We present MAPFF1.0_Lambda, the first global analysis at next-to-next-to-leading order in perturbative QCD of the collinear unpolarised fragmentation functions of Lambda hyperons. The fit is based on data from single-inclusive electron-positron annihilation, and from both neutral-current and -- for the first time -- charged-current semi-inclusive deep-inelastic scattering. We have adopted a statistical framework based on Monte Carlo sampling and parametrised fragmentation functions in terms of a neural network. The fragmentation function set comprises a total of seven independent parton flavours, allowing for the first independent determination of valence-quark distributions. Our analysis offers new insights into the hadronisation mechanism of strange baryons and establishes a baseline for future phenomenological and experimental investigations.

We present a new extraction of unpolarized Dihadron Fragmentation Functions, which describe the probability density for an unpolarized parton to fragment into a π+π− pair. Our analysis is based on data from the BELLE collaboration. We improve on previous determinations in several key aspects: we employ state-of-the-art perturbative QCD calculations up to next-to-next-to-leading order (NNLO); we limit the use of Monte Carlo event generators to estimating the relative contributions of different flavors, a necessary input due to the limited flavor sensitivity of the available data; and, in addition to a traditional fit based on a physics-informed functional form, we explore a Neural Network parametrization. This latter approach paves the way for more robust and flexible determinations of Dihadron Fragmentation Functions using machine learning techniques.

We present a first joint extraction of the Collins-Soper kernel (CSK) combining experimental and lattice QCD data in the context of an analysis of transverse-momentum-dependent distributions (TMDs). Based on a neural-network parametrization, we perform a Bayesian reweighting of an existing fit of TMDs using lattice data, as well as a joint TMD fit to lattice and experimental data. We consistently find that the inclusion of lattice information shifts the central value of the CSK by approximately 10% and reduces its uncertainty by 40%-50%, highlighting the potential of lattice inputs to improve TMD extractions.

We present an analytical parametrization of the non-perturbative transverse-momentum-dependent (TMD) parton distribution function of unpolarized quarks, extracted from Drell-Yan data using a combination of neural-network fitting and symbolic regression. A factorized neural network is trained directly against experimental cross-section data from fixed-target, Tevatron, RHIC, and LHC experiments at next-to-next-to-next-to-leading logarithmic accuracy, and symbolic regression is subsequently applied to each network component to discover compact analytical expressions. The final formula is selected from a Pareto front in the space of expression complexity and experimental $χ^2$, yielding a closed-form non-perturbative function with 9 free numerical constants that achieves $χ^2/\mathrm{ndf}=1.040$ over 482 data points. A non-trivial $x$-$b_T$ cross term is retained even under a sparsity prior that biases it toward zero, indicating a mild but genuine correlation between the longitudinal momentum fraction and the transverse momentum. This work demonstrates that symbolic regression is a viable tool for bridging flexible machine-learning fits and interpretable analytical TMD parametrizations, and opens a systematic path toward data-driven discovery of specific features of non-perturbative QCD.

We present the first extraction of the unpolarised gluon transverse-momentum-dependent (TMD) parton distribution from Higgs-boson production data at the LHC within the framework of TMD factorisation. The analysis is based on the currently available set of ATLAS and CMS measurements of the Higgs q_T distribution at √(s) = 8 and 13 TeV in the diphoton and four-lepton decay channels, restricted to the small-q_T region where TMD factorisation is applicable. Theoretical predictions are computed up to N^3LL accuracy, with the contribution of the linearly polarised gluon TMD h_1^⊥ g accounted for. Fiducial selections are consistently incorporated for both two- (diphoton) and four-body (four-lepton) final states. The fit reproduces both the shape and the normalisation of the experimental data, and yields a moderate sensitivity to the nonperturbative content of gluon TMDs. We further assess the convergence of the perturbative expansion and the stability of the extracted distribution under variations of the q_T cut. This analysis provides a baseline for future extractions combining LHC Higgs measurements with other gluon-sensitive processes spanning a broader range of hard scales.

