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Uncertainties in the parametrization of Parton Distribution Functions (PDFs) are becoming a serious limiting systematic uncertainty in Large Hadron Collider (LHC) searches for Beyond the Standard Model physics. This is especially true for…

High Energy Physics - Experiment · Physics 2019-03-13 Christopher Willis , Raymond Brock , Daniel Hayden , Tie-Jiun Hou , Joshua Isaacson , Carl Schmidt , Chien-Peng Yuan

We present NNPDF3.0, the first set of parton distribution functions (PDFs) determined with a methodology validated by a closure test. NNPDF3.0 uses a global dataset including HERA-II deep-inelastic inclusive cross-sections, the combined…

We introduce a general Monte Carlo method based on Nested Sampling (NS), for sampling complex probability distributions and estimating the normalising constant. The method uses one or more particles, which explore a mixture of nested…

Computation · Statistics 2012-02-27 Brendon J. Brewer , Livia B. Pártay , Gábor Csányi

We implement a Monte Carlo sampling strategy to extract helicity parton densities and their uncertainties from a reference set of longitudinally polarized scattering data, chosen to be that used in the DSSV14 global analysis. Instead of…

High Energy Physics - Phenomenology · Physics 2019-12-25 Daniel de Florian , Gonzalo Agustin Lucero , Rodolfo Sassot , Marco Stratmann , Werner Vogelsang

Modern analysis on parton distribution functions (PDFs) requires calculations of the log-likelihood functions from thousands of experimental data points, and scans of multi-dimensional parameter space with tens of degrees of freedom. In…

High Energy Physics - Phenomenology · Physics 2022-08-24 DianYu Liu , ChuanLe Sun , Jun Gao

We perform the first global QCD analysis of parton distribution functions (PDFs) in the pion, combining $\pi A$ Drell-Yan data with leading neutron electroproduction from HERA within a Monte Carlo approach based on nested sampling.…

High Energy Physics - Phenomenology · Physics 2018-10-17 P. C. Barry , N. Sato , W. Melnitchouk , Chueng-Ryong Ji

Recent high precision experimental data from a variety of hadronic processes opens new opportunities for determination of the collinear parton distribution functions (PDFs) of the proton. In fact, the wealth of information from experiments…

High Energy Physics - Phenomenology · Physics 2018-08-24 Bo-Ting Wang , T. J. Hobbs , Sean Doyle , Jun Gao , Tie-Jiun Hou , Pavel M. Nadolsky , Fredrick I. Olness

We provide an analysis of the x-dependence of the bare unpolarized, helicity and transversity iso-vector parton distribution functions (PDFs) from lattice calculations employing (maximally) twisted mass fermions. The x-dependence of the…

A new and simple statistical approach is performed to calculate the parton distribution functions (PDFs) of the nucleon in terms of light-front kinematic variables. Analytic expressions of x-dependent PDFs are obtained in the whole x…

High Energy Physics - Phenomenology · Physics 2011-04-07 Lijing Shao , Yunhua Zhang , Bo-Qiang Ma

We present the software framework underlying the NNPDF4.0 global determination of parton distribution functions (PDFs). The code is released under an open source licence and is accompanied by extensive documentation and examples. The code…

In the framework of quantum chromodynamics (QCD), parton distribution functions (PDFs) quantify how the momentum and spin of a hadron are divided among its quark and gluon constituents. Two main approaches exist to determine PDFs. The first…

Uncertainty estimation in deep models is essential in many real-world applications and has benefited from developments over the last several years. Recent evidence suggests that existing solutions dependent on simple Gaussian formulations…

Machine Learning · Computer Science 2022-05-11 Jurijs Nazarovs , Ronak R. Mehta , Vishnu Suresh Lokhande , Vikas Singh

The Hessian method is widely applied in the global analysis of parton distribution functions (PDFs), which uses a set of orthogonal eigenvectors to give predictions of a physical observable. Its uncertainty is estimated based on the…

High Energy Physics - Phenomenology · Physics 2025-09-12 Wenxiao Zhan , Siqi Yang , Minghui Liu , Liang Han , Daniel Stump , C. -P. Yuan

We present a first global determination of spin-dependent parton distribution functions (PDFs) and their uncertainties using the NNPDF methodology: NNPDFpol1.1. Longitudinally polarized deep-inelastic scattering data, already used for the…

High Energy Physics - Phenomenology · Physics 2015-06-22 Emanuele R. Nocera , Richard D. Ball , Stefano Forte , Giovanni Ridolfi , Juan Rojo

Discrepancies play an important role in the study of uniformity properties of point sets. Their probability distributions are a help in the analysis of the efficiency of the Quasi Monte Carlo method of numerical integration, which uses…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. F. W. van Hameren

A statistical learning approach for parametric PDEs related to Uncertainty Quantification is derived. The method is based on the minimization of an empirical risk on a selected model class and it is shown to be applicable to a broad range…

Numerical Analysis · Mathematics 2020-01-07 Martin Eigel , Reinhold Schneider , Philipp Trunschke , Sebastian Wolf

We extract pion parton distribution functions (PDFs) in a Monte Carlo global QCD analysis of experimental data together with reduced Ioffe time pseudo-distributions and matrix elements of current-current correlators generated from lattice…

High Energy Physics - Phenomenology · Physics 2022-07-13 P. C. Barry , C. Egerer , J. Karpie , W. Melnitchouk , C. Monahan , K. Orginos , Jian-Wei Qiu , D. Richards , N. Sato , R. S. Sufian , S. Zafeiropoulos

We examine the sources of parton distribution errors in the $W$ mass measurement, and point out shortcomings in the existing literature. Optimistic assumptions about strategies to reduce the error by normalizing to $Z$ observables are…

High Energy Physics - Phenomenology · Physics 2015-08-26 Seth Quackenbush , Zack Sullivan

We present the first global analysis of parton distribution functions (PDFs) at approximate N$^{3}$LO in the strong coupling constant $\alpha_{s}$, extending beyond the current highest NNLO achieved in PDF fits. To achieve this, we present…

High Energy Physics - Phenomenology · Physics 2023-03-14 J. McGowan , T. Cridge , L. A. Harland-Lang , R. S. Thorne

Probabilistic prediction of sequences from images and other high-dimensional data is a key challenge, particularly in risk-sensitive applications. In these settings, it is often desirable to quantify the uncertainty associated with the…

Machine Learning · Computer Science 2024-10-31 Qidong Yang , Weicheng Zhu , Joseph Keslin , Laure Zanna , Tim G. J. Rudner , Carlos Fernandez-Granda
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