Pileup Subtraction and Jet Energy Prediction Using Machine Learning

Abstract: In the Large Hardron Collider (LHC), multiple proton-proton collisions cause pileup in reconstructing energy information for a single primary collision (jet). This project aims to select the most important features and create a model to accurately estimate jet energy. Different machine learning methods were explored, including linear regression, support vector regression and decision tree. The best result is obtained by linear regression with predictive features and the performance is improved significantly from the baseline method. Submission history From: Vein Kong [view email][v1] Tue, 15 Dec 2015 08:08:39 GMT (204kb,D)


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