Kinematic variables and feature engineering for particle phenomenology
Roberto Franceschini, Doojin Kim, Kyoungchul Kong, K. Matchev, Myeonghun Park, Prasanth Shyamsundar
Abstract
Kinematic variables are important tools for analyzing collider experiments. This article reviews a variety of such tools, which were designed primarily for the experiments at the Large Hadron Collider, but which have potential uses in other experiments. The article also discusses the interconnection and mutual complementarity of kinematic variables and modern machine-learning techniques.
Topics & Concepts
KinematicsPhysicsPhenomenology (philosophy)Particle physicsLarge Hadron ColliderVariety (cybernetics)Statistical physicsTheoretical physicsClassical mechanicsArtificial intelligenceEpistemologyComputer sciencePhilosophyParticle physics theoretical and experimental studiesHigh-Energy Particle Collisions ResearchParticle Detector Development and Performance