b-jet production cross section at cdf monica d’onofrio university of geneva wine&cheese...

B-jet production cross section at CDF

Monica D’Onofrio

University of Geneva

Wine&Cheese Seminar, September 9th 2005

Monica D'Onofrio Wine&Cheese Seminar, Fermilab September 9th 2005

2

In the last 15 years… Study of events with b-quarks has led to important

Tevatron results Discovery and study of the top quark B physics in general (spectroscopy, lifetimes measurement,

sin 2etc..) Measurement of quarkonium states and appreciation of

color-octet-mediated production mechanisms

These results mostly obtained

when a factor 3 discrepancy

was reported between theory

predictions and experimental

data by both CDF and DØ

in b-hadron cross sections


3

« To claim that we need to understand b production in order to make new discoveries is therefore a bit exaggerated …

.. Nevertheless, lack of confidence in the ability to describe properties of events containing b quarks, in addition to raising doubts over the general applicability of pQCD in hadronic collisions, does limit our potential for the discovery of possible subtle and unexpected new phenomena » (M.Mangano, HCP2004)

Therefore, the study of b production properties should be one of the main priorities for RunII … …also considering high statistics..

Ecm=1.96 TeV (bb) ~ 50 b

few kHz event rate!!


4

Outline Recent advances in the theory of b production

cross sections in hadronic collisions and application to experimental results related to B-hadrons.

Exploring b-jets at CDF: Inclusive b-jet cross section

Event selection, experimental tools Results and preliminary comparison with theoretical

calculations at Next-to-Leading order (NLO)

More exclusive b-jet cross sections bb-jets correlations: to disentangle b production

processes Z+b-jet cross section: to probe b content of the proton

Conclusions

The theory and recent developments


6

B-quark production in hadron collisions

Leading Order Next to Leading Order

Gluon splitting

Flavor excitation

Flavor creation

g

g

gg

Q

Q

other radiative corrections..

Experimental inputs are B-Hadrons or b-jets rather than b-quark

Factorization theorem: factorize physical observable into a calculable part and a non-calculable but universal piece

DFbpd

bXqgggqqd

Bpd

BXppd Bbpp

TT

//

NLO QCD

Observed Proton structure

Fragmentation


7

Proton structure: PDF

Parton Distribution Functions (PDFs) are universal global fitsto data on proton structure independent of the process Momentum distributions of the

partons inside proton

Generally PDF uncertainties are estimated at ~ 15%

Dominant contribution due to high x gluon distribution

gluon

u

d

d

x

Uncertainty on gluon PDF (from CTEQ6)

x


8

Fragmentation functions Db B

''' dxxxx DDDpertnonpertmeas

Perturbative part: probability to find a hadron with fraction x’ of original parton momentum

Hadronization: non perturbative QCD, need models


9

Recent theory advances • pQCD calculations:

• resummation of slog(pT/m) terms

Fixed Order Next Leading Log (FONLL)

• pT >> m need large corrections

• Moment analysis to treat Dmeas

for fragmentation (new approach: Cacciari et. Al. 2002)

Release date of PDF

bN

LO(|y

|<1)

(b

)

<1994

now

• Cross section very dependent on PDF evolution


10

Testing FONLL: B hadron production

J/

K+B+

J/ decays of B-Hadrons used to measure the b production cross section

Find J/ inclusive cross section Extract fraction of J/ from decay of long-lived b-hadrons Find b-hadrons cross section for

pT(B) down to 0 considering |y(J/)|<0.6

B J/ Xshape from MC templates

J/ from B J/ Xwill be displaced

Maximum likelihood fit on flight path to extract b fraction as function of pT(J/)


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B hadron production cross section

Total inclusive single b-hadron (Hb) cross section

considering Br(HbJ/X) = 1.160.10% and Br(J/) = 5.880.10%

Good agreement with theory prediction


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Summary on theory advances

comparison with RunI data |y(Hb)| < 1, RunII multiplied by B+ fragmentation=0.4 (Ecm rescaled)

RunI

RunII

Reduction of discrepancy is due to four basic points:

• FONLL calculation brings 20% increase in intermediate pT region• fragmentation step from perturbative b quark to B hadron at small pT was too strong: 20% increase in this pT region • Peterson fragmentation function was too soft: use new LEP data =0.002 additional 20% increase• PDF evolution (> 20% increase)

Data moved ~ 20% down (still within errors)Many little changes combined together

big effect in Data/Theory comparison


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Why b-jets?• b-jets include most of quark fragmentation remnants small dependence on fragmentation • wide PT spectrum

In RunI studies performed to measure bottomand charm fraction in inclusive jet samples

b = 19 ± 2(stat) (syst) [nb]

at PT> 35 GeV/c

+5- 6 +3

- 1

In RunI differential b-jet cross section using semi-leptonic decays of the b

(muon tagger)

PT(B) GeV/c

(p

T>

pTm

in,

|y|<

1)(

nb)

Inclusive b-jet cross section at CDF


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The Tevatron in RunII•Peak luminosity in 2005 above 1032 cm-2 s-1

•CDF collected ~ 1 fb-1 on tape!!

