Related papers: Questions on Uncertainties in Parton Distributions
In Bayesian inference, an unknown measurement uncertainty is often quantified in terms of a Gamma distributed precision parameter, which is impractical when prior information on the standard deviation of the measurement uncertainty shall be…
An important limitation in current fits of parton distribution functions (PDFs) is that PDF uncertainties do not include any source of theoretical uncertainty. Here we present a general method for incorporating theoretical uncertainties…
Engineering design problems are often modeled as multi-objective optimization tasks in which a scalarized utility function selects an optimal design from the Pareto set. In practice, preferences are imperfectly known, so uncertainty in the…
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…
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 compared to recent experimental results.
Due to lack of scientific understanding, some mechanisms may be missing in mathematical modeling of complex phenomena in science and engineering. These mathematical models thus contain some uncertainties such as uncertain parameters. One…
Generalized parton distributions provide a unified parameterization of hadron structure and allow one to combine information from many different observables. Lattice QCD calculations already provide important input to determine these…
The paper presents a construction of a quantitative measure of variability for parameter estimates in the data fitting problem under interval uncertainty. It shows the degree of variability and ambiguity of the estimate, and the need for…
The quantum statistical parton distributions approach proposed more than one decade ago is revisited by considering a larger set of recent and accurate Deep Inelastic Scattering experimental results. It enables us to improve the description…
The Generalized Parton Distributions (GPDs) are the appropriate framework for a universal description of the partonic structure of the nucleon. They characterize the dynamics of quarks and gluons inside the nucleon and consequently contain…
In this work, we revisit the problem of uniformity testing of discrete probability distributions. A fundamental problem in distribution testing, testing uniformity over a known domain has been addressed over a significant line of works, and…
One of the most ubiquitous problems in optimization is that of finding all the elements of a finite set at which a function $f$ attains its minimum (or maximum). When the codomain of $f$ is equipped with a total order, it is easy to…
I review recent developments in the extraction of nuclear parton distribution functions. First describing the global analysis framework, I then present a comparison of the latest analyses in terms of included data and theoretical details,…
Generalized parton distributions provide information on the longitudinal and transverse distribution of partons in the fast moving nucleon. Furthermore, they contain information on the spin structure of the nucleon. First results of a…
We perform next-to-leading order global analyses of deep inelastic and related data for different fixed values of $\alpha_S (M_Z^2)$. We present sets of parton distributions for six values of $\alpha_S$ in the range 0.105 to 0.130. We…
For an unpolarized target, the generalized parton distribution $H_q(x,0,t)$ is related to the distribution of partons in impact parameter space. The transverse distortion of this distribution for a transversely polarized target is described…
This article is an introduction to parton distribution functions and their generalizations which describe the quark and gluon structure of hadrons, and can be measured in various high-energy scattering processes. We provide the theoretical…
In some cases it may be useful to know parton distributions in a photon gas. This may be relevant, e.g., for the analysis of interactions of high energy cosmic ray particles with the cosmic microwave background radiation. The latter can be…
We review basic ideas and recent developments on the determination of the parton substructure of the nucleon, in view of applications to precision hadron collider physics. We review the way information on parton distributions (PDFs) is…
Model uncertainty is a crucial issue in statistics, econometrics and machine learning, yet its definition remains ambiguous and is subject to various interpretations in the literature. So far, there has not been a universally accepted…