July 7, 2008 SLAC Annual Program Review Page 1
New Approaches to Hadronic Final State Reconstruction
D. W. Miller
SLAC ATLAS
July 7, 2008 SLAC Annual Program Review Page 2
Overview
• Extending jet algorithm functionality and flexibility for first data
• New approaches to jet reconstruction and missing energy through use of tracking information
• Jet-vertex association for high luminosity jet identification, jet-energy corrections and primary vertex selection
• Semileptonic b-jet energy corrections
• Missing ET significance
Extending jet algorithms for first data
Legacy jet algorithms
• Tower algorithm (TowerJets)– Built from geometrical
arrangements of calorimeter cells
– No noise suppression is applied
• Topological clusters (TopoJets)– Built from topological clusters
of calorimeter cells– Noise suppression is applied– Clusters size can grow non-
linearly in presence of pile-up
New approach in ATLASNew approach in ATLAS• Use the most desirable aspects
of each algorithm– Towers are finite, well-defined
objects– Clusters efficiently select cells
above a dynamic noise threshold
Build towers using only cells used in topological clusters– Noise suppression– Well-behaved at high-
luminosity– Overlap studies between
TopoJets and TowerJets now possible
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(DWM, SLAC)
Advances in jet resolution using tracking information
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Jet structureJet structure Jet response depends on ftrkJet response depends on ftrk Improvements with ftrk correctionImprovements with ftrk correction
Jet response improved using the charged energy fraction ftrk
ftrk provides information on jet fragmentation, particle content and topology and permits jet energy corrections after all other jet-energy scale corrections are applied
Jet response improved using the charged energy fraction ftrk
ftrk provides information on jet fragmentation, particle content and topology and permits jet energy corrections after all other jet-energy scale corrections are applied
New approach in ATLASNew approach in ATLAS: use tracks to provide additional information on jet compositionTracks improve calorimeter measurements of jet-energy (calibrated in an average way) by accounting for jet-to-jet fluctuations and allowing for energy corrections on a jet-by-jet basis.
New approach in ATLASNew approach in ATLAS: use tracks to provide additional information on jet compositionTracks improve calorimeter measurements of jet-energy (calibrated in an average way) by accounting for jet-to-jet fluctuations and allowing for energy corrections on a jet-by-jet basis.
(Marshall, Columbia U.)
Jets & tracks: improvements and implementation
ftrk response corrections
• Jet resolution– Corrections applied in bins of ftrk – Jet-by-jet fluctuations are reduced– Improvement in overall jet energy
resolution
• Jet resolution– Corrections applied in bins of ftrk – Jet-by-jet fluctuations are reduced– Improvement in overall jet energy
resolution
Improvements to jet-resolution: 10% at 40 GeVImprovements to jet-resolution: 10% at 40 GeV
• Official ATLAS software package integrated into full reconstruction
• Available to all ATLAS users for first data
• Documentation in ATLAS internal note
– ATL-COM-PHYS-2008-074• Used in Higss Z/Wjjγγ analysis
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(Marshall, Columbia U.)
Missing energy applications
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Improvements to jet-energy has implications for missing energy measurements– Integral for both standard model measurements and new physics searches with b-jets
Improvements to jet-energy has implications for missing energy measurements– Integral for both standard model measurements and new physics searches with b-jets
Missing energy using ftrk
Artificial missing energy from pT imbalance is corrected following jet energy corrections
(Schwartzman, SLAC)
Tracks-jets as complementary to calorimeter jets
Calorimeter jets can incorporate particles from multiple interactions
Using track-jets with Z information, can separate interactions
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New approach in ATLASNew approach in ATLASBuild “jets” from tracks in Inner Detector tracker
– Inherently 3D objects (Z, η, φ) unluke calo jets
New approach in ATLASNew approach in ATLASBuild “jets” from tracks in Inner Detector tracker
– Inherently 3D objects (Z, η, φ) unluke calo jets
(Schwartzman, SLAC)
Improved jet-finding efficiency with track-jets
Limited by tracker acceptance Improved efficiency for low-pT
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The use of tracks provides complementary information to calorimetersTrack-jets allow for the measurement of jet reconstruction efficiencyEnergy losses in the inner detector and cryostat decrease calo efficiency but do not affect track-jets
The use of tracks provides complementary information to calorimetersTrack-jets allow for the measurement of jet reconstruction efficiencyEnergy losses in the inner detector and cryostat decrease calo efficiency but do not affect track-jets
Identification of fake missing energy with track-jets
Unmeasured calorimeter jets results in artificial missing energy
• Calibration of hadronic energy incorrect • Using track-jets to pin-point un-reconstructed jets, events with fake missing energy can be removed
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(Majewski, BNL)
Jet-vertex association (JVF)
• Associate standard calorimeter jets to primary vertices using tracks
• Jet-by-jet energy correction for pile-up and jet-selection criterion.
• Improve jet-energy reconstruction, missing energy resolution and primary vertex (PV) selection using this jet-vertex fraction, or JVF.
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JVF measures the fraction of charged particle transverse (track) momentum in each jet from each identified primary vertex in the event.
