1. Performance of jets algorithms in ATLAS
Nikola Makovec
September the 8th, 2009

2. Experimental Requirements for Jet Finders
Detector independence: The performance of the algorithm should be as independent as possible of the detector that provides the data. For example, the algorithm should not be strongly dependent on detector segmentation, energy response, or resolution.
Minimization of resolution smearing and angle biases: The algorithm should not amplify the inevitable effects of resolution smearing and angle biases.
Stability with luminosity: Jet finding should not be strongly affected by multiple hard scatterings at high beam luminosities. For example, jets should not grow to excessively large sizes due to additional interactions. Furthermore the jet angular and energy resolutions should not depend strongly on luminosity.
Efficient use of computer resources: The jet algorithm should provide jet identification with a minimum of computer time. However, changes in the algorithm intended to minimize the necessary computer resources, e.g., the use of seeds and preclustering, can lead to problems in the comparison with theory. In general, it is better to invest in more computer resources instead of distorting the definition of the algorithm.
Maximal reconstruction efficiency: The jet algorithm should efficiently identify all physically interesting jets (i.e., jets arising from the energetic partons described by perturbative QCD).
Ease of calibration: The algorithm should not present obstacles to the reliable calibration of the final kinematic properties of the jet.
Ease of use: The algorithm should be straightforward to implement with typical experimental detectors and data.
Fully specified: Finally, the algorithm must be fully specified. This includes specifications for clustering, energy and angle definition, and all details of jet splitting and merging.
Blazey et al. hep-ex/000501
Nikola Makovec

3. The Atlas Calorimeters
EM Endcap EMEC
EM Barrel EMB
Hadronic Endcap
Forward
Tile Barrel
Tile Extended Barrel
Electromagnetic Barrel
|| < 1.4
Electromagnetic EndCap
1.375 < || < 3.2
Hadronic Tile
|| < 1.7
Hadronic EndCap
1.5 < || < 3.2
Forward Calorimeter
3.2 < || < 4.9
At least 10 interaction lengths
~ channels
Varied granularity Varied technologies Overlap/crack regions
Nikola Makovec

4. Calorimeter Signals: Towers
Regular grid
Δη×Δφ = 0.1×0.1
Calorimeter cell signals are summed up in tower bins
No cell selection, all cells are included
Indiscriminatory signal sum includes cells without any true signal at all
Sum typically includes geometrical weight
Towers have fixed direction given by geometrical grid center
Massless four-momentum representation
projective cells
non-projective
cells
Nikola Makovec

5. Calorimeter Signals: Topological clusters
Attempt reconstruction of individual particle showers
Uses cell signal significance
Electronic
Electronic + pile-up (quadratic sum)
Attempt to suppress noise with least bias on physics signals
Algorithm:
Seeding (S=4)
Cells with signal significance above primary seed threshold
Collecting (P=2)
Directly neighboring cells with signals above basic threshold,
directly neighboring seed cells in 3-dim
Growth control (N=0)
Collect neighbors of neighbors if those have signals above secondary seed significance
Splitting
Find local signal maxima in cluster with
E > 500 MeV
Split cluster between those
Nikola Makovec

6. Calorimeter Signals: TopoTowers
Noise suppressed towers Electromagnetic energy scale signal only
Only cells surviving noise suppression are used in the towers
TopoClusters are used as noise suppression tool
Additional cell filters possible
Nikola Makovec

7. Degrees of freedom Jet algorithm: Inputs: Size: ATLAS seeded cone
SISCone Kt
AntiKt
Inputs:
Truth particles (excluding neutrinos and muons)
Towers
Topocluster
Topotower
Size:
Narrow R=0.4
Wide R=0.6 or 0.7
Nikola Makovec

8. Timing: HLT
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9. Timing: offline
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10. Energy scale and resolution
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11. Efficiency
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12. Purity
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13. Pile-up: multiplicity
Nikola Makovec

14. Pile-up: multiplicity
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15. Pile-up: constituents
Nikola Makovec

16. Pile-up: response
Nikola Makovec

17. Randomly triggered events
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18. Randomly triggered events
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19. Randomly triggered events
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20. Back up
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21. Efficiency The plots are done using QCD MC events [560-1120GeV]
Nikola Makovec

22. Nikola Makovec

23. Pile-up: response
Nikola Makovec

24. Pile-up: response
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25. 75%
Et cut on proto-jet
Dark tower
Nikola Makovec