measurement of dijet production with a jet veto at atlas
DESCRIPTION
Measurement of dijet production with a jet veto at ATLAS. Alessandro Tricoli - CERN on behalf of the ATLAS collaboration. LOW-X MEETING SANTIAGO DE COMPOSTELA 3 rd -7 th June 2011. Dijet Production with Jet Veto. - PowerPoint PPT PresentationTRANSCRIPT
Measurement of dijet production with a jet veto
at ATLAS
Alessandro Tricoli - CERNon behalf of the ATLAS collaboration
LOW-X MEETING SANTIAGO DE COMPOSTELA
3rd-7th June 2011
A. Tricoli 2
Dijet Production with Jet Veto
Low-x meeting, 3rd – 7th June 2011
Test pQCD calculations and constrain phenomenological models used in event generators in HEP
Beneficial for Higgs searches
High pT dijets are a key probe for understanding activity in the rest of the event, such as radiation between two leading or two most forward jets
Selection of a sample of dijet events and study of radiation in rapidity range bounded by dijet system: in Dy range bounded by dijet system
estimate jet activity by measuring average jet multiplicity estimate absence of jet activity by measuring the fraction of dijet events with no
additional jet with pT > Q0 (veto scale) - “gap fraction”
Jet 1 Jet 2
Dy
A. Tricoli 3
Purpose of analysis
Low-x meeting, 3rd – 7th June 2011
Test pQCD calculations and constrain phenomenological models used in event generators in HEP
test of BFKL-like dynamics – important for large jet rapidity separation study effect of wide-angle soft-gluon radiation when avrg. jet pT >> veto scale (Q0) study of colour singlet exchange when events have high pT and large Δy
beneficial for Higgs searches jet veto used in Higgs searches in Vector-Boson-Fusion channel (H+2 jets) to
reject background
A. Tricoli 4
Boundary Conditions
Low-x meeting, 3rd – 7th June 2011
Selection Aboundaries set by highest pT jets
Selection Bboundaries set by most forward jets in rapidity (y)
Observables (in <pT> and Dy of boundary jets):1) Mean Jet Multiplicity: between boundary jets2) Gap Fraction: fraction of events without jet in gap
ATLAS-CONF-2011-038
increased sensitivity to BFKL dynamics
increased sensitivity to wide-anglesoft-gluon radiation
|Dy| |Dy|
A. Tricoli 5
ATLAS Detector
Low-x meeting, 3rd – 7th June 2011
Design Goal: Precision measurements of theStandard Model and New Physics discovery
Focus on sub-systems relevant to this analysis:
Inner Detector for Tracking (|h|<2.5)
EM and HAD Calorimeters (|h|<4.9)
Different technologies:
LAr/Pb in EM calorimeter (|h|<3.2)• Three layers and high granularity
HAD calorimeters (|h|<4.9)• Tile scintillator/steel in barrel and extended barrel• LAr/Cu in endcaps• LAr/Cu, LAr/Tu in forward region
A. Tricoli 6
Event and Jet Selection
Low-x meeting, 3rd – 7th June 2011
Event Selection: Anti-kT jets with R = 0.6 (Infrared safe, collinear safe) Select inclusive dijet events with jet pT > 20 GeV and |y| < 4.5 <pT> of boundary jets > 50 GeV Veto Jet pT > 20 GeV (Q0) – for ‘gap fraction’ measurement Single interaction-vertex events [91% (19%) events retained in early (late) data-taking
periods]
ATLAS-CONF-2011-038
Events collected in year 2010 corresponding to 38 pb-1
Jets reconstructed at the EM scale and calibrated to the Jet Energy Scale (JES) using h-pT dependent corrections derived from MC simulation
Jet Energy Scale uncertainty is evaluated from combination of measurements and MC• For jet pT=20 GeV JES uncertainty between ~5%(barrel) - 13% (forward) [ATLAS-CONF-2011-032]
Event Triggering: specific single jet triggers used in slices of <pT> of boundary jets, such that
trigger efficiency greater than 99% in each <pT> slice
→ Cancellation of JES uncertainty in ratios (gap fraction)
A. Tricoli 7
Experimental Uncertainties
Low-x meeting, 3rd – 7th June 2011
ATLAS-CONF-2011-038
Experimental uncertainties smaller than theoretical uncertainties
Systematic uncertainties dominated by Uncertainties on Jet Energy Scale and
Unfolding of detector effects few % (up to ~9% at very large Dy) in Gap-Fraction 5-8% in mean number of jet multiplicity
Experimental data points dominated by systematic uncertainties at low <pT> and Dy
