Measuring QCD Splittings with Invertible Networks

Understand

QCD splittings are among the most fundamental theory concepts at the LHC.

• We show how they can be studied systematically with the help of invertible neural networks.
• These networks work with sub-jet information to extract fundamental parameters from jet samples.
• Our approach expands the LEP measurements of QCD Casimirs to a systematic test of QCD properties based on low-level jet observables.