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

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

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(MZ2) and the PDFs, was performed with the result αs(MZ2)=0.1156±0.0011(exp)-0.0002+0.0001(model+parameterisation)±0.0029(scale). The PDF sets of HERAPDF2.0Jets NNLO were determined with separate fits using two fixed values of αs(MZ2), αs(MZ2)=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

Unbinned deep learning jet substructure measurement in high Q 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 kT jet clustering algorithm. Results are reported at high transverse momentum transfer Q2&gt;150GeV2, and inelasticity 0.

Measurement of Lepton-Jet Correlation in Deep-Inelastic Scattering with the H1 Detector Using Machine Learning for Unfolding

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 with calculations performed within the context of collinear or transverse-momentum-dependent factorization in quantum chromodynamics as well as Monte&nbsp;Carlo event generators

Determination of the strong coupling constant alpha(s) (m(Z)) in next-to-next-to-leading order QCD using H1 jet cross section measurements (vol 77, 791, 2017)

Abstract The determination of the strong coupling constant $$\alpha _{\mathrm{s}} (m_{\mathrm{Z}})$$ α s ( m Z ) from H1 inclusive and dijet cross section data [1] exploits perturbative QCD predictions in next-to-next-to-leading order (NNLO) [2–4]. An implementation error in the NNLO predictions was found [4] which changes the numerical values of the predictions and the resulting values of the fits. Using the corrected NNLO predictions together with inclusive jet and dijet data, the strong coupling constant is determined to be $$\alpha _{\mathrm{s}} (m_{\mathrm{Z}}) =0.1166\,(19)_{\mathrm{exp}}\,(24)_{\mathrm{th}}$$ α s ( m Z ) = 0.1166 ( 19 ) exp ( 24 ) th . Complementarily, $$\alpha _{\mathrm{s}} (m_{\mathrm{Z}})$$ α s ( m Z ) is determined together with parton distribution functions of the proton (PDFs) from jet and inclusive DIS data measured by the H1 experiment. The value $$\alpha _{\mathrm{s}} (m_{\mathrm{Z}}) =0.1147\,(25)_{\mathrm{tot}}$$ α s ( m Z ) = 0.1147 ( 25 ) tot obtained is consistent with the determination from jet data alone. Corrected figures and numerical results are provided and the discussion is adapted accordingly

Measurement of exclusive π+π- and ρ meson photoproduction at HERA: H1 Collaboration

Exclusive photoproduction of ρ(770) mesons is studied using the H1 detector at the ep collider HERA. A sample of about 900,000 events is used to measure single- and double-differential cross sections for the reaction γp→ π+π-Y. Reactions where the proton stays intact (mY= mp) are statistically separated from those where the proton dissociates to a low-mass hadronic system (mp<mY<10GeV). The double-differential cross sections are measured as a function of the invariant mass mππ of the decay pions and the squared 4-momentum transfer t at the proton vertex. The measurements are presented in various bins of the photon–proton collision energy Wγp. The phase space restrictions are 0.5≤mππ≤2.2GeV, |t|≤1.5GeV2, and 20≤Wγp≤80GeV. Cross section measurements are presented for both elastic and proton-dissociative scattering. The observed cross section dependencies are described by analytic functions. Parametrising the mππ dependence with resonant and non-resonant contributions added at the amplitude level leads to a measurement of the ρ(770) meson mass and width at mρ=770.8-2.7+2.6(tot.)MeV and Γρ=151.3-3.6+2.7(tot.)MeV, respectively. The model is used to extract the ρ(770) contribution to the π+π- cross sections and measure it as a function of t and Wγp. In a Regge asymptotic limit in which one Regge trajectory α(t) dominates, the intercept α(t=0)=1.0654-0.0067+0.0098(tot.) and the slope α′(t=0)=0.233-0.074+0.067(tot.)GeV-2 of the t dependence are extracted for the case mY= mp