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

Abstract

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.

Authors:
 [1];  [2];  [3];  [3];  [2];  [4]; ORCiD logo [5];  [2];  [6]
  1. Univ. of Torino (Italy)
  2. Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)
  3. Pennsylvania State Univ. Berks, Reading, PA (United States)
  4. Lebanon Valley College, Annville, PA (United States)
  5. Pennsylvania State Univ. Berks, Reading, PA (United States); Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Temple Univ., Philadelphia, PA (United States)
  6. Pennsylvania State Univ. Berks, Reading, PA (United States); Prepared for Flight, LLC, York, PA (United States)
Publication Date:
Research Org.:
Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Pennsylvania State Univ. Berks, Reading, PA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Nuclear Physics (NP); National Science Foundation (NSF); European Union (EU)
Contributing Org.:
JAM Collaboration
OSTI Identifier:
1863933
Alternate Identifier(s):
OSTI ID: 1887742
Report Number(s):
JLAB-THY-22-3550; DOE/OR/23177-5409; arXiv:2201.12197
Journal ID: ISSN 1029-8479; TRN: US2305676
Grant/Contract Number:  
AC05-06OR23177; FG02-07ER41460; PHY-2011763; PHY-2012002; 824093
Resource Type:
Accepted Manuscript
Journal Name:
Journal of High Energy Physics (Online)
Additional Journal Information:
Journal Name: Journal of High Energy Physics (Online); Journal Volume: 2022; Journal Issue: 4; Journal ID: ISSN 1029-8479
Publisher:
Springer Nature
Country of Publication:
United States
Language:
English
Subject:
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; specific QCD phenomenology; deep inelastic scattering or small-x physics; Specific QCD Phenomenology, Deep Inelastic Scattering or Small-X Physics

Citation Formats

Boglione, M., Diefenthaler, M., Dolan, S., Gamberg, L., Melnitchouk, W., Pitonyak, D., Prokudin, Alexei, Sato, N., and Scalyer, Z. New tool for kinematic regime estimation in semi-inclusive deep-inelastic scattering. United States: N. p., 2022. Web. doi:10.1007/jhep04(2022)084.
Boglione, M., Diefenthaler, M., Dolan, S., Gamberg, L., Melnitchouk, W., Pitonyak, D., Prokudin, Alexei, Sato, N., & Scalyer, Z. New tool for kinematic regime estimation in semi-inclusive deep-inelastic scattering. United States. https://doi.org/10.1007/jhep04(2022)084
Boglione, M., Diefenthaler, M., Dolan, S., Gamberg, L., Melnitchouk, W., Pitonyak, D., Prokudin, Alexei, Sato, N., and Scalyer, Z. Thu . "New tool for kinematic regime estimation in semi-inclusive deep-inelastic scattering". United States. https://doi.org/10.1007/jhep04(2022)084. https://www.osti.gov/servlets/purl/1863933.
@article{osti_1863933,
title = {New tool for kinematic regime estimation in semi-inclusive deep-inelastic scattering},
author = {Boglione, M. and Diefenthaler, M. and Dolan, S. and Gamberg, L. and Melnitchouk, W. and Pitonyak, D. and Prokudin, Alexei and Sato, N. and Scalyer, Z.},
abstractNote = {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.},
doi = {10.1007/jhep04(2022)084},
journal = {Journal of High Energy Physics (Online)},
number = 4,
volume = 2022,
place = {United States},
year = {Thu Apr 14 00:00:00 EDT 2022},
month = {Thu Apr 14 00:00:00 EDT 2022}
}

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