B-tagging for the high-p T physics program of ATLAS Laurent Vacavant FZU/Academy of Sciences &...

b-tagging for the high-pT physics program of ATLAS

Laurent Vacavant

FZU/Academy of Sciences & FJFI/Czech Technical University – Prague – Dec 19 2008

Laurent Vacavant FZU/ASCR & FJFI/CVUT – Prague – Dec 19 2008 2

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


Top-quark physics

• At least 1 btag: Ru ~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 pT> 30 GeV

3 jets pT> 40 GeV +

PT(lep) > 20 GeV

Missing ET > 20 GeV

No b-tagging

modest efficiency OK


Higgs sector

SM Higgsbb (searches & properties): • natural interest for low mass region (Γff ∼ mf

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


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), Et

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., Ru 3-10% change

cut ttH ttbb(EW) ttbb(QCD) tt+jets

1 Lepton (fb) 56.9 141 1356 63710

+ 6 jets (fb) 36.2 76.7 665 26214

+ 4 b-jets loose (fb) 16.2 23.4 198 2589

+ 4 b-jets tight (fb) 3.76 4.2 29.6 50.7

500

Significance of lepton+jets channel, 30 fb-1: 2.2but requires precise background extraction


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-pT b-jets ( O(TeV) ) challenging experimentally

b-tagging basics


b-tagging basics

BBa0<0

a0>0

x

y

Secondary Vertex

Primary vertex

Jet axis

Soft lepton

Soft-lepton tagging:• Low pT electron from B (D)• Low pT muon from B (D)

Hard fragmentation of b quarks xB ~ 70%High mass mB ~ 5 GeVLifetime 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

(limited by Br: around 20% each)


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√sinθ m

4.022 R


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


Tracks with shared hits

0.951

Tagging algorithms


Impact parameter-based b-tagging

Simplest algorithm: • counting tracks with large d0 or d0/σ

Impact parameter: • signed w.r.t. jet direction• use significance (d0/σ)


JetProb tagging algorithmJetProb algorithm: (à la ALEPH)

• compatibility of tracks with primary vertex•resolution function extracted from data


Likelihood ratio IP taggers

trN

i i

ijet Su

SbW

1 )(

)(ln

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

R impact parameter significanceZ

im

pac

t p

aram

eter

sig

nif

ican

ce

Z vs R

trN

i ZiRi

ZiRijet SSu

SSbW

1 ),(

),(ln


Inclusive vertex:1. Find all two-track vertices (tracks away from primary vertex: L3D/σ > 2)

2. Remove vertices compatibles w/ γ conv., Ks, Λ, material inter.

3. Fit all remaining tracks into single inclusive vertex4. Remove iteratively worst tracks5. 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)

Secondary vertex-based b-tagging

N

Ks Λ


Secondary vertex-based b-tagging

SV

X m

ass

M

F ratio

b-jets

light jets

),,(

),,(log

),(

),(log

1 00

00

NFMu

NFMb

zdu

zdb

WWW

trackN

i ii

ii

vertextracksjet

Basic algorithm:• SV0 tagger: returns L3D/σ

MF

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


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 {disti}

~20% improvementin light jet rej.

promising for b/c separation

Topological reconstruction of B/D decay

charm

jet

reje

ctio

n

light

jet

reje

ctio

n


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)

Their Performance


Performance of b-tagging algorithms

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

5% dead pixels

tt


Tagging high and very high-pT jets

Example: Z’(2 TeV) bb, uuafter 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

Require dedicated treatment for clustering, pattern-recognition

Fraction of jets (WH400):


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 reco2. 1 + additional pixel random misalignments introduced in reco only3. 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)


Impact of misalignments: CSC challenge


Improving performance: Track Categories

Idea: • use dedicated p.d.f. for variousclasses of tracks.• already used for Shared 10%(20%) improvement for b=60%(50%)


Optimizing the tracks-jet association

Distance track-jet vs pT:

Tracks from B/DOther tracks

All jets in ttbar events:

• choose f(pT) such that 95% of decay products of B/D are included for all pT

• For non-isolated jets: x3 (x2) the rejection power for (b)= 50% (60%)• Sample-dependent

Measuring b-tagging performance in data


• 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%

Muon

jet

SVT tag jet

Muon jet

Calibrating b-tagging efficiency with di-jet events

(pTjet<30 GeV)


System8 on di-jet events

Measurements

system solvable analytically for , r and sample composition !

k: correlation between soft muon & track-based taggers,: sample dependency


Calibrating b-tagging efficiency with top events

W jets: ET>40 GeV, 20b-veto(weight < 3)

Hadronic side b-jet: ET>40 GeVb-tag (weight>3)

Leptonic side b-jet: ET>20 GeVNo tag requirement

Lepton: ET>20 GeV

ETmiss>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. error 3.4% 14.2% 6.2%

can also be used to extract b’s p.d.fs


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


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 !

B-tagging for the high-p T physics program of ATLAS Laurent Vacavant FZU/Academy of Sciences &...

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