On the Topic of Jets: Disentangling Quarks and Gluons at Colliders
This method addresses the problem of disentangling quark and gluon jets in particle physics experiments, such as at the Large Hadron Collider, by providing a data-driven approach with minimal reliance on simulation or theory.
The authors introduced a framework called 'jet topics' to identify underlying classes of jets from collider data by applying topic modeling techniques, enabling the extraction of separate quark and gluon jet distributions for observables like constituent multiplicity and rapidity spectra from mixed samples.
We introduce jet topics: a framework to identify underlying classes of jets from collider data. Because of a close mathematical relationship between distributions of observables in jets and emergent themes in sets of documents, we can apply recent techniques in "topic modeling" to extract jet topics from data with minimal or no input from simulation or theory. As a proof of concept with parton shower samples, we apply jet topics to determine separate quark and gluon jet distributions for constituent multiplicity. We also determine separate quark and gluon rapidity spectra from a mixed Z-plus-jet sample. While jet topics are defined directly from hadron-level multi-differential cross sections, one can also predict jet topics from first-principles theoretical calculations, with potential implications for how to define quark and gluon jets beyond leading-logarithmic accuracy. These investigations suggest that jet topics will be useful for extracting underlying jet distributions and fractions in a wide range of contexts at the Large Hadron Collider.