(but 1.2 fb-1 already delivered)

•Analysis shown here use ~ 300 pb-1


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The CDF experiment

Collider Detector Fermilab

CENTRAL and PLUG Calorimeter energy and direction

2 systems of passive layers-scintillators

Silicon Detector

With 750,000 channels, the largest Silicon detector in the world!

position

3 systems of single or double sided detector

down to 10 m spatial resolution (3D)

COT position

drift chamber

spatial resolution

100 m

Muon Chamber (collision hall)

position and pT

4 systems of scintillators and proportional chambers

min scattering resolution [12/p;25/p] cm/p

TOF time

Scintillators

100 ns resolution

Solenoid (1.4 T)


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B-jet cross section

Nitagged is the number of tagged jets

ib-tag is the b-tagging efficiency

fib is the fraction of b-jets among tagged jets

Ciunfold are correction factors from Monte Carlo for acceptance

and smearing effects

Y is the rapidity range

piT is the size of bin in transverse momentum

∫L is the integrated luminosity


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Jet reconstruction

Final state partons are revealed through collimated flows of hadrons called jets

Beam remnants

Hard scattering

Multiple partons interaction

Two main type of jet algorithms (in CDF):- Cone Algorithm JETCLU and MIDPOINT- KT algorithm

Jet

Seed towers Only iterate over towers above certain

threshold (3 GeV at CDF) MidPoint adds extra seed in centre of each

pair of seeds Infrared safe Ratcheting (JetClu only)

All towers initially inside a cone must stay in a cone

Merging/Splitting

fmerge=0.75


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Event selection MIDPOINT jets, Rcone = 0.7, |Yjet|<0.7

PT range 30-360 GeV/c

38-400 GeV/c for corrected PT jets

use 5 samples with different ET

jet threshold

Total luminosity used ~ 300 pb-1

Inclusive calorimetric triggers: Level 1: selection based on ET of

cal towers (EM+HAD) Level 2: accept tower clusters

with ET above a fixed threshold Level 3: jets reconstructed (JETCLU, Rcone=0.7, Zv=0)

L1L2L3

Dataset

Path

>|Z primary vertex|<50 cm to assure good energy measurement, vertexing capability> Cut on missing ET Significance ( = ET/√∑ET) implemented to reject to cosmic rays

Event Selection

Trigger efficiency


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Jet corrections: detector effects

For each calorimeter jet in |Y|<0.7 look for the corresponding hadronic (particle) jet to remove dependence from detector effects

Tim

e

20 ÷ 10%

• b-quark-originated jets different from ordinary jets• account for smearing effects for detector resolution

apply “unfolding” correction bin by bin for b-jet from Monte Carlo hadronic b-jet

• need inclusive correction that takes into account the

bias due to the tagger correction on tagged jets


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Jet Corrections: Pile up

Effects in jet PT: about -1 GeV/c per each additional primary vertex

Jet samples

Average number of primary vertices as a function of instantaneous luminosity

Small dependence on Lum.

6 different slices of Instantaneous luminosity

UEM (PT) = 0.932±0.002 GeVMain idea: measure PT in a random cone in Minimum Bias sample (central region) as a function of # primary vertices to define effect due to multiple interactions;


22

B tagging algorithm

• Looks for tracks associated with a jet

• the track selection is based on on measurement of impact parameter (d0)

with respect to primary vertex

In general b-tagging procedures take advantage of the long life-time of B hadrons c ~ 450 m

• Need ≥ two displaced tracks to reconstruct a secondary vertex (made in 2 steps)

• After secondary vertex reconstruction require to be well separated from primary vertex in r- space by looking at Lxy and its error:

Jets passing those selections: tagged


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B tagging efficiency (1) Use Monte Carlo simulation to cover the wide PT spectrum [38-400] GeV/c Measure efficiency scale factor to take into account simulation imperfections (tracking efficiency&resolution, B hadron decay

models…) For this purpose, use independent dataset

• Sample enhanced in b-jet content: dijet events one e/jet + “away” jet tagged• look e.g. at b-jet for the muon jet

b jet =F tag bjet Ntag+ jet

Fbjet N jet

b-jet content after tagging

b-jet content before tagging

Measure b-tagging efficiency in Data and MCb-jet content extract

using PTrel muon-jet


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B tagging efficiency (2)

