English
Related papers

Related papers: Dual parametrization of GPDs versus the double dis…

200 papers

Using momentum sum rule for evolution equations for Double Parton Distribution Functions (DPDFs) in the leading logarithmic approximation, we find that the double gluon distribution function can be uniquely constrained via the single gluon…

High Energy Physics - Phenomenology · Physics 2016-06-07 Krzysztof Golec-Biernat , Emilia Lewandowska , Mirko Serino , Zachary Snyder , Anna Stasto

An explicit formula is obtained for the generalized Macdonald functions on the $N$-fold Fock tensor spaces, calculating a certain matrix element of a composition of several screened vertex operators. As an application, we prove the…

Quantum Algebra · Mathematics 2020-12-02 Masayuki Fukuda , Yusuke Ohkubo , Jun'ichi Shiraishi

A shift-invariant system is a collection of functions $\{g_{m,n}\}$ of the form $g_{m,n}(k) = g_m(k-an)$. Such systems play an important role in time-frequency analysis and digital signal processing. A principal problem is to find a dual…

Numerical Analysis · Mathematics 2025-10-20 Thomas Strohmer

Recently, we made significant advancements in improving the computational efficiency of lattice QCD calculations for Generalized Parton Distributions (GPDs). This progress was achieved by adopting calculations of matrix elements in…

We investigate the helicity dependent generalized parton distributions (GPDs) in momentum as well as transverse position (impact) spaces for up and down quarks in a proton when the momentum transfer in both the transverse and longitudinal…

High Energy Physics - Phenomenology · Physics 2017-09-28 Chandan Mondal

In this paper we consider double parton distribution functions (dPDFs) which are the main non perturbative ingredients appearing in the double parton scattering cross section formula in hadronic collisions. By using recent calculation of…

High Energy Physics - Phenomenology · Physics 2017-03-08 Matteo Rinaldi , Federico Alberto Ceccopieri

Recent parameterizations of parton distribution functions (PDFs) have led to the determination of the gravitional form factors of the nucleon's dependence on generalized parton distributions of nucleons in the limit $\xi$$\to 0$. This paper…

High Energy Physics - Phenomenology · Physics 2025-07-21 Hossein Vaziri Mohammad Reza Shojaei ID

We have investigated the unpolarized valence quark generalized parton distribution functions (GPDs) and parton distribution functions (PDFs) for heavy spin-$0$, $B$- and $D$-mesons in the light-front quark model (LFQM). PDFs have been…

High Energy Physics - Phenomenology · Physics 2024-08-16 Satyajit Puhan , Harleen Dahiya

We extend the formalism of asymmetric frames of reference for generalized parton distributions (GPDs) to the case of nonzero skewness, i.e., including longitudinal momentum transfer. The framework, based on Lorentz-invariant amplitudes and…

Generalized parton distributions (GPDs) provide a link between form factors, parton distributions and other observables. I discuss the connection between GPDs and parton distributions as a function of the impact parameter. Since this…

High Energy Physics - Phenomenology · Physics 2009-10-31 Matthias Burkardt

Dual continuation, an innovative insight into extending the real