New tool for kinematic regime estimation in semi-inclusive deep-inelastic scattering

A bstract We introduce a new phenomenological tool based on momentum region indicators to guide the analysis and interpretation of semi-inclusive deep-inelastic scattering measurements. The new tool, referred to as “affinity”, is devised to help visualize and quantify the proximity of any experiment...

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Bibliographic Details
Published in:The journal of high energy physics 2022-04, Vol.2022 (4), p.84-31, Article 84
Main Authors: Boglione, M., Diefenthaler, M., Dolan, S., Gamberg, L., Melnitchouk, W., Pitonyak, D., Prokudin, A., Sato, N., Scalyer, Z.
Format: Article
Language:English
Subjects:
Affinity
Classical and Quantum Gravitation
Deep Inelastic Scattering or Small-X Physics
Elementary Particles
High energy physics
Inelastic scattering
Kinematics
Machine learning
Physics
Physics and Astronomy
PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
Quantum Field Theories
Quantum Field Theory
Quantum Physics
Regular Article - Theoretical Physics
Relativity Theory
Specific QCD Phenomenology
Specific QCD Phenomenology, Deep Inelastic Scattering or Small-X Physics
String Theory
Transverse momentum
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Summary:A bstract We introduce a new phenomenological tool based on momentum region indicators to guide the analysis and interpretation of semi-inclusive deep-inelastic scattering measurements. The new tool, referred to as “affinity”, is devised to help visualize and quantify the proximity of any experimental kinematic bin to a particular hadron production region, such as that associated with transverse momentum dependent factorization. We apply the affinity estimator to existing HERMES and COMPASS data and expected data from Jefferson Lab and the future Electron-Ion Collider. We also provide an interactive notebook based on Machine Learning for fast evaluation of affinity.
ISSN:1029-8479
1029-8479
DOI:10.1007/JHEP04(2022)084