Data b-jet/MC b-jet Scale Factor (SF)

SF = 0.9090.06(stat+syst)

Systematic error due to hadronic VS semileptonic b-decay below 3%

Geometrical acceptance and energy dependence of the tagger from simulation

Tagging rates parametrized as function of relevant variables to define systematic error on PT

dependence 5%


25

Extract fraction of b-tagged jets from data using shape of mass of secondary vertex as discriminating quantitybin-by-bin as a function of jet pT

2 component fit:b and non-b templates (Monte Carlo PYTHIA)

b-fraction tagged jets

82 < pTjet < 90 GeV/c


26

Systematics errors

• Main sources:o jet reconstruction o Secondary vertex mass templates

Uncertainty: MC generator, fitting procedure Heavy quark multiplicity in jets Fragmentation

3% ES Resolution Smearing effect on cross section ~ 20-40%

Tota

l Je

t R

eco

nst

r. (

%)

JES o

nly

(%

)


27

Systematics on Secondary vertex MassTo estimate systematics: Test fit stability depending on templates shape and statistic

- also PYTHIA/HERWIG comparison effects of fluctuation in relative composition of 2b/1b and 2c/1c

estimate from NLO calculation

Check on templates variation due to fragmentation scheme:PYTHIA Lund model, =0.0025 (default) VS Peterson model, =0.006

148 < pT < 202 GeV/c

1c/2c 1b/2b

Total systematic from fraction: from 10% to 30% (but for last bin ~ 50%)


28

b-jet cross section: results

Total systematic error ~ 25% 70% in the last bin

Differential b-jet cross section at particle level (range pT 38-400 GeV/c)

Ratio Data/Pythia MC(CTEQ5L)

Preliminary comparison with NLO for inclusive b-

jet cross section


30

b-jets @ NLO

- NLO calculation for b-jets Mangano&Frixione- 2 3 process, so jets are very simple: 1 or 2 partons inside

Shape very sensitive to bb content from gluon splitting (more likely to have 2 b inside same jet)

gg

qq qg

qbbqg

gbbqq

gbbgg

total


31

Scale dependence of b-jets @ NLO

Fraction of double b-quark ending up in the same jet depend on gluon splitting, only appearing at LO

mP bTFR

22

0

24/1

Strong scale dependence

~ 45%

~ 30%

Rate bb-jets / All jets


32

Hadronization and Underlying events

Hadronization Underlying events

~ 20% correction for lowest bin None for b-jets above 130 GeV/c

Corrections that needto be added to theory

from PYTHIA Monte Carlo

Before comparison with theoretical expectations correct NLO b-jets for hadronization and underlying events


33

Preliminary Data VS NLO b-jets

NLO theoretical expectation for b-jetcorrected at particle level

2/2/ 22

0 mP bTFR

in analogy to inclusive jet crosssection measurements

mb=4.75 GeV/c2

PDF Uncertainty: 7% 20% Merging/splitting issue: Rtheory=Rdata*Rsep, Rsep=1.3

10% uncertainty

Include scale uncertainty

~ from 40% 20% (PT

bjet>250 GeV/c)

004/


34

Data/NLO ratio

Ratio up to 1.5 above 100 GeV/c jetsPoor agreement but still within systematics without considering scale uncertainty

if considering scale uncertainty overlap region increase


35

Comparison with Run I D results

Use for central theory value data close to upper band of systematic (=0/2 PDF uncertainty) direct comparison of data not possible (different center of mass energy s, different jet algorithm, different rapidity range …) For jets below 100 GeV/c, D0 data in RunI showed a similar pattern


36

Issues on high PT b-jets

• Unknown impact of higher order contributions: • reduced scale dependence • event has more partons in the final state, thus closer

to the real world • better description of the transverse momentum of

final state due to double radiation of initial states

Logarithmic log(pT/m) enhancement of higher order contribution due to

gluon splitting is not included in NLO calculations (neither in MC@NLO)

at low PT effects are small (range of B-hadron cross section)

at high PT are very important and need to be considered

Experimentally:• study of bb-jets correlation to disentangle different production mechanisms• Z+b jets and +b jets

could help to constrain the b density in the proton

More exclusive bjet cross sections


38

bb jets cross section dijet events

• JETCLU, Rcone=0.7 jets

• ET1>30GeV, ET

2>20GeV

•|jets| < 1.2 central jets: more likely to be sensitive to flavor creation

Jets corrected at particle level for b flavor jets

Tag 2 jets with b-tagging algorithm earlier described

Flavor excitation

g

g

gg

Q

Q

Gluon splitting

Flavor creation ( +radiative corrections)

predominantly back-to-back

Small data sample used still preliminary Analysis with larger sample in progress


39

bb jets cross section results

b fraction fromMass secvtx fit

(global fit all ET range)

