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This project consist of the development and implementation of an alternative noise suppression technique based on energy-density rather than absolute energy to select calorimeter cells. This is a novel idea, proposed originally for the D0 experiment, but has never been studied beforeIntenational Linear Collider Detector. This method has not only the potential to improve the jet energy resolution, but it can also provide an alternative jet reconstruction scheme to validate and cross check results with early data.
The first step is to study different calorimeter density definitions in randomly triggered events (noise only events) and simulated multi-jet events, and to determine an optimal criteria for calorimeter signal selection based on density. The second step is to study the physics performance of density-based jet algorithms and compare them with the standard jet energy reconstruction in ATLAS. Future applications inlcude the development of cluster-level density-based clustering methods for jet sub-structure analysis and calibration.