Recent jet measurements at the Tevatron Sofia Vallecorsa University of Geneva

IFAE 2006 Pavia, Aprile Outlines The Tevatron and the experiments Jet Recostruction Inclusive jet cross section –Cone algorithm (CDF,D0) –K T algorithm (CDF) Boson+ jets –W+jets (CDF) –Z+jets (D0) Heavy flavour –  - tagged jets (D0) –Inclusive b-jet cross section (CDF) –bb correlation (CDF) Conclusions

The Tevatron Peak luminosity ~ cm -2 s -1 Integrated lumininosity ~ 25 pb -1 /week ~ 1.6 fb -1 already delivered Highest energy collider currently running ~1.2 fb -1 on tape

CDF and D0 Both detectors: Silicon Microvertex Tracker Calorimeter Muon Chambers High speed Trigger/DAQ D0: Excellent  ID and acceptance Excellent tracking acceptance |  | < 2-3 CDF: L2 trigger on displaced vertex Excellent tracking resolution

IFAE 2006 Pavia, Aprile TO COMPARE:  Need a common and unambiguous definition for theory and experiments.  Jet reconstruction algorithms:  Jet corrections Jets at Tevatron  Cone based algorithms MidPoint (new RunII ) Infrared safe and well defined  Merging pairs of particles according to their relative pt Kt (recently CDF) Infrared and collinear safe JETS : collimated flows of hadrons Measurements LEVEL Theory prediction LEVEL

IFAE 2006 Pavia, Aprile Jet corrections Calorimeter jets: complex detector behavior. –correct for detector resolution and efficiency –correct for pile-up interactions (~up to 6 extra interactions) Hadron jets: model dependent correction –Underlying event subtraction –Remove fragmentation/hadronization effects –MC based -> need to be tuned on data by using different observables Parton jets: model dependent correction –Gluon radiation, energy loss (MC based) Hadronic showers EM showers

IFAE 2006 Pavia, Aprile Inclusive jet cross section

IFAE 2006 Pavia, Aprile Inclusive Jet Production: Run I Run I –Cone jet finding algorithm –Apparent excess at high pT, but within the overall systematic errors –Is it New Physics or parton distribution function ? Between Run I and Run II –Machinery for improved jet finding algorithms: - MidPoint Cone Algorithm - kT Algorithm PDFs are further tuned data/theory – 1, %

IFAE 2006 Pavia, Aprile Inclusive jet cross section MidPoint algorithm cone 0.7 Inclusive calorimetric trigger L3 Et>20,50,70,100 Central jets 0.1<|y|0.7 DATA: dominated by JES uncertainties (2-3%) NLO:dominated by high X gluon PDFs L=1fb -1 Sensitive to UE+Hadronisation effects for P T <100 GeV/c Good agreement with NLO

Inclusive jet cross section MidPoint algorithm R = regions in rapidity explored |y jet |< 0.4, 0.4 <|y jet |< 0.8 JES gives biggest contr. to uncertainty G ood agreement with NLO prediction (NLOJET++) L = 380 pb -1

IFAE 2006 Inclusive jet cross section K T algorithm D=0.7 Inclusive calorimetric trigger L3 Et >5,20,50,70,100 Central jets GeV/c L~1fb -1 NLO corrected to hadron level Measurement extended over 8 orders of magnitude Very good agreement with NLO

IFAE 2006 Pavia, Aprile Inclusive jet cross section Forward jets measurements constrain gluon distribution in a kinematic region where no effect from new physics is expected -> help to distinguish between new physics and PDF if any excess is found in the central region K T jets D=0.7 5 region in rapidity: –|Y| < 0.1 –0.1 < |Y| < 0.7 –0.7 < |Y| < 1.1 –1.1 < |Y| < 1.6 –1.6 < |Y| < 2.1

IFAE 2006 Pavia, Aprile Boson + jets

Pavia, Aprile W+jets production L = 320 pb -1 Background to top and Higgs Physics Testing ground for pQCD in multijet environment –Key sample to test LO and NLO ME+PS predictions Restrict  W : –W  ev, |  e |< 1.1 JETCLU jets (R=0.4): –E T jets >15 GeV, |  jet | < 2. Uncertainties dominated by background subtraction and Jet Energy Scale LO predictions normalized to data integrated cross sections  Shape comparison only

IFAE 2006 Pavia, Aprile W+jets production Differential cross section w.r.t. di-jet DR in the W+2 jet inclusive sample Differential cross section w.r.t. di-jet invariant mass  in the W+2 jet inclusive sample More exhaustive comparisons expected soon!!! LO predictions normalized to data integrated cross sections  Shape comparison only

Z+jets production MCFM: NLO for Z+1p or Z+2p  good description of the measured cross sections ME + PS: with MADGRAPH tree level process up to 3 partons  reproduce shape of N jet distributions (Pythia used for PS) L = 343 pb - 1 p T spectra of n th jet distribution Z+j Z+2j Z+3j Same motivations as W + jets –  Z) ~  W) / 10, but Z  e + e - cleaner Central electrons (|  |<1.1) MidPoint jets: – R = 0.5, p T > 20 GeV/c, |y jet |<2.5

