More QCD Masterclass Lectures on Jet Physics and Machine Learning
Andrew J. Larkoski
Abstract
These lectures were presented at the 2026 QCD Masterclass in Saint-Jacut-de-la-mer, France. They supplement the published notes from the 2024 school with presentation of a few new topics that have become popular in recent years. These include event metrics, anomaly detection, scaling laws, the limits of classification performance, and regression that respects spacetime symmetries. Many of the presented results are known, but some new results are derived, especially related to anomaly detection. As was the case in those original notes, while all these problems are motivated from machine learning applied to QCD, no discussion of details of machine learning is presented in these notes. All results follow from application of fundamental principles of QCD. I begin these notes with an apology for humanist physics.
Create a lesson
Related papers
Electromagnetic form factors of vector mesons in Einstein-dilaton holographic QCD
Alfonso Ballon-Bayona, Tobias Frederico, Luis A. H. Mamani et al.
An invertible map between 3D Breit-frame mechanical distributions and 2D infinite-momentum-frame mechanical densities in spin-1 hadrons
Kemal Tezgin
Adiabatic hydrodynamization with transverse spatial gradients in boost-invariant plasmas
Uri Sharell, Jasmine Brewer, Weiyao Ke
Line shapes of Ω(2012) production in the Ξ K and Ξπ K decay channels
Natsumi Ikeno, Eulogio Oset
A quantum representation of π fragmentation functions through variational quantum circuits
David F. Rentería-Estrada, Roger J. Hernández-Pinto, Germán Rodrigo et al.
Particle Physics Driven by Quantum Technology - Quantum Simulations and Quantum Sensing
Itay M. Bloch, Marcela Carena, Yifan Chen et al.