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Charged particles production in the electron-positron, pbarp and pp collisions in full phase space as well as in the restricted phase space slices, at high energies are described with predictions from shifted Gompertz distribution, a model…

High Energy Physics - Phenomenology · Physics 2018-11-06 R. Chawla , M. Kaur

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…

High Energy Physics - Phenomenology · Physics 2017-04-05 Jacques Soffer , Claude Bourrely

This paper introduces constrained mixtures for continuous distributions, characterized by a mixture of distributions where each distribution has a shape similar to the base distribution and disjoint domains. This new concept is used to…

Machine Learning · Statistics 2015-03-29 Conrado S. Miranda , Fernando J. Von Zuben

We analyze a (symmetrical) two-sensor arrangement with a joint boundary line between the sensors for fluctuation-enhanced sensing. We show a way to separate the adsorption-desorption signal components from the diffusive signal component.…

General Physics · Physics 2008-03-10 Gabor Schmera , Laszlo B. Kish

In multi-room environments, modelling the sound propagation is complex due to the coupling of rooms and diverse source-receiver positions. A common scenario is when the source and the receiver are in different rooms without a clear line of…

Audio and Speech Processing · Electrical Eng. & Systems 2024-07-19 Kyung Yun Lee , Nils Meyer-Kahlen , Georg Götz , U. Peter Svensson , Sebastian J. Schlecht , Vesa Välimäki

In this paper we introduce a bivariate distribution on $\mathbb{R}_{+} \times \mathbb{N}$ arising from a single underlying Markov jump process. The marginal distributions are phase-type and discrete phase-type distributed, respectively,…

Methodology · Statistics 2022-07-05 Martin Bladt , Clara Brimnes Gardner

We study photon echo generation in disordered media with the help of multiple scattering theory based on diagrammatic approach and numerical simulations. We show that a strong correlation exists between the driving fields at the origin of…

Optics · Physics 2018-06-20 Romain Pierrat , Rémi Carminati , Jean-Louis Le Gouët

First-order statistics of scattered light is described using the representation of probability density cloud which visualizes a two-dimensional distribution for complex amplitude. The geometric parameters of the cloud are studied in detail…

Instrumentation and Methods for Astrophysics · Physics 2017-08-02 Natalia Yaitskova

Dihadron azimuthal correlations in Au+Au collisions at $\sqrt{S_{NN}}$=200 GeV have been explored by using a multi-phase transport (AMPT) model. In order to obtain the contributions from jet-medium interactions, the combined harmonic flow…

Nuclear Theory · Physics 2013-09-27 Yu-hui Zhu , Y. G. Ma , J. H. Chen , G. L. Ma , S. Zhang , C. Zhong

Using the superstatistics method, we propose an extension of the random matrix theory to cover systems with mixed regular-chaotic dynamics. Unlike most of the other works in this direction, the ensembles of the proposed approach are basis…

Statistical Mechanics · Physics 2007-05-23 A. Y. Abul-Magd

Dirichlet process mixture models (DPMM) play a central role in Bayesian nonparametrics, with applications throughout statistics and machine learning. DPMMs are generally used in clustering problems where the number of clusters is not known…

Machine Learning · Statistics 2020-10-20 Chiao-Yu Yang , Eric Xia , Nhat Ho , Michael I. Jordan

We explore the application of a two-component model of proton structure functions in the analysis of deep-inelastic scattering (DIS) data at low $Q^2$ and small $x$. This model incorporates both vector meson dominance and the correct…

High Energy Physics - Phenomenology · Physics 2019-11-21 X. G. Wang , A. W. Thomas

When light travels through scattering media, speckles (spatially random distribution of fluctuated intensities) are formed due to the interference of light travelling along different optical paths, preventing the perception of structure,…

Optics · Physics 2020-06-15 Honglin Liu , Xin Wang , Puxiang Lai , Zhentao Liu , Jianhong Shi , Shensheng Han

We formulate empirically the rapidity density distribution of produced particles in multiple particle production. The assumed mechanism is that the produced particles are emitted isotropically from several emitting centers, located on the…

High Energy Physics - Phenomenology · Physics 2010-09-21 A. Ohsawa , E. H. Shubuya , M. Tamada

This paper presents a study of the large-sample behavior of the posterior distribution of a structural parameter which is partially identified by moment inequalities. The posterior density is derived based on the limited information…

Statistics Theory · Mathematics 2010-01-13 Yuan Liao , Wenxin Jiang

Intrinsic transverse parton momenta pT play an important role in the understanding of azimuthal/spin asymmetries in semi-inclusive deep-inelastic scattering (SIDIS) and the Drell-Yan process (DY). We review and update what is presently…

High Energy Physics - Phenomenology · Physics 2014-11-20 P. Schweitzer , T. Teckentrup , A. Metz

A family of parsimonious shifted asymmetric Laplace mixture models is introduced. We extend the mixture of factor analyzers model to the shifted asymmetric Laplace distribution. Imposing constraints on the constitute parts of the resulting…

Methodology · Statistics 2013-11-05 Brian C. Franczak , Paul D. McNicholas , Ryan P. Browne , Paula M. Murray

The energy loss of a hard parton is regarded as a useful tool to probe properties of a soft medium. However, the information obtained by a measurement of the nuclear suppression R_AA is not very sensitive to medium properties. Thus, more…

High Energy Physics - Phenomenology · Physics 2007-05-23 Thorsten Renk

Most semantic drift studies report multiple signals e.g., embedding displacement, neighbor changes, distributional divergence, and recursive trajectory instability, without a shared explanatory theory that relates them. This paper proposes…

Computation and Language · Computer Science 2026-02-24 Stephen Russell

In the mixture models problem it is assumed that there are $K$ distributions $\theta_{1},\ldots,\theta_{K}$ and one gets to observe a sample from a mixture of these distributions with unknown coefficients. The goal is to associate instances…

Machine Learning · Statistics 2013-12-02 Jason D Lee , Ran Gilad-Bachrach , Rich Caruana
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