-tagging algorithms 5% dead pixels tt IP3D+SV1, w>4, tt • Factorization(≠ channels): dependency on jet pT, and env. (∆R) • Degraded performance: • low pT: MS, secondaries • high η: lever-arm (z0),secondaries • high pT: 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 FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Tagging high and very high-pT 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 pT • gains (x2,x3) possible for non-isolated jets • pattern-recognition issues • ‘late’ B-decays Fraction of jets (WH400): • Require dedicated treatment for clustering, pattern-recognition FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
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 • all displacements known in reco • 1 + additional pixel random • misalignments introduced in reco only • actual ATLAS alignment procedure ! Impact on b-tagging: Both 1 and 2 require a specific procedure to increase the hit errors fully recovers tracking efficiency and fake levels 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) FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Impact of misalignments: CSC challenge FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
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%) FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Optimizing the tracks-jet association Distance track-jet vs pT: All jets in ttbar events: Tracks from B/D Other tracks • For non-isolated jets: x3 (x2) • the rejection power for • (b)= 50% (60%) • Sample-dependent • choose f(pT) such that 95% • of decay products of B/D are • included for all pT FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
Muon jet Muon jet SVT tag jet Calibrating b-tagging efficiency with di-jet events • Key-ingredient: soft muons • Dedicated -jet trigger: • staged jet ET thresholds • 1 Hz 100k in 30h (1 pb-1@1031 cm-2s-1) • Method 1: pTrel templates • b & c templates from MC • fit in pT, 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 pTjet<80 GeV • Systematic uncertainties dominate for > 50 pb-1 Current precision on b-tag efficiency: 6% (pTjet<30 GeV) FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
System8 on di-jet events Measurements system solvable analytically for , r and sample composition ! k: correlation between soft muon & track-based taggers ,: sample dependency FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
W jets: ET>40 GeV, 20 b-veto (weight < 3) Hadronic side b-jet: ET>40 GeV b-tag (weight>3) Lepton: ET>20 GeV Leptonic side b-jet: ET>20 GeV No tag requirement ETmiss> 20 GeV Calibrating b-tagging efficiency with top events • 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: can also be used to extract b’s p.d.fs FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
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 Ru • 4% total error with 100 pb-1 • slightly better for di-lepton FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008
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 ! FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008