Unifying the Fixed Order Evolution of Fragmentation Functions with the Modified Leading Logarithm Approximation

An approach which unifies the Double Logarithmic Approximation at small x and the leading order DGLAP evolution of fragmentation functions at large x is presented. This approach reproduces exactly the Modified Leading Logarithm Approximation, but is more complete due to the degrees of freedom given to the quark sector and the inclusion of the fixed order terms. We find that data from the largest x values to the peak region can be better fitted than with other approaches

Novel Scaling Behavior for the Multiplicity Distribution under Second-Order Quark-Hadron Phase Transition

Deviation of the multiplicity distribution $P_q$ in small bin from its Poisson counterpart $p_q$ is studied within the Ginzburg-Landau description for second-order quark-hadron phase transition. Dynamical factor $d_q\equiv P_q/p_q$ for the distribution and ratio $D_q\equiv d_q/d_1$ are defined, and novel scaling behaviors between $D_q$ are found which can be used to detect the formation of quark-gluon plasma. The study of $d_q$ and $D_q$ is also very interesting for other multiparticle production processes without phase transition.Comment: 4 pages in revtex, 5 figures in eps format, will be appeared in Phys. Rev.

Deep Bilevel Learning

We present a novel regularization approach to train neural networks that enjoys better generalization and test error than standard stochastic gradient descent. Our approach is based on the principles of cross-validation, where a validation set is used to limit the model overfitting. We formulate such principles as a bilevel optimization problem. This formulation allows us to define the optimization of a cost on the validation set subject to another optimization on the training set. The overfitting is controlled by introducing weights on each mini-batch in the training set and by choosing their values so that they minimize the error on the validation set. In practice, these weights define mini-batch learning rates in a gradient descent update equation that favor gradients with better generalization capabilities. Because of its simplicity, this approach can be integrated with other regularization methods and training schemes. We evaluate extensively our proposed algorithm on several neural network architectures and datasets, and find that it consistently improves the generalization of the model, especially when labels are noisy.Comment: ECCV 201

Parton-Hadron duality in event generators

The validity of local parton-hadron duality within the framework of HERWIG and JETSET event generators is investigated. We concentrate on ${\rm e}^{+}{\rm e}^{-}$ annihilations in LEP 2 energy range as these interactions provide theoretically the cleanest condition for the discussion of this concept.Comment: PRA-HEP-92/14, 10 pages and 7 PS figures obtainable upon request, LATEX. email transmission errors corrected. Requests for figures can be sent on the above ID or to CHYLA@CSPGAS1

Bilingual episodic memory: an introduction

Our current models of bilingual memory are essentially accounts of semantic memory whose goal is to explain bilingual lexical access to underlying imagistic and conceptual referents. While this research has included episodic memory, it has focused largely on recall for words, phrases, and sentences in the service of understanding the structure of semantic memory. Building on the four papers in this special issue, this article focuses on larger units of episodic memory(from quotidian events with simple narrative form to complex autobiographical memories) in service of developing a model of bilingual episodic memory. This requires integrating theory and research on how culture-specific narrative traditions inform encoding and retrieval with theory and research on the relation between(monolingual) semantic and episodic memory(Schank, 1982; Schank & Abelson, 1995; Tulving, 2002). Then, taking a cue from memory-based text processing studies in psycholinguistics(McKoon & Ratcliff, 1998), we suggest that as language forms surface in the progressive retrieval of features of an event, they trigger further forms within the same language serving to guide a within-language/ within-culture retrieval

Generalizing the DGLAP Evolution of Fragmentation Functions to the Smallest x Values

An approach which unifies the Double Logarithmic Approximation at small x and the leading order DGLAP evolution of fragmentation functions at large x is presented. This approach reproduces exactly the Modified Leading Logarithm Approximation, but is more complete due to the degrees of freedom given to the quark sector and the inclusion of the fixed order terms. We find that data from the largest x values to the peak region can be better fitted than with other approaches.Comment: 10 pages, 3 figure

Factorial Moments of Continuous Order

The normalized factorial moments $F_q$ are continued to noninteger values of the order $q$, satisfying the condition that the statistical fluctuations remain filtered out. That is, for Poisson distribution $F_q = 1$ for all $q$. The continuation procedure is designed with phenomenology and data analysis in mind. Examples are given to show how $F_q$ can be obtained for positive and negative values of $q$. With $q$ being continuous, multifractal analysis is made possible for multiplicity distributions that arise from self-similar dynamics. A step-by-step procedure of the method is summarized in the conclusion.Comment: 15 pages + 9 figures (figures available upon request), Late

Intermittency in Branching Processes

We study the intermittency properties of two branching processes, one with a uniform and another with a singular splitting kernel. The asymptotic intermittency indices, as well as the leading corrections to the asymptotic linear regime are explicitly computed in an analytic framework. Both models are found to possess a monofractal spectrum with $\varphi_{q}=q-1$. Relations with previous results are discussed.Comment: 20 pages, UCLA93/TEP/2