gap-fraction
mean number of jetsUnfolding of detector effects bin-by-bin unfolding in each observable with PYTHIA including jet reconstruction efficiency and jet energy
resolution and their uncertainties
A. Tricoli 8
Theoretical Predictions
Low-x meeting, 3rd – 7th June 2011
ATLAS-CONF-2011-038
Measurement (unfolded to hadron level) compared to various theoretical predictions
1) L.O. Event Generators commonly used for predictive purposes PYTHIA 6 (MRST LO* PDF with AMBT1 tune) HERWIG++ (MRST LO* PDF with internal tune for LO* PDF) ALPGEN+HERWIG/JIMMY (CTEQ6L1 PDF with AUET1 tune)
2) Theoretical Predictions beyond L.O.: POWHEG and HEJ (MSTW2008 NLO PDF) HEJ: parton level calculation, based on BFKL resummation
uncertainties include renormalisation/factorisation scale and PDF uncertainties
POWHEG: NLO dijet calculations interfaced to PYHTIA or HERWIG for parton showering, hadronisation and underlying event
Scale variation in POWHEG (fixed order) leads to very small uncertainty with respect to the uncertainty predicted by HEJ (BFKL-resummation)
Difference between POWHEG+PYTHIA and POWHEG+HERWIG larger than uncertainty error on POWHEG (Matrix-Element) prediction
A. Tricoli 9
Jet Multiplicity in Gap
Low-x meeting, 3rd – 7th June 2011
ATLAS-CONF-2011-038
Selection A
PYTHIA slightly overestimates jet activity at low <pT> and low Dy, but gives best description of data HERWIG++ underestimate (overestimate) jet activity at low (high) Dy ALPGEN shows largest deviation from data: too much jet activity
Similar resultsfor Selection B(see backup slides)
Jet activity in gap increases as function of <pT> and Dy
A. Tricoli 10
Gap Fraction
Low-x meeting, 3rd – 7th June 2011
ATLAS-CONF-2011-038
Selection A
Similar features as in previous slide: PYTHIA slightly underestimates gap fraction at low <pT> and low Dy, but gives best description of data HERWIG++ tends to overestimate (underestimate) gap fraction at low (high) Dy ALPGEN shows largest deviation from data, underestimating gap fraction
Similar resultsfor Selection B(see backup slides)
Gap fraction decreases as function of <pT> and Dy
A. Tricoli 11Low-x meeting, 3rd – 7th June 2011
ATLAS-CONF-2011-038
Selection A
Jet Multiplicity and Gap Fractionas function of <pT>
Deviations between HEJand data at large <pT>
includes all order resummation in Dy
but not all important terms as <pT>/Q0 increases
POWHEG+PYTHIA describes data well POWHEG+HERWIG
overestimates jet activity (underestimates gap fraction)
Jet Multiplicity Gap Fraction
A. Tricoli 12Low-x meeting, 3rd – 7th June 2011
ATLAS-CONF-2011-038
Selection B
Jet Multiplicity and Gap Fractionas function of <pT>
Gap FractionJet Multiplicity
Smaller deviation between HEJ and data
at large <pT> expected as includes all
order resummation in Dy
POWHEG+PYTHIA describes data well
POWHEG+HERWIG overestimates jet activity (underestimates gap fraction)
A. Tricoli 13
Jet Multiplicity and Gap Fraction as function of Dy
Low-x meeting, 3rd – 7th June 2011
ATLAS-CONF-2011-038
Selection A Selection B
HEJ describes well jet activity in
low, medium Dy some discrepancies at high
Dy
POWHEG underestimates Gap Fraction at large Dy
with Selections A and B parton shower not
recovering resummation terms important as Dy increases
Gap FractionJet Multiplicity
A. Tricoli 14Low-x meeting, 3rd – 7th June 2011
ATLAS-CONF-2011-038
Selection B
Jet Multiplicity and Gap Fractionas function of Dy with Veto Scale Q0=<pT>
HEJ agreement degrades at high Dy
POWHEG+PYTHIA & POWHEG+HERWIG describe data well
reduced dependence on modeling of parton shower, hadronisation and underlying event
Gap FractionJet Multiplicity
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Summary (I)
Low-x meeting, 3rd – 7th June 2011
ATLAS-CONF-2011-038
ATLAS measurement of jet activity in the rapidity interval between boundary jets Average Jet Multiplicity Gap Fraction (fraction of events without jet in gap)
These results test important aspects of pQCD and will benefit global efforts to produce phenomenological tunes for the event generators.