QCD calculations for collider physics make use of perturbative solutions of renormalization group equations. Ambiguities related to these solutions can contribute significantly to systematic uncertainties of theoretical predictions for physical observables. We propose a general method to estimate these systematic effects using techniques inspired by soft-gluon and transverse-momentum resummation approaches. We first discuss the cases of the evolution of strong coupling alpha(s), collinear parton-distribution functions, and transverse-momentum-dependent distributions. We then study the implications for precision observables in hadron-collider processes, such as the deep-inelastic scattering structure functions and the transversemomentum distribution of the lepton pair in Drell-Yan production.

We present the first extraction of transverse-momentum-dependent distributions of unpolarized quarks from experimental Drell-Yan data using neural networks to parametrize their nonperturbative part. We show that neural networks outperform traditional parametrizations providing a more accurate description of data. This Letter establishes the feasibility of using neural networks to explore the multidimensional partonic structure of hadrons and paves the way for more accurate determinations based on machine-learning techniques.

We study relativistic corrections to prompt psi(2S) at high pT in hadron colliders. Our calculation employs leading-power factorization with Fragmentation Functions (FFs) computed in nonrelativistic QCD and evolved to next-to-leading-logarithmic accuracy. Relativistic corrections increase the cross section significantly for the gluon channel, but moderately for charm. We perform a full analysis of uncertainties. We observe a good agreement with both ATLAS and CMS cross sections without the need of higher-order color-octet contributions. The polar anisotropy is found to be close to CMS data.

We present MAPPDFpol1.0, a new determination of the helicity-dependent parton distribution functions (PDFs) of the proton from a set of longitudinally polarised inclusive and semi-inclusive deep-inelastic scattering data. The determination includes next-to-next-to-leading order QCD corrections to both processes, and is carried out in a framework that combines a neural-network parametrisation of PDFs with a Monte Carlo representation of their uncertainties. We discuss the quality of the determination, in particular its dependence on higher-order corrections, on the choice of data set, and on theoretical constraints.

We compute the one-loop correction to the forward matrix element of an off-light-cone bi-local quark correlator characterised by a space-like separation z^2 in the presence of heavy quarks with mass m. This calculation allows us to extract the one-loop matching kernel, necessary to connect quasi- and pseudo-distributions to collinear parton distribution functions (PDFs), accounting for heavy-quark mass effects. Our result is exact in that it includes all powers of z^2m^2 at one loop. In the limit z^2m^2→ 0 , it consistently reduces to the known massless result. We also carry out a numerical implementation of our expressions, which allows us to compute the charm pseudo-distribution of the proton given its PDFs. We finally comment on the quantitative impact of heavy-quark mass corrections.

We present the one-loop matching coefficients necessary to match all of the leading-twist generalised transverse-momentum-dependent distributions (GTMDs) onto generalised parton distributions (GPDs). Matching functions are extracted by computing the first radiative corrections to partonic bilocal correlators with staple-like Wilson lines, as appropriate for high-energy collisions. These correlators are characterised by a transverse displacement and skewed kinematics of external states. Using the proton helicity basis, they are parametrised in terms of GTMDs, which are subsequently related to leading-twist GPDs. Our results provide new insights into the complex dynamics of GTMDs generated by radiative corrections. In particular, we show that time-reversal even and odd contributions to GTMDs in the so-called ERBL region mix both under matching and evolution. Finally, we present a selection of numerical results and comment on the quantitative behaviour of GTMDs.

