Exclusive cone jet algorithms for high energy particle colliders

Abstract

In this thesis, I develop an exclusive cone jet algorithm based on the principles of jet substructure and demonstrate its use for physics analyses at the Large Hadron Collider. Based on the event shape N-jettiness, this algorithm, called "XCone," partitions the event into a fixed number of conical jets of size RO in the rapidity-azimuth plane. This algorithm is designed to locate substructure independent of momentum, allowing accurate resolution of jets at both low and high energy scales. I present three potential analyses using XCone to search for heavy resonances, Higgs bosons, and top quarks at various momenta and show that it reconstructs these particles with efficiencies between 60% and 80% without any additional substructure techniques, and maintains this efficiency over a wide kinematic range. This algorithm provides many key advantages over traditional jet algorithms that make it appealing for use at the LHC and other high energy particle colliders.