相关论文: PartonDensity.jl: a novel parton density determina…
We perform a next to leading order QCD global analysis of nuclear deep inelastic scattering and Drell-Yan data using the convolution approach to parameterize nuclear parton densities. We find both a significant improvement in the agreement…
The estimation of probability densities based on available data is a central task in many statistical applications. Especially in the case of large ensembles with many samples or high-dimensional sample spaces, computationally efficient…
The decision boundaries of Bayes classifier are optimal because they lead to maximum probability of correct decision. It means if we knew the prior probabilities and the class-conditional densities, we could design a classifier which gives…
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 this work we develop and implement a novel Bayesian method for computing the DOS of a system. This method is based on the use of a test function with adjustable parameters and we use Bayes theorem to find the best parameters given a…
We introduce a software package, Pigeons.jl, that provides a way to leverage distributed computation to obtain samples from complicated probability distributions, such as multimodal posteriors arising in Bayesian inference and…
Accurate quantification of local packing density and mixing in simulations of particulate systems is essential for many industrial applications. Traditional methods which simply count the number of particle centres within a given volume of…
The QCD treatment of the parton structure of virtual photons is briefly recalled, and possible limitations and open questions are pointed out. Various models for these densities are compared, completed by a short discussion of the treatment…
We present the determination of a set of parton distributions of the nucleon, at next-to-leading order, from a global set of deep-inelastic scattering data: NNPDF1.0. The determination is based on a Monte Carlo approach, with neural…
We discuss possible studies of parton distributions at the proposed 50-GeV PS facility. First, comments are given in general on the importance of large-x physics for finding new physics. Second, polarized deuteron reactions are discussed in…
This paper proposes a new method for finding the highest predictive density set or region, within the heteroscedastic regression framework. This framework enjoys the property that any highest predictive density set is a translation of some…
Error estimates on parton density distributions are presently based on the traditional method of least squares minimisation and linear error propagation in global QCD fits. We review the underlying assumptions and the various mathematical…
We discuss the determination of the parton substructure of hadrons by casting it as a peculiar form of pattern recognition problem in which the pattern is a probability distribution, and we present the way this problem has been tackled and…
We separate the contributions of parton distributions from higher twist corrections to the deeply inelastic lepton-proton scattering in the resonance region using the Jefferson Lab data at low $Q^2$. The study indicates that the concept of…
We present a new analysis to extract pion's parton distribution functions (PDFs) in the framework of the statistical model. Starting from the statistical model framework first developed for the spin-1/2 nucleon, we apply appropriate…
We discuss the main features of the recent NNPDF2.1 NLO set, a determination of parton distributions from a global set of hard scattering data using the NNPDF methodology including heavy quark mass effects. We present the implications for…
A density estimation method in a Bayesian nonparametric framework is presented when recorded data are not coming directly from the distribution of interest, but from a length biased version. From a Bayesian perspective, efforts to…
Bayesian variable selection has gained much empirical success recently in a variety of applications when the number $K$ of explanatory variables $(x_1,...,x_K)$ is possibly much larger than the sample size $n$. For generalized linear…
A study of the parameterization uncertainty at low Bjorken $x \le 0.1$ for the parton distribution functions of the proton is presented. The study is based on the HERA I combined data using a flexible parameterization form based on…
Radiatively generated, LO quark (u,d,s,c,b) and gluon densities in the real, unpolarized photon, calculated in the CJK model being an improved realization of the CJKL approach, have been recently presented. The results were obtained through…