Related papers: Reweighting NNPDFs: the W lepton asymmetry
We present a set of parton distribution functions (PDFs), based on the NNPDF2.3 set, which includes a photon PDF, and QED contributions to parton evolution. We describe the implementation of the combined QCD+QED evolution in the NNPDF…
We present a new set of parton distributions, NNPDF3.1, which updates NNPDF3.0, the first global set of PDFs determined using a methodology validated by a closure test. The update is motivated by recent progress in methodology and available…
The reweighting procedure that using Bayesian statistics incorporates the information contained in a new data set, without the need of re-fitting, is applied to the quark Sivers function extracted from Semi-Inclusive Deep Inelastic…
We discuss how the experimental information from longitudinal single-spin asymmetries for $W^{\pm}$ boson production in polarised proton-proton collisions can be included in a polarised parton determination by Bayesian reweighting of a…
The use of QCD calculations that include the resummation of soft-collinear logarithms via parton-shower algorithms is currently not possible in PDF fits due to the high computational cost of evaluating observables for each variation of the…
We discuss the Hessian PDF reweighting - a technique intended to estimate the effects that new measurements have on a set of PDFs. The method stems straightforwardly from considering new data in a usual $\chi^2$-fit and it naturally…
We investigate the feasibility of constraining parton distribution functions in the proton through a comparison with data on semi-inclusive deep-inelastic lepton-nucleon scattering. Specifically, we reweight replicas of these distributions…
The NNPDF collaboration has recently presented NNPDF3.1, a new determination of the parton distribution functions (PDFs) of the proton including a number of new data, some of which are particularly sensitive to the gluon PDF at large x. In…
In global analyses of nuclear parton distribution functions (nPDFs), neutrino deep-inelastic scattering (DIS) data have been argued to exhibit tensions with the data from charged-lepton DIS. Using the nCTEQ framework, we investigate these…
We analyse a tension between the D0 and CDF inclusive jet data and the perturbative QCD calculations, which are based on the ABKM09 and ABM11 parton distribution functions (PDFs) within the nuisance parameter framework. Particular attention…
Learning in weight spaces, where neural networks process the weights of other deep neural networks, has emerged as a promising research direction with applications in various fields, from analyzing and editing neural fields and implicit…
We report on an analysis of the impact of available experimental data on hard processes in proton-lead collisions during Run I at the Large Hadron Collider on nuclear modifications of parton distribution functions. Our analysis is…
We discuss the statistical properties of parton distributions within the framework of the NNPDF methodology. We present various tests of statistical consistency, in particular that the distribution of results does not depend on the…
A re-analysis of the NMC and SLAC data leads to a great improvement in our knowledge of the valence d and u parton distribution functions at high x. Standard parton distributions with our modifications are in good agreement with QCD…
A new combined next to leading order QCD analysis of the polarized inclusive and semi-inclusive deep inelastic lepton-hadron scattering (DIS) data is presented. In contrast to previous combined analyses, the $1/Q^2$ terms (kinematic -…
Imbalanced data pose challenges for deep learning based classification models. One of the most widely-used approaches for tackling imbalanced data is re-weighting, where training samples are associated with different weights in the loss…
We consider the generic problem of performing a global fit to many independent data sets each with a different overall multiplicative normalization uncertainty. We show that the methods in common use to treat multiplicative uncertainties…
The precise knowledge of parton distribution functions (PDFs) is indispensable to the accurate calculation of hadron-initiated QCD hard scattering observables. Much of our information on PDFs is extracted by comparing deep inelastic…
In this contribution we briefly report on the progress and open problems in parton distribution functions (PDFs), with emphasis on their implications for LHC phenomenology. Then we study the impact of the recent ATLAS and CMS W lepton…
We present a new regression model for the determination of parton distribution functions (PDF) using techniques inspired from deep learning projects. In the context of the NNPDF methodology, we implement a new efficient computing framework…