Neural Network QCD analysis of charged hadron Fragmentation Functions in the presence of SIDIS data

Abstract

In this paper, we present a QCD analysis to extract the Fragmentation Functions (FFs) of unidentified light charged hadron entitled as SHK22.h from high-energy lepton-lepton annihilation and lepton-hadron scattering data sets. This analysis includes the data from all available single inclusive electron-positron annihilation (SIA) processes and semi-inclusive deep-inelastic scattering (SIDIS) measurements for the unidentified light charged hadron productions. The SIDIS data which has been measured by the COMPASS experiment could allow the flavor dependence of the FFs to be well constrained. We exploit the analytic derivative of the Neural Network (NN) for fitting of FFs at next-to-leading-order (NLO) accuracy in the perturbative QCD (pQCD). The Monte Carlo method is implied for all sources of experimental uncertainties and the Parton distribution functions (PDFs) as well. Very good agreements are achieved between the SHK22.h FFs set and the most recent QCD fits available in literature, namely JAM20 and NNFF1.1h. In addition, we discuss the impact arising from the inclusion of SIDIS data on the extracted light-charged hadron FFs. The global QCD resulting at NLO for charged hadron FFs provides valuable insights for applications in present and future high-energy measurement of charged hadron final state processes.

18 pages, 8 figures, and 1 table

References in corpus (18)

• LHAPDF6: parton density access in the LHC precision era
• Parton-to-Pion Fragmentation Reloaded
• Parton Fragmentation Functions
• Multiplicities of charged pions and kaons from semi-inclusive deep-inelastic scattering by the proton and the deuteron
• A determination of the fragmentation functions of pions, kaons, and protons with faithful uncertainties
• Simultaneous Monte Carlo analysis of parton densities and fragmentation functions
• Nuclear Parton Distributions from Lepton-Nucleus Scattering and the Impact of an Electron-Ion Collider
• Production of light-flavor hadrons in pp collisions at $\sqrt{s}$ = 7 and $\sqrt{s}$ = 13 TeV
• nNNPDF2.0: Quark Flavor Separation in Nuclei from LHC Data
• First Monte Carlo analysis of fragmentation functions from single-inclusive $e^{+}{e}^{-}$ annihilation
• Unbiased determination of DVCS Compton Form Factors
• A determination of unpolarised pion fragmentation functions using semi-inclusive deep-inelastic-scattering data: MAPFF1.0
• $B$-hadron fragmentation functions at next-to-next-to-leading order from global analysis of $e^{+}{e}^{-}$ annihilation data
• ${\Lambda }_c^{+}$ fragmentation functions from pQCD approach and the Suzuki model
• Simultaneous extraction of fragmentation functions of light charged hadrons with mass corrections
• Update of inclusive cross sections of single and pairs of identified light charged hadrons
• First NNLO fragmentation functions of $K_S^0$ and $\Lambda /\bar{\Lambda }$ and their uncertainties in the presence of hadron mass corrections
• Antiproton over proton and K${}^{-}$ over K${}^{+}$ multiplicity ratios at high $z$ in DIS

Cited by in corpus (11)

• Machine Learning and LHC Event Generation
• First simultaneous global QCD analysis of dihadron fragmentation functions and transversity parton distribution functions
• Vector quarkonia at the LHC with JETHAD: A high-energy viewpoint
• Emergence of high-energy dynamics from cascade-baryon detections at the LHC
• Automated calculation of Jet fragmentation at NLO in QCD
• Exotic tetraquarks at the HL-LHC with JETHAD: A high-energy viewpoint
• Triply Heavy $\Omega$ Baryons with JETHAD: A High-Energy Viewpoint
• An analysis of the fragmentation function of gluon at next-to-leading order approximation
• Tetraquark-Jet Systems at the High-Luminosity LHC
• Determination of $K_S^0$ Fragmentation Functions including BESIII Measurements and using Neural Networks
• Study of nuclear corrections on the charged hadron fragmentation functions in a Neural Network global QCD analysis