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相关论文: Parton Distribution Function Uncertainties

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Goals for planning problems are typically conceived of as subsets of the state space. However, for many practical planning problems in robotics, we expect the robot to predict goals, e.g. from noisy sensors or by generalizing learned models…

机器人学 · 计算机科学 2025-07-01 Adam Conkey , Tucker Hermans

Sets of parton distribution functions (PDFs) of the proton are reported for the leading (LO), next-to-leading (NLO) and next-to-next-to leading order (NNLO) QCD calculations. The parton distribution functions are determined with the…

We propose a novel distribution-free scheme to solve optimization problems where the goal is to minimize the expected value of a cost function subject to probabilistic constraints. Unlike standard sampling-based methods, our idea consists…

最优化与控制 · 数学 2025-05-28 Francesco Cordiano , Matin Jafarian , Bart De Schutter

Polarized parton distribution functions are determined by using world data from the longitudinally polarized deep inelastic scattering experiments. A new parametrization of the parton distribution functions is adopted by taking into account…

高能物理 - 唯象学 · 物理学 2014-11-17 Y. Goto , N. Hayashi , M. Hirai , H. Horikawa , S. Kumano , M. Miyama , T. Morii , N. Saito , T. -A. Shibata , E. Taniguchi , T. Yamanishi

We review various methods used to estimate uncertainties in quantum correlation functions, such as parton distribution functions (PDFs). Using a toy model of a PDF, we compare the uncertainty estimates yielded by the traditional Hessian and…

高能物理 - 唯象学 · 物理学 2022-08-17 N. T. Hunt-Smith , A. Accardi , W. Melnitchouk , N. Sato , A. W. Thomas , M. J. White

A survey is given on the present knowledge of the polarized parton distribution functions. We give an outlook for further developments desired both on the theoretical as well on the experimental side to complete the understanding of the…

高能物理 - 唯象学 · 物理学 2007-08-13 Johannes Blümlein

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…

高能物理 - 唯象学 · 物理学 2017-11-29 Ignacio Borsa , Rodolfo Sassot , Marco Stratmann

Transverse momentum dependent parton distribution functions are a key ingredient in the description of spin and azimuthal asymmetries in deep-inelastic scattering processes. Recent results from non-perturbative calculations in effective…

高能物理 - 唯象学 · 物理学 2010-02-04 H. Avakian , A. V. Efremov , P. Schweitzer , O. V. Teryaev , F. Yuan , P. Zavada

The notion of probability density for a random function is not as straightforward as in finite-dimensional cases. While a probability density function generally does not exist for functional data, we show that it is possible to develop the…

统计理论 · 数学 2010-03-01 Aurore Delaigle , Peter Hall

Obtaining Compton Form Factors (CFFs) and Transverse Momentum Dependent parton distribution functions (TMDs) from experimental data using neural network-based information extraction requires the precise propagation of experimental errors.…

高能物理 - 唯象学 · 物理学 2025-09-16 Dustin Keller

In this paper a class of optimization problems with uncertain linear constraints is discussed. It is assumed that the constraint coefficients are random vectors whose probability distributions are only partially known. Possibility theory is…

最优化与控制 · 数学 2021-11-30 Romain Guillaume , Adam Kasperski , Pawel Zielinski

We discuss the determination of polarized parton distributions from charged-current deep-inelastic scattering experiments. We summarize the next-to-leading order treatment of charged-current polarized structure functions, their relation to…

高能物理 - 唯象学 · 物理学 2009-10-08 Stefano Forte , Michelangelo L. Mangano , Giovanni Ridolfi

The capabilities of a neutrino factory in the determination of polarized parton distributions from charged-current deep-inelastic scattering experiments is discussed. We present a study of the accuracy in the determination of polarized…

高能物理 - 唯象学 · 物理学 2009-11-07 G. Ridolfi

Given additional distributional information in the form of moment restrictions, kernel density and distribution function estimators with implied generalised empirical likelihood probabilities as weights achieve a reduction in variance due…

统计方法学 · 统计学 2019-10-08 Vitaliy Oryshchenko , Richard J. Smith

The parton distributions functions (PDFs) derived from the NNLO QCD analysis of existing light-targets deep-inelastic-scattering data are presented. The NLO and NNLO PDFs are compared in order to analyze perturbative stability of the…

高能物理 - 唯象学 · 物理学 2007-05-23 S. Alekhin

In this talk an introduction to generalized parton distributions is given. Recent developments are shortly reviewed, including non-perturbative calculations, phenomenological aspects and evaluation of higher order perturbative and power…

高能物理 - 唯象学 · 物理学 2015-06-25 D. Müller

We present the basic aspects of deep inelastic phenomena in the framework of the QCD parton model. After recalling briefly the standard kinematics, we discuss the physical interpretation of unpolarized and polarized structure functions in…

高能物理 - 唯象学 · 物理学 2007-05-23 C. Bourrely , J. Soffer

We summarize recent results on the evolution of unpolarized parton densities and deep-inelastic structure functions in massless perturbative QCD. Due to last year's extension of the integer-moment calculations of the three-loop splitting…

高能物理 - 唯象学 · 物理学 2008-11-26 W. L. van Neerven , A. Vogt

We briefly recall the main physical features of the parton distributions in the quantum statistical picture of the nucleon. Some predictions from a next-to-leading order QCD analysis are successfully compared to recent unpolarized and…

高能物理 - 唯象学 · 物理学 2011-12-02 Jacques Soffer

We investigate the polarized parton distribution functions (PDFs) and their uncertainties by using the world data on the spin asymmetry A_1. The uncertainties of the polarized PDFs are estimated by the Hessian method. The up and down…

高能物理 - 唯象学 · 物理学 2008-11-26 M. Hirai , S. Kumano , N. Saito