Don Lincoln. QCD Results from the Tevatron

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Transcription:

Recent Don Lincoln

Fermilab

DØ Calorimeter Uranium-Liquid Argon Calorimeter stable, uniform response, radiation hard Compensating: e/π 1 Uniform hermetic coverage η 4.2, recall η ln[tan(θ/2)] Longitudinal Segmentation 4 EM Layers (2,2,7,10) X o 4 5 Hadronic Layers (6λ) Transverse Segmentation p T = 432 GeV p T = 396 GeV η φ = 0.05 0.05 in EM 3 η φ = 0.10 0.10 otherwise ϕ = 0 η = -2 ϕ = π η = 0 ϕ = 2π η = 2

DØ Run II Detector

R = + 2 2 η φ Run I Add up towers around a seed Iterate, using jets as seeds, until stable Jet quantities: E, η, φ E jet = R 0.7 E tower Modifications for Run II Use 4-vector scheme p instead of E Add midpoints between jets as additional seeds Infrared safe Correct to particles Cone Jet Definition

Jet Energy Scale Measured jet energy is corrected to particle level E corr E O = uncorr RS O energy due to previous events, multiple interactions, noise, etc. (minimum bias, etc.) R calorimeter response to hadrons (includes non-linearities, dead material, etc.) Measured from E imbalance in γ + jet events S net fraction of particle-jet energy that remains inside jet cone after showering in calorimeter (jet transverse shapes) Large statistical uncertainties and substantial systematic uncertainties (increases with energy due to extrapolation) Current γ + jet statistics extends only to about 200 GeV

Dijets in Run II Cross section at E CM = 1.96 TeV is 2-5 times greater as compared to 1.8 TeV Higher statistics allow: Better determination of proton structure at large x Testing pqcd at a new level (resummation, NNLO theory, NLO event generators, etc.) Improved searches for new physics (quark compositeness, resonances, etc.)

Dijet Sample Selection Selection criteria: N jet 2 η jet < 0.5 R = 0.7 cone jets Data sample MET/p jet < 0.7 Primary vertex: Z vertex < 50 cm Ntracks 5 Run selection based on hardware status, MET Jet selection based on calorimeter characteristics to reduce fakes and noise (i.e. hot cells) Integrated Luminosity: 34 pb 1

Level 1 Hardware trigger Trigger Selection Fast calorimeter readout Multi-tower triggers Coverage is η < 2.4 Level 2 Software trigger with special hardware Fast calorimeter readout Simple jet clustering Level 3 Software trigger Precision calorimeter readout Simple cone algorithm with R = 0.7 (no splitting & merging) L3 p Threshold 25 GeV 45 GeV 65 GeV Offline M JJ Cut 150 GeV 180 GeV 300 GeV 95 GeV 390 GeV

Jet Energy Resolution Use the data dijet sample Asymmetry measurement Unsmearing Correction A = Correct for third jets and particle jet resolution Dijet Mass resolution unsmearing Smear PYTHIA events in mass bins Gaussian fit to Mjj/Mjj in each bin Fit to σ ( M M JJ JJ Determine unsmearing correction ) = N M p p σ = 2σA 2 2 JJ pt + N M jet1 t jet1 t 2 JJ + p p + C jet2 t jet2 t 2

Efficiencies Estimated from data Vertex quality: ~78% Jet quality: ~94% Dijet Mass Cross Section dσ dm JJ = N event L 1 M JJ C unsmear ε eff 10% normalization uncertainty not shown (luminosity) NLO pqcd JETRAD compared to data All scales set equal R sep = 1.3

Theory Comparison Main uncertainties: jet energy scale, p resolution, jet quality cuts. (Dominated by jet energy scale.) 10% normalization uncertainty not shown.

dσ dp t = N L event p Event and jet efficiencies are estimated from data 10% normalization uncertainty from luminosity is not shown The theory is NLO pqcd calculated with JETRAD T C Inclusive Jet Cross Section unsmear ε eff

Inclusive Jet Cross Section Systematic error band, dominated by energy scale (10% luminosity normalization not included)

CDF Jet 2 E T = 546 GeV (raw) η det = -0.30 Jet 1 E T = 583 GeV (raw) η det = 0.31 Collider Detector at Fermilab (CDF) New plug calorimeter (1.1 < η < 3.6) New tracking system Upgraded trigger CDF Run II Preliminary

Inclusive Jet Cross Section Event selection cuts Repeat Run I analyses z vertex < 60 cm E Use CDF cone jet algorithm T < 1500 GeV missing with R = 0.7 (JetClu) E T / E < 2 to 7 T dσ de = N ε L T E T η Require fully efficient trigger Apply jet energy corrections (same as in Run I)

Systematic Uncertainties Luminosity uncertainty = 6% Largest uncertainty

Corrected: Log 8 orders of magnitude! CTEQ 6.1: hep-ph/0303013

Corrected: Linear CDF Run II Preliminary σ ratio: Data / CTEQ6.1 JetClu cone R = 0.7, s = 1.96 TeV CDF data 5% Energy scale uncertainty CTEQ 6.1 uncertainty Good agreement (within uncertainties) Inclusive jet E T (GeV)

Dijet Mass Higher σ in Run II due to higher s 3 more bins at high dijet mass

Summary We have made significant progress on two important QCD measurements Inclusive jet cross-section Di-jet mass cross section Data/theory agreement excellent, although errors in this preliminary measurement are larger than our published results. Improved statistics for calibration will yield a measurement competitive with published results by summer, with superior results following. Analysis efforts ongoing, including a rich diffractive physics effort.

Our Jet Algorithm We use a four vector cone algorithm with a radius of 0.7 in η-ϕ space Identify seed tower in the calorimeter Using the event s vertex, assign a four vector to that seed Add all other other four vectors inside R to generate the jet s four vector If the jet s four vector does not line up with the seed s repeat using the new jet four vector as the seed. Changes from Tevatron Run I We use the midpoints between jets as seeds for new jets We use four vectors instead of scalar quantites p y (η, ϕ) (η 0, ϕ 0 ) R=0.7 J The Jet Definition = ( E J, J T 1 E ln 2 E v p ( E J ) = i J i, p i x J ( ) 2 J p ( p ) 2 p = + + p J j j z = J j pz x y, p The Jet s Properties ϕ i y, p arctan p i z J J y = J px )

Unsmearing The steeply falling cross section means that we get more jets migrating into a bin from its left than its right To unsmear this, we guess an ansatz function for the true cross section and smear it with our jet resolution We vary the ansatz s parameters to get the best possible fit Lastly, we multiply our data by the same amount that the ansatz is multiplied by to get the smeared ansatz that matches the data Steeply Falling Spectrum 1st Bin 2nd Bin 3rd Bin 4th Bin F s ( M ) JJ = dm ' JJ f ( M ' JJ ) G( M ' JJ M JJ, M ' JJ ) 0

Unsmearing the Cross Sections Because the cross section is steeply falling, imperfect jet resolution causes the cross section to shift to the right.