Transcript Jet Reconstruction in Athena

Jet Reconstruction and Calibration in Athena
US ATLAS Software Workshop
BNL, 27/08/03
Ambreesh Gupta, for the JetRec Group
University of Chicago
Outline:
• Jet Reconstruction Setup and Algorithms
• Jet Calibration
• Some Highlights from JetRec Meeting in Barcelona.
Jet Physics at Hadron Colliders
Final state partons produce
a collimated jet of particles.
An ideal algorithm will map
jets with final state partons.
Jet algorithms sensitive to
experimental and theoretical
uncertainty.
The Steps of Jet Measurement
Jet Measurement can be broadly divided in three steps
Jet Reconstruction
Energy deposit in the calorimeter is clustered by Jet
reconstruction algorithms, e.g Cone and Kt.
Energy Calibration
Energy of a Jet is calibrated for non-compensation,
dead material, magnetic field, etc.
Flavor Identification
b-tag, -tag, etc.
Jet Algorithms
Jet algorithms have two steps
Clustering hadrons, calorimeter tower etc.,
for “nearness”
Nearness in Angle => Cone Algorithm
Nearness in Momentum => Kt Algorithm
Recombination Scheme is the momentum
addition rule for the set of particles that
have been identified with a jet.
KT jet
Cone jet
• 4-vector addition
• Snow mass scheme
•...
Jet Reconstruction Packages
Many Kind of
Input Data
Abstract The
Inputs For Algs
Many Kind of
Algorithms
CalCell
Cone
CaloTower
Kt Cluster
CaloCluster
Tracks
Energy Flow
MC Truth
ProtoJet
…..
ProtoJet Class:
. Can be created for different
sub system.
. Homogenous.
Writing Multiple Jets to the N-tuple
CaloTower ProtoJet
Truth Particle ProtoJet
Cone Algorithm
Seed less Cone
Pre-Cluster
Split-Merge
Kt Algorithm
All algorithms can be
configured to run in
the same job
CBNT
ParticleInJet
Multiple algorithm
output can be stored
with different names
Jet Samples Used
The results reported use the following two samples
- Multi-jet sample produced with different Pt cut values
( 35,70,.., 540 GeV)
-SUSY data challenge sample. Run 002315.
Comparing Jet Multiplicity
Mean = 5.7
Cone
Mean = 5.6
K
T
Mean = 6.0
Number of Jets
Seed Less
Cone
Comparing Jet Transverse Energy
Mean = 114 GeV
Mean = 118 GeV
Cone
K
T
Mean = 126 GeV
Transverse Energy
Seed Less
Cone
Reconstructed jet energy
In bins if true energy at
eight energy points.
Good fits to gaussians.
Jet Energy Calibration
To account for non-compensation, dead material etc.,
- H1 scheme (Implemented by Frank Paige)
- Sampling based corrections (in development)
Jet Reconstruction
Algorithms
Energy Correction
Algorithms
Sampling Based
Correction
Cone
Kt Cluster
…..
Jet
Jet
H1 Style
Correction
Navigating Composite Objects
Jet algorithms work with abstractions like ProtoJet. In order to do
energy correction, the navigating the composition of Jet needed.
Jet
PJet
PJet
JetToken
PJetToken
PJet
TowerTower
Cell Cell
Cell
TowerToken
CellToken
H1 Calibration
• H1 Strategy: EM showers are much denser than hadronic ones.
Weight high E cell with EM scale and low E cell with hadronic scale.
• H1 weights derived from di-jet samples. Same weights improve
missing Et resolution.
Jet Calibration: Further developments
Further studies to develop tools for calculating and storing weights.
- requires reading large number (~100K) of jets
- calculate weights (interface to a minimizer)
- store the weights to be accessed for calibration.
Sampling based weights
- calculated in different eta region of the detector.
- first set of weights obtained. Not yet in accessible in Athena.
Sampling based Correction
Evolution of JetRec: Barcelona Meeting
• Since, the last JetRec working group meeting in Tucson (Aug
2001), a lot of progress made in Jet reconstruction software.
• Another working group meeting was held in Barcelona ( July
2003 ) to review the RTF recommendations. Attended by
Present: Frank Merritt, Tom LeCompte, Peter Loch, Srini
Rajagopalan, Martine Bosman.
By Phone: F. Paige, D. Cavalli, S. Resconi, D. Rousseau, A. Gupta,
S. George, P. Calafiura.
• Initial draft of meeting report can be found at JetRec meetings
minutes web-page ( date: 30th of July)
Barcelona Meeting: Highlights
• EnergyCluster class will replace the existing ProtoJet class.
The nature of abstraction remains the same, as far as Jet
algorithms are concerned, but it conforms to the general Athena
reconstruction setup and hence will utilize common services.
• The Jet Data Objects will conform to the general Athena scheme
to navigate composite objects.
• Associating information with Jets, e.g, tracks in jet, will be
provided by extending the present Jet class interface with the
help of a templated method for the type of association requested.
Summary
• Jet Reconstruction packages are in fully functional state.
• There have been various user feedback using dc1 dataset
– bugs hunted and fixed.
• With the availability of “noise” and “pileup”, a more realistic
test of jet algorithms possible.
• RTF recommendations reviewed at Barcelona meeting.
Structural changes proposed to conform with general Athena
reconstruction setup.