Flavor Structure of the Nucleon Sea

We review the current status and future prospects on the subject of flavor structure of the nucleon sea. The flavor structure of the nucleon sea provides unique information on the non-perturbative aspects of strong interactions allowing stringent tests of various models on the partonic structures of the nucleons as well as lattice QCD calculations. The scope of this review covers the unpolarized, polarized, and the transverse-momentum dependent sea-quark distributions of the nucleons. While the main focus of this review is on the physics motivation and recent progress on the subject of the nucleon sea, we also discuss future prospects of addressing some outstanding issues on the flavor structure of the nucleon sea.Comment: 61 pages and 36 figures; published versio

A False Acceptance Error Controlling Method for Hyperspherical Classifiers

Controlling false acceptance errors is of critical importance in many pattern recognition applications, including signature and speaker verification problems. Toward this goal, this paper presents two post-processing methods to improve the performance of hyperspherical classifiers in rejecting patterns from unknown classes. The first method uses a self-organizational approach to design minimum radius hyperspheres, reducing the redundancy of the class region defined by the hyperspherical classifiers. The second method removes additional redundant class regions from the hyperspheres by using a clustering technique to generate a number of smaller hyperspheres. Simulation and experimental results demonstrate that by removing redundant regions these two post-processing methods can reduce the false acceptance error without significantly increasing the false rejection error

A Training Sample Sequence Planning Method for Pattern Recognition Problems

In solving pattern recognition problems, many classification methods, such as the nearest-neighbor (NN) rule, need to determine prototypes from a training set. To improve the performance of these classifiers in finding an efficient set of prototypes, this paper introduces a training sample sequence planning method. In particular, by estimating the relative nearness of the training samples to the decision boundary, the approach proposed here incrementally increases the number of prototypes until the desired classification accuracy has been reached. This approach has been tested with a NN classification method and a neural network training approach. Studies based on both artificial and real data demonstrate that higher classification accuracy can be achieved with fewer prototypes

Interpretation of Angular Distributions of ZZ-boson Production at Colliders

High precision data of dilepton angular distributions in $\gamma^*/Z$ production were reported recently by the CMS Collaboration covering a broad range of the dilepton transverse momentum, $q_T$, up to $\sim 300$ GeV. Pronounced $q_T$ dependencies of the $\lambda$ and $\nu$ parameters, characterizing the $\cos^2\theta$ and $\cos 2\phi$ angular distributions, were found. Violation of the Lam-Tung relation was also clearly observed. We show that the $q_T$ dependence of $\lambda$ allows a determination of the relative contributions of the $q \bar q$ annihilation versus the $qG$ Compton process. The violation of the Lam-Tung relation is attributed to the presence of a non-zero component of the $q - \bar q$ axis in the direction normal to the "hadron plane" formed by the colliding hadrons. The magnitude of the violation of the Lam-Tung relation is shown to reflect the amount of this `non-coplanarity". The observed $q_T$ dependencies of $\lambda$ and $\nu$ from the CMS and the earlier CDF data can be well described using this approach.Comment: 5 pages, 3 figure