JVF measures the fraction of charged particle transverse (track) momentum in each jet from each identified primary vertex in the event.
ATLAS detector with pileup
Additional interactions contribute to both jet multiplicity and jet energy
Tevatron techniques using an average correction discount large fluctuations in the form of jets
New approach:New approach: use tracking + calorimeter + vertex information to account for jet origin use tracking + calorimeter + vertex information to account for jet origin
Additional interactions contribute to both jet multiplicity and jet energy
Tevatron techniques using an average correction discount large fluctuations in the form of jets
New approach:New approach: use tracking + calorimeter + vertex information to account for jet origin use tracking + calorimeter + vertex information to account for jet origin
New approach to jet identification in ATLAS
Using JVF to select hard-scatter jets in events with pile-up
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Using JVF we recover the flat jet-multiplicity distribution
without raising the jet pT thresholdIn official ATLAS software and available to all ATLAS users for first dataFully documented in internal ATLAS note: ATL-COM-PHYS-2008-008
Using JVF we recover the flat jet-multiplicity distribution
without raising the jet pT thresholdIn official ATLAS software and available to all ATLAS users for first dataFully documented in internal ATLAS note: ATL-COM-PHYS-2008-008
ttbar events: 1033 cm-2s-1 ttbar events: 2x1033 cm-2s-1
(DWM, SLAC)
Jet-by-jet energy corrections for pile-up contributionsJet energy response vs. JVF: 1033 & 2x1033 cm-2s-1 (ttbar) Jet energy response vs. pT and JVF (ttbar)
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Using JVF to correct jet energies in a luminosity independent manner
Derive jet-energy correction similar to that already done for ftrk to correct jets for pileup contributions on a per jet basisper jet basis
Using JVF to correct jet energies in a luminosity independent manner
Derive jet-energy correction similar to that already done for ftrk to correct jets for pileup contributions on a per jet basisper jet basis
(DWM, SLAC)
Using jet-vertex association to select primary vertices
Improving primary vertex selection in events with multiple interactions
• The high luminsotiy environment in ATLAS will oresent challenges to correct hard-scatter vertex identification
• By using information from reconstructed objects in the event, this selection can be improved
– Extremely important for b-tagging
• New approach in ATLAS• Measure efficiencies in real data
with high-pT lepton tagging
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Muons and JVF tagged correct PV
Jet & μ-tagJet & μ-tag
DefaultDefaultμ
jet
jet
jet
(DWM, SLAC)
Semileptonic b-jet corrections
b-jet response in ttbar events
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Correcting for missing neutrino energy• Jets with constituent ν’s have energies
systematically underestimated by 10%– Use pT
jet and pTμ to parameterize response
– Apply correction in barrel and end cap regions
• In official ATLAS jet reconstruction software
• Available to all users for first data
• Documented in internal ATLAS note: – ATL-COM-PHYS-2008-086(Mateos,
Columbia U.)
Use of semileptonic b-jet correction in ATLAS
Data-driven methods for estimating corrections under way
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Not only will the jet energy scale of b-jets occupy an integral role in many standard model measurements in early data (such as ttbar) but the preponderance of b-jet channels in SUSY and Higgs searches renders it even more important
Not only will the jet energy scale of b-jets occupy an integral role in many standard model measurements in early data (such as ttbar) but the preponderance of b-jet channels in SUSY and Higgs searches renders it even more important
Technique applied in Higgs Working Group H(120 GeV)bbbar analysis
(Mateos, Columbia U.)
Missing energy significance
• Combine known jet resolutions with measured jet energy and missing ET to define a likelihood function that jet energy fluctuations contribute to the missing ET
– Separate true missing ET from fake missing ET
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QCD Events (fake missing ET) W+jets
(real missing ET)
(Perez, Columbia U.)
Summary
• SLAC is providing a coherent yet wide range of contributions to ATLAS Jet/MET performance and physics groups– New approaches to combined detector performance using tracking and
calorimetry– Novel techniques for coping with and correcting for pile-up in the LHC
environment– Coherent approach to maximizing precision jet-energy measurements for
standard model measurements and for new physics searches– Applications to many physics analyses– Extensive documentation in internal ATLAS notes– All methods are available to the ATLAS community for first data
• Several active areas of research and techniques not covered!– Quark/gluon tagging: SUSY jet+MET background reduction– b/c quark-jet separation: b-jet background reduction– Gluon splitting (gluonbbbar) removal: large source of background for
SUSY b-jet+MET– Di-jet resolution measurements in first data
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Outlook and conclusions
• This work has provided many important tools and techniques for understanding the first physics data from ATLAS– Roadmap for jet-energy scale with first data is being planned with this
work at the forefront
– Expect to be heavily involved (lead??) the data-driven approaches to measuring the jet-energy scale and applying these new techniques
– New approach to jet-tower building is expected to aid greatly in understanding the jet response in first data
The tools and methodologies being developed by the SLAC ATLAS group provide users with the capability to select, improve and reject events in his or her own analysis and are already proving useful in both standard model studies as well as physics searches.
July 7, 2008 SLAC Annual Program Review Page 18