Measurement of lepton-jet correlation in deep-inelastic scattering with the H1 detector using machine learning for unfolding

0566752 - FZÚ 2023 RIV US eng J - Článek v odborném periodiku
Andreev, V. - Arratia, M. - Baghdasaryan, A. - Cvach, Jaroslav - Hladký, Jan - Reimer, Petr … celkem 143 autorů
Measurement of lepton-jet correlation in deep-inelastic scattering with the H1 detector using machine learning for unfolding.
Physical Review Letters. Roč. 128, č. 13 (2022), č. článku 132002. ISSN 0031-9007. E-ISSN 1079-7114
Grant CEP: GA MŠMT LG14033
Institucionální podpora: RVO:68378271
Klíčová slova: HERA * deep inelastic scattering * lepton-jet correlation * machine learning
Obor OECD: Particles and field physics
Impakt faktor: 8.6, rok: 2022
Způsob publikování: Open access

The first measurement of lepton-jet momentum imbalance and azimuthal correlation in lepton-proton scattering at high momentum transfer is presented. These data, taken with the H1 detector at HERA, are corrected for detector effects using an unbinned machine learning algorithm(MultiFold), which considers eight observables simultaneously in this first application. The unfolded cross sections are compared to calculations performed within the context of collinear or transverse-momentum-dependent (TMD) factorization in Quantum Chromodynamics (QCD) as well as Monte Carlo event generators.
Trvalý link: https://hdl.handle.net/11104/0338045