IFAE 2006 Pavia, Aprile Heavy flavour jets

IFAE 2006 Pavia, Aprile Inclusive b jet cross section: Run I In Run I, a factor 3 discrepancy was reported between theory predictions and experimental data by both CDF and DØ in b-hadron cross sections Recent theory development: FONLL (Cacciari et. al.) – NLO resummed Very good agreement with more exclusive B-hadron production check for more inclusive observable - bjet production – comparison with NLO only

IFAE 2006 Tagging b jets B hadrons are massive – decay into lighter flavors – use decay products to tag B – ‘Soft Lepton Tag’ B hadrons are long lived – c  ~ 460  m – give rise to secondary vertices – tracks from secondary vertex have non-vanishing impact parameter d 0 at primary vertex – ‘Secondary Vertex Tag’ & ‘Jet probability’

 -tagged jets production Midpoint cone R=0.5 jets Central region |Y|<0.5 Require pt>5 GeV/c  inside cone R=0.5 Heavy flavour fraction % from MC L=300 pb -1 Data/Pythia ~1.3 Main systematics on data: JES and HF fraction NLOJET++ NLOJET++(CTEQ6M,  =pt/2)  b - fraction (from Pythia)

Inclusive b - jet cross section More than 6 orders of magnitude covered Data systematic uncertainties dominated by Jet Energy Scale and b-fraction uncertainties Main uncertainties on NLO due  R /  F scales Agreement with pQCD NLO within systematic uncertainties  Sensitive to high order effect (NNLO) MidPoint jets: R = 0.7, |y jet |< 0.7 Reconstruct secondary vertex from B hadron decays (b-tagging) Shape of secondary vertex mass used to extract b-fraction from data L = 300 pb -1

bb correlations JetClu (RunI cone) jets  R=0.7 – |  | 20 GeV,30 GeV Main systematics: –Jet energy scale (~20%) –b tag efficiency (~8%) UE Herwig description + JIMMY Generator for multiparton interactions (links to Herwig) --> Better description of underlying event Data34.5 ± 1.8 ± 10.5nb Pythia(CTEQ5l)  0.62nb Herwig(CTEQ5l)  0.66nb  0.58nb Total cross section  = 36  2 nb

IFAE 2006 Pavia, Aprile Conclusions In 2005, Tevatron achieved the 1 fb -1 goal Delivered total luminosity 1.6 fb -1  1.2 fb -1 on tape available to analyses Very rich QCD physics program ongoing at CDF and D0  Explore different jet algorithms  W/Z + jets production provides good feedback for MC tools (Matrix element and Parton showering)  Precision measurements to test pQCD and constrain PDF

IFAE 2006 Pavia, Aprile Back-up

IFAE 2006 Pavia, Aprile Jet reconstruction algorithms K T algorithm: Preferred by theory –Partons are separated into jets according to their transverse momentum Compute for each pair (i,j) and for each particle (i) the quantities –Iteration until find stable jets –Use E-scheme –Infrared and collinear safe No merging/splitting parameter needed successfully used at LEP and HERA  relatively new in hadron colliders More sensitive to Underlying event and multiple interactions Cone algorithms: Seed towers –Only iterate over towers above certain threshold JETCLU: Snowmass (E T ) - scheme MIDPOINT: E - scheme –MidPoint adds extra seed in centre of each pair of seeds  Infrared and collinear safe Ratcheting (JetClu only) –All towers initially inside a cone must stay in a cone Jet merging/splitting is an issue: –Need to define a F merge parameter

IFAE 2006 Pavia, Aprile Parton to hadron correction NLO calculation for inclusive jet production only has 2,3 partons in the final state -> prediction at parton level -> Need to correct to hadron level to compare to data  UE : additional energy is added in the jet cone (Multiple Particle Interactions + Beam Remnants) -> Need to add to theory prediction  Hadronization effects: some energy is loss from the jet cone -> Need to subtract to theory prediction Use Pythia tune A which include tuned parameters for UE

IFAE 2006 Pavia, Aprile Inclusive Jet Production Probes physics at small distances ≈ m Higher reach in pT due to increased √s Test pQCD over more than 9 decades in  Sensitive to PDF high-x) Uncertainty on gluon PDF (from CTEQ6)

IFAE 2006 Pavia, Aprile Forward jets (k T algorithm) 0.7<|Y|< <|Y|<1.61.6<|Y|<2.1

IFAE 2006 Pavia, Aprile W+jets production Integrated cross section w.r.t. jet E T in each of the 4 W+n jet inclusive samples

IFAE 2006 Pavia, Aprile b quark production in hadron collisions Leading OrderNext to Leading Order Gluon splitting Flavor excitation Flavor creation g g g g Q Q other radiative corrections.. Experimental inputs are B-Hadrons or b-jets rather than b-quark NLO QCD Proton structure Fragmentation => Another stringent test of NLO QCD

IFAE 2006 Pavia, Aprile NLO/LO comparison As example: bjet cross section calculated in the past (2003) R cone jet=0.4, |  bjet |<0.6 as function of E T not meant to be direclty compared to the measured one Contribution more suppressed in a LO MC Initial states NLO/LO increase at high ET  Gluon splitting dominant As function of b inside jets

IFAE 2006 Pavia, Aprile High P T b-jet cross section (CDF) Extract fraction of b-tagged jets from data:  use shape of secondary vertex mass 82 < p T jet < 90 GeV/c D isplaced tracks inside jet used to reconstruct secondary vertex from B hadron decays (b-tagging)