The approximate SACOT-chi scheme for heavy quark production in deep-inelastic scattering was initially formulated for the neutral current structure functions F2 and FL. We extend this approach to the charged current case (also including F3), and thereby complete the definitions for the most relevant inclusive structure functions. Furthermore, we implement these structure functions in the open-source code APFEL++ which provides fast numerical evaluations over a wide kinematic range; this addition to the APFEL++ code is publicly available, with details provided in the Appendix. This SACOT-chi implementation enables detailed numerical insights on the mass dependence of the structure functions and cross sections in the (x; Q2)-plane for both neutral and charged current processes. We consider kinematic regions relevant for the experimental measurements from fixed-target nu DIS experiments (NuTeV, CCFR, and Chorus) and HERA, and also projections for the upcoming EIC. In particular, the nu DIS experiments reveal a surprisingly strong dependence on the mass effects, offering valuable insights that may help resolve long-standing challenges in accurately describing these datasets.

We present a benchmark comparison of the massless inclusive deep-inelastic-scattering (DIS) structure functions up to 𝒪(α _s ^3) in perturbative QCD. The comparison is performed using the codes apfel++ and hoppet within the framework of the variable-flavour-number scheme and over a broad kinematic range relevant to the extraction of parton distribution functions. We provide results for both the single structure functions and the reduced cross sections in both neutral- and charged-current DIS. Look-up tables for future reference are included, and we also release the code used for the benchmark.

This document presents the initial scientific case for upgrading the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab (JLab) to 22 GeV. It is the result of a community effort, incorporating insights from a series of workshops conducted between March 2022 and April 2023. With a track record of over 25 years in delivering the world's most intense and precise multi-GeV electron beams, CEBAF's potential for a higher energy upgrade presents a unique opportunity for an innovative nuclear physics program, which seamlessly integrates a rich historical background with a promising future. The proposed physics program encompass a diverse range of investigations centered around the nonperturbative dynamics inherent in hadron structure and the exploration of strongly interacting systems. It builds upon the exceptional capabilities of CEBAF in high-luminosity operations, the availability of existing or planned Hall equipment, and recent advancements in accelerator technology. The proposed program cover various scientific topics, including Hadron Spectroscopy, Partonic Structure and Spin, Hadronization and Transverse Momentum, Spatial Structure, Mechanical Properties, Form Factors and Emergent Hadron Mass, Hadron-Quark Transition, and Nuclear Dynamics at Extreme Conditions, as well as QCD Confinement and Fundamental Symmetries. Each topic highlights the key measurements achievable at a 22 GeV CEBAF accelerator. Furthermore, this document outlines the significant physics outcomes and unique aspects of these programs that distinguish them from other existing or planned facilities. In summary, this document provides an exciting rationale for the energy upgrade of CEBAF to 22 GeV, outlining the transformative scientific potential that lies within reach, and the remarkable opportunities it offers for advancing our understanding of hadron physics and related fundamental phenomena.

Abstract We present an extraction of the unpolarized transverse-momentum-dependent parton distribution and fragmentation functions that takes into account possible differences between quark flavors and final-state hadrons. The extraction is based on experimental measurements from Drell-Yan processes and semi-inclusive deep-inelastic scattering, whose combination is essential to distinguish flavor differences. The analysis is carried out at N3LL accuracy. The extracted flavor-dependent distributions give a very good description of the data (χ2/Ndat = 1.08). The resulting error bands take fully into account also the uncertainties in the determination of the corresponding collinear distributions.

Abstract We present a benchmark comparison of the massless inclusive deep-inelastic-scattering (DIS) structure functions up to $$\mathcal {O}(\alpha _s ^3)$$ O ( α s 3 ) in perturbative QCD. The comparison is performed using the codes apfel++ and hoppet within the framework of the variable-flavour-number scheme and over a broad kinematic range relevant to the extraction of parton distribution functions. We provide results for both the single structure functions and the reduced cross sections in both neutral- and charged-current DIS. Look-up tables for future reference are included, and we also release the code used for the benchmark.

We discuss hysteresis effects in the perturbative solution of renormalization group equations for the strong coupling and parton distribution functions, and study their impact on precision determinations of proton's deep-inelastic structure functions $F_2$ and $F_L$.