2014/02/28 by Timothy Cohen, Martin Jankowiak, Mariangela Lisanti +2
Engineering · Mathematics · Physics and Astronomy · #Classical mechanics #Computer science #Engineering #Function (biology) #High-Energy Particle Collisions Research #Jet (fluid) #Kinematics #Large Hadron Collider #Mathematics #Mechanics #Monte Carlo method #Particle physics #Particle physics theoretical and experimental studies #Physics #Quantum Chromodynamics and Particle Interactions #Quantum chromodynamics #Statistical physics #Statistics #Substructure #Template #hep-ex #hep-ph
paper · pdf · doi:10.1007/jhep05(2014)005
v2: 24 pages plus appendices, 11 figures, journal version
openalex publication_date 2014/05/01 · arxiv created 2014/10/20 · arxiv updated 2014/10/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
QCD is often the dominant background to new physics searches for which jet substructure provides a useful handle. Due to the challenges associated with modeling this background, data-driven approaches are necessary. This paper presents a novel method for determining QCD predictions using templates — probability distribution functions for jet substructure properties as a function of kinematic inputs. Templates can be extracted from a control region and then used to compute background distributions in the signal region. Using Monte Carlo, we illustrate the procedure with two case studies and show that the template approach effectively models the relevant QCD background. This work strongly motivates the application of these techniques to LHC data.