Fbb=0.830.04

= 34.5 1.8 nb+10.3- 10.7

(stat.) (syst)

Integrated cross section:

A = trigger acceptance ~ 1

LA

FNother

b

lead

b

tagb

tag

evts

bb

Pythia (CTEQ 5l) 38.71 0.62nb

MC@NLO 28.49 0.58nb

Monte Carlo prediction:

= 35.7 ± 2.0 nb with preliminary UE tuning

Need to add more statistics on MC@NLO with final Underlying Event tuning

Data results


40

bb jets correlations

Predominantly back to back Explains agreement in cross

section with Pythia LO MC deviates away at low

(where statistics are still low)

Differential cross section as function of jets

Compared to MC@NLO

Linear scale

Log scale


41

Z+b jet production In QCD, Z+b can help constrain b density in the proton

Probe the heavy flavor content of proton

+

With HERA Fbb2 data:

CTEQ below MRST by down to 1/2 and below data Z+b jets can help understand this picture

Important background for new physics such as higgs search


42

Analysis strategy Leptonic decays for Z reconstruction: Z e+e-, +-

Signal defined as Z0,l+l- events with 66<Mll<116 GeV/c2

Z associated with jets - Rcone jet = 0.7, ||<1.5, ET>20 GeV

Backgrounds: - fake electrons/same-sign muons (Data) - Real signatures e+e-/+- + bjet (MC)

Muon channel equivalent


43

Mass of secondary vertex Fit

Look for tagged jets in Z events same b-tagging algorithm as in

previous analyses extract fraction of b-tagged jets

from secondary vertex Mass Use negative tagged jets to

better constrain light and c

quarks Make no assumption on the

charm content

extract b: NbData/Nb

MC

Main source of systematic uncertainty from dependence of mass templates on b/bb content in the jet


44

Z+bjets results Z+b jet cross section corrected at particle (hadron) level:

ZmeasN DataZ

N MCZ

N MCHadZ

N MCHadbjetZ

SFbbjetZ

b : NbData/Nb

MC in Z events SF : scale factor for b-tagNZ+b

MCHad : MC particle b-jets in Z evts

NZMCHad

: total MC Z evtsNZ

MC : MC evts passing Z cuts

NZData

: Data evts passing Z cuts

meas(Z) : CDF Z cross section

=MZ Uncertainty ~10% changing scale

Central value for Z+b cross section also above theoretical expectations

pbsyststat )(14.0)(32.096.0


45

Summary and Conclusion In the last year many advances in theory calculation for b

production at intermediate and low PT

Good agreement with B-Hadron cross section

Big effort in study of b-jets production in CDF RunII

Inclusive b-jet cross section measurement done within a wide range in transverse momentum using ~300 pb-1 data

Similar behaviour to D RunI cross section w.r.t.

theoretical expectations for jet PT below 100 GeV/c

Agreement with theory within uncertainties: NLO b-jet cross section calculation still shows big scale dependences

Study of more exclusive b-jet cross section could help:

bb correlations to disentangle production processes

Z+b to understand b content in the initial radiation

Back up


47

Impact parameter resolution

Typical d0 resolution


48

B-jet cross section: Data/Herwig MC


49

bb jets differential cross section

Differential cross section as function of dijet mass

Differential cross section as function of leading jet ET

Comparison Data VS MC @NLO + UE tuning

Comparison Data VS MC @NLO + UE tuning


50

Z + b

Z +- channel: same-sign muons events with a reconstructed jet

Specific background in muon channel


51

NLO uncertainty for Z+b Scale dependence is small ( 10%) Big uncertainty on b density in the proton


52

Sec. Vertex mass (GeV)

Et > 25 GeV (||<1.0) + jet with secondary vertex

Determine b, c, uds contributions (fit secondary vertex mass)

Subtract bkg, find cross-section as fn. Et

25–29 GeV 29–34 GeV

34–42 GeV 42–60 GeV

+b/ +c production


53

Results consistent with LO

(+b) (+c)

+b/ +c production

b-jet production cross section at cdf monica d’onofrio university of geneva wine&cheese...

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