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

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

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 ~200000 channels Varied granularity Varied technologies Overlap/crack regions Nikola Makovec

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

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

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

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

Timing: HLT Nikola Makovec

Timing: offline Nikola Makovec

Energy scale and resolution Nikola Makovec

Efficiency Nikola Makovec

Purity Nikola Makovec

Pile-up: multiplicity Nikola Makovec

Pile-up: multiplicity Nikola Makovec

Pile-up: constituents Nikola Makovec

Pile-up: response Nikola Makovec

Randomly triggered events Nikola Makovec

Randomly triggered events Nikola Makovec

Randomly triggered events Nikola Makovec

Back up Nikola Makovec

Efficiency The plots are done using QCD MC events [560-1120GeV] Nikola Makovec

Nikola Makovec

Pile-up: response Nikola Makovec

Pile-up: response Nikola Makovec

75% Et cut on proto-jet Dark tower Nikola Makovec