Measurement of Lepton-Jet Correlation in Deep-Inelastic Scattering with the H1 Detector Using Machine Learning for Unfolding
- Resource Type
- Source
- Physical review letters : PRL 128(13), 132002 (2022). doi:10.1103/PhysRevLett.128.132002
HAL
Physical review letters
Physical Review Letters
Physical Review Letters, 128 (13)
Physical review letters 128(13), 132002 (2022). doi:10.1103/PhysRevLett.128.132002
Phys.Rev.Lett.
Phys.Rev.Lett., 2022, 128 (13), pp.132002. ⟨10.1103/PhysRevLett.128.132002⟩ - Subject
correlation: two-particle electron p: deep inelastic scattering data analysis method neural network FOS: Physical sciences General Physics and Astronomy collinear parton: distribution function transverse momentum dependence High Energy Physics - Experiment energy dependence High Energy Physics - Experiment (hep-ex) High Energy Physics - Phenomenology (hep-ph) statistical analysis factorization quantum chromodynamics [PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex] ddc:530 deep inelastic scattering [positron p] two-particle [correlation] Particle Physics - Phenomenology hep-ex angular correlation positron p: deep inelastic scattering Physics high [momentum transfer] High Energy Physics::Phenomenology hep-ph Monte Carlo [numerical calculations] High Energy Physics - Phenomenology DESY HERA Stor kinematics [PHYS.HPHE]Physics [physics]/High Energy Physics - Phenomenology [hep-ph] deep inelastic scattering [electron p] H1 High Energy Physics::Experiment distribution function [parton] numerical calculations: Monte Carlo Particle Physics - Experiment momentum transfer: high experimental results - Language
- English
- ISSN
- 0031-9007
1079-7114