Two different selections adopted to probe both soft and hard emissions between widely separated jets
Probing different approximations implemented in Event Generetors L.O. or N.L.O. + Parton Shower (e.g. PYTHIA, POWHEG)
- all-order QCD for soft and/or collinear higher order emissions BFKL-like dynamics (HEJ)
- all-order QCD for hard and well-separated higher order emissions
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Summary (II)
Low-x meeting, 3rd – 7th June 2011
ATLAS-CONF-2011-038
The constraining the event generator modeling of QCD radiation between widely separated jets leads to an improved understanding in the application of jet vetoes in Higgs-plus-2 jet analyses
Accuracy of Experimental Results sensitive to theoretical modeling None of the theory calculations describe the data in all kinematic regions
PYTHIA and POWHEG+PYTHIA describe well gap fraction and mean jet multiplicity HEJ generally well describes Dy dependence, but predicts too little jet activity at
large values of <pT>/Q0 , i.e. when soft and collinear emissions need to be accounted for (not interfaced with Parton Shower)
POWHEG+HERWIG, HERWIG++ and ALPGEN+HERWIG predict too much activity between jets
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Backup
Low-x meeting, 3rd – 7th June 2011
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The ATLAS Calorimeters
Low-x meeting, 3rd – 7th June 2011
A. Tricoli 19
Jet Multiplicity in Gap
Low-x meeting, 3rd – 7th June 2011
ATLAS-CONF-2011-038
Selection B
PYTHIA slightly overestimates jet activity, but gives best description of data HERWIG++ underestimate jet activity at low Dy ALPGEN shows largest deviation from data
to much jet activity, especially at large Dy and <pT>
A. Tricoli 20
Gap Fraction
Low-x meeting, 3rd – 7th June 2011
ATLAS-CONF-2011-038
Selection B
PYTHIA slightly underestimates gap fraction at low <pT> and low Dy, but gives best description of data HERWIG++ tends to overestimate (underestimate) gap fraction at low (high) Dy ALPGEN shows largest deviation from data, underestimating gap fraction
A. Tricoli 21
Jet Multiplicity in Gapas function of Dy
Low-x meeting, 3rd – 7th June 2011
ATLAS-CONF-2011-038
Selection A Selection B
HEJ well describes jet
activity in low, medium Dy
underestimates it at high Dy with Selection A
POWHEG describes data well
POWHEG+PYTHIA in better agreement with data
A. Tricoli 22Low-x meeting, 3rd – 7th June 2011
ATLAS-CONF-2011-038
Selection A
Gap Fractionas function of Dy
HEJ well describes Gap Fract.
in low, medium Dy slightly underestimates at
high Dy with Selection B
POWHEG slightly underestimates data at large Dy parton shower not
recovering resummation terms important as Dy increases
Selection B
A. Tricoli 23
Jet Reconstruction
Low-x meeting, 3rd – 7th June 2011
Starting point:➢ calorimeter cells calibrated to electromagnetic (EM) scaleInput to jet reconstruction➢ 3D Topological clusters➔ uses nearest neighbor energy significanceto localize showers in the calorimeter➔ efficient noise suppression
Jet reconstruction➢ Jets are reconstructed using the anti-Kt algorithm with size parameter R set at 0.6
Jet calibration➢ Energy and momentum of a jet measured in the calorimeter are corrected using kinematics of a Monte Carlo truth jet as reference
➔ for non-compensation, energy losses in dead material, shower leakage➔ using PYTHIA inclusive QCD events
EM+JES schema simple default Monte Carlo based calibration➔ (h, pT) dependent correction factor Etruth / Ecalo
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Jet Energy Scale Uncertainty
Low-x meeting, 3rd – 7th June 2011
0.3< |η| < 0.8
JES uncertainty evaluated from combination of measurements and MC1) Uncertainty of single hadrons measured in data and propagated to jets using MC
Uncertainty for single isolated hadrons is measured by E/p from isolated tracks (p<20 GeV), or from test-beam
Correlate single particle uncertainty with jet uncertainty using jet composition2) Uncertainty is assessed up to |h|=4.5 using dijet balance measurements3) Finally combined with additional uncertainties evaluated using systematic variations of MC
➔ dead material, noise, hadronic shower models, soft physics effects, generators
Monte Carlo based jet energy calibration has tested insitu(good agreement with JES uncertainty from single hadron response)
➔ multijet balance➔ calorimeter jet – track jet balance➔ direct gamma-jet balance➔ photon balance using missing transverse momentum projection
Summary on fractional systematic JES uncertainty as a function of jet pT
ATLAS-CONF-2011-032
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Jet Energy Resolution
Low-x meeting, 3rd – 7th June 2011
Jet momentum resolution measured insitu with dijets using bisector technique
Advanced calibrations improve resolution by 10-30% ➔ Monte Carlo agrees with data within 10%
A. Tricoli 26
ATLAS Jets
Low-x meeting, 3rd – 7th June 2011
Anti-kT Algorithm Infrared safe, collinear safeRegular, cone-like jets in calorimeter
[Cacciari, Salam - JHEP 0804:063,2008]