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相关论文: Cut Moments approach in the analysis of DIS data

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We elaborate a cut (truncated) Mellin moments (CMM) approach that is constructed to study deep inelastic scattering in lepton-hadron collisions at the natural kinematic constraints. We show that generalized CMM obtained by multiple…

高能物理 - 理论 · 物理学 2015-06-19 D. Kotlorz , S. V. Mikhailov

We demonstrate advantages of the truncated Mellin moments (TMM) approach in the analysis of DIS data. We present a novel method for determination of the Bjorken sum rule (BSR) from restricted in $x$ variable experimental data. We show how…

高能物理 - 唯象学 · 物理学 2020-07-24 D. Strozik-Kotlorz , S. V. Mikhailov , O. V. Teryaev , A. Kotlorz

We review evolution equations for the truncated Mellin moments of the parton distributions and some their applications in QCD analysis. The main finding of the presented approach is that the $n$th truncated moment of the parton distribution…

高能物理 - 唯象学 · 物理学 2015-06-19 Dorota Kotlorz , Andrzej Kotlorz

We derive the LO DGLAP evolution equation for the full Mellin moments of the truncated at $x_0$ first moment of the nonsinglet parton distribution. This "moment of moment" approach allows to determine the small-$x_0$ behaviour of the…

高能物理 - 唯象学 · 物理学 2010-03-25 D. Kotlorz , A. Kotlorz

We develop a generalized method of moments (GMM) approach for fast parameter estimation in a new class of Dirichlet latent variable models with mixed data types. Parameter estimation via GMM has been demonstrated to have computational and…

统计理论 · 数学 2016-03-24 Shiwen Zhao , Barbara E. Engelhardt , Sayan Mukherjee , David B. Dunson

We solve the LO DGLAP QCD evolution equation for truncated Mellin moments of the nucleon nonsinglet structure function. The results are compared with those, obtained in the Chebyshev-polynomial approach for $x$-space solutions. Computations…

高能物理 - 唯象学 · 物理学 2014-11-18 D. Kotlorz , A. Kotlorz

We present progress in development of the truncated Mellin moments approach (TMMA). We show our recent results on the generalization of DGLAP evolution equations and discuss some their applications in spin physics.

高能物理 - 唯象学 · 物理学 2016-02-17 D. Strozik-Kotlorz , S. V. Mikhailov , O. V. Teryaev

Detection and modeling of change-points in time-series can be considerably challenging. In this paper we approach this problem by incorporating the class of Dynamic Generalized Linear Models (DGLM) into the well know class of Product…

We present generalized evolution equations and factorization in terms of the truncated Mellin moments (TMM) of the parton distributions and structure functions. We illustrate the $x$ and $Q^2$ dependence of TMM in the polarized case. Using…

高能物理 - 唯象学 · 物理学 2016-12-09 D. Kotlorz , A. Kotlorz

We propose a new method for computing Dynamic Mode Decomposition (DMD) evolution matrices, which we use to analyze dynamical systems. Unlike the majority of existing methods, our approach is based on a variational formulation consisting of…

数值分析 · 数学 2019-05-24 Omri Azencot , Wotao Yin , Andrea Bertozzi

We review our previous studies of truncated Mellin moments of parton distributions. We show in detail the derivation of the evolution equation for double truncated moments. The obtained splitting function has the same rescaled form as in a…

高能物理 - 唯象学 · 物理学 2011-06-21 D. Kotlorz , A. Kotlorz

We define truncated Mellin moments of parton distributions by restricting the integration range over the Bjorken variable to the experimentally accessible subset x_0 < x < 1 of the allowed kinematic range 0 < x < 1. We derive the evolution…

高能物理 - 唯象学 · 物理学 2014-11-17 Stefano Forte , Lorenzo Magnea , Andrea Piccione , Giovanni Ridolfi

Dirichlet Process Mixture Models (DPMMs) are widely used to address clustering problems. Their main advantage lies in their ability to automatically estimate the number of clusters during the inference process through the Bayesian…

机器学习 · 统计学 2023-12-19 Reda Khoufache , Mustapha Lebbah , Hanene Azzag , Etienne Goffinet , Djamel Bouchaffra

Since Pearson [Philosophical Transactions of the Royal Society of London. A, 185 (1894), pp. 71-110] first applied the method of moments (MM) for modeling data as a mixture of one-dimensional Gaussians, moment-based estimation methods have…

机器学习 · 计算机科学 2025-07-29 Liu Zhang , Oscar Mickelin , Sheng Xu , Amit Singer

We propose a semi-partitioned Generalized Method of Moments (GMM) framework for analyzing longitudinal data with time-dependent covariates, within a marginal modeling paradigm. This approach addresses limitations of both aggregated and…

统计方法学 · 统计学 2026-03-04 Niloofar Ramezani , Jeffrey R. Wilson

It is proposed the modification of the Jacobi polynomial expansion method (MJEM) which is based on the application of the truncated moments instead of the full ones. This allows to reconstruct with a high precision the local quark helicity…

高能物理 - 唯象学 · 物理学 2009-11-11 A. N. Sissakian , O. Yu. Shevchenko , O. N. Ivanov

In this paper, we propose a new time-aware dissimilarity measure that takes into account the temporal dimension. Observations that are close in the description space, but distant in time are considered as dissimilar. We also propose a…

机器学习 · 计算机科学 2016-01-13 Marian-Andrei Rizoiu , Julien Velcin , Stéphane Lallich

Work presented in this paper describes a general algorithm and its finite element implementation for performing concurrent multiple sub-domain simulations in linear structural dynamics. Using this approach one can solve problems in which…

数值分析 · 数学 2013-12-25 Tejas Ruparel , Azim Eskandarian , James Lee

We examine convergence properties of reconstructing the generalized parton distributions (GPDs) through the universal moment parameterization (GUMP). We provide a heuristic explanation for the connection between the formal…

高能物理 - 唯象学 · 物理学 2024-12-05 Hao-Cheng Zhang , Xiangdong Ji

A matrix-based approach to numerical integration of the DGLAP evolution equations is presented. The method arises naturally on discretisation of the Bjorken x variable, a necessary procedure for numerical integration. Owing to peculiar…

高能物理 - 唯象学 · 物理学 2014-11-17 Philip G. Ratcliffe
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