Impact of jet-production data on the next-to-next-to-leading-order determination of HERAPDF2.0 parton distributions

The HERAPDF2.0 ensemble of parton distribution functions (PDFs) was introduced in 2015. The final stage is presented, a next-to-next-to-leading-order (NNLO) analysis of the HERA data on inclusive deep inelastic ep scattering together with jet data as published by the H1 and ZEUS collaborations. A perturbative QCD fit, simultaneously of αs(M2Z) and the PDFs, was performed with the result αs(M2Z)=0.1156±0.0011 (exp) +0.0001−0.0002 (model +parameterisation) ±0.0029 (scale). The PDF sets of HERAPDF2.0Jets NNLO were determined with separate fits using two fixed values of αs(M2Z), αs(M2Z)=0.1155 and 0.118, since the latter value was already chosen for the published HERAPDF2.0 NNLO analysis based on HERA inclusive DIS data only. The different sets of PDFs are presented, evaluated and compared. The consistency of the PDFs determined with and without the jet data demonstrates the consistency of HERA inclusive and jet-production cross-section data. The inclusion of the jet data reduced the uncertainty on the gluon PDF. Predictions based on the PDFs of HERAPDF2.0Jets NNLO give an excellent description of the jet-production data used as input

Measurement of the charm and beauty structure functions using the H1 vertex detector at HERA

Inclusive charm and beauty cross sections are measured in e − p and e + p neutral current collisions at HERA in the kinematic region of photon virtuality 5≤Q 2≤2000 GeV2 and Bjorken scaling variable 0.0002≤x≤0.05. The data were collected with the H1 detector in the years 2006 and 2007 corresponding to an integrated luminosity of 189 pb−1. The numbers of charm and beauty events are determined using variables reconstructed by the H1 vertex detector including the impact parameter of tracks to the primary vertex and the position of the secondary vertex. The measurements are combined with previous data and compared to QCD predictions

Study of Charm Fragmentation into D^{*\pm} Mesons in Deep-Inelastic Scattering at HERA

The process of charm quark fragmentation is studied using $D^{*\pm}$ meson production in deep-inelastic scattering as measured by the H1 detector at HERA. Two different regions of phase space are investigated defined by the presence or absence of a jet containing the $D^{*\pm}$ meson in the event. The parameters of fragmentation functions are extracted for QCD models based on leading order matrix elements and DGLAP or CCFM evolution of partons together with string fragmentation and particle decays. Additionally, they are determined for a next-to-leading order QCD calculation in the fixed flavour number scheme using the independent fragmentation of charm quarks to $D^{*\pm}$ mesons.Comment: 33 pages, submitted to EPJ

Unbinned Deep Learning Jet Substructure Measurement in High Q2Q^2 ep collisions at HERA

The radiation pattern within high energy quark- and gluon-initiated jets (jet substructure) is used extensively as a precision probe of the strong force as well as an environment for optimizing event generators with numerous applications in high energy particle and nuclear physics. Looking at electron-proton collisions is of particular interest as many of the complications present at hadron colliders are absent. A detailed study of modern jet substructure observables, jet angularities, in electron-proton collisions is presented using data recorded using the H1 detector at HERA. The measurement is unbinned and multi-dimensional, using machine learning to correct for detector effects. All of the available reconstructed object information of the respective jets is interpreted by a graph neural network, achieving superior precision on a selected set of jet angularities. Training these networks was enabled by the use of a large number of GPUs in the Perlmutter supercomputer at Berkeley Lab. The particle jets are reconstructed in the laboratory frame, using the $k_{\mathrm{T}}$ jet clustering algorithm. Results are reported at high transverse momentum transfer $Q^2>150$ GeV${}^2$, and inelasticity $0.2 < y < 0.7$. The analysis is also performed in sub-regions of $Q^2$, thus probing scale dependencies of the substructure variables. The data are compared with a variety of predictions and point towards possible improvements of such models.Comment: 33 pages, 10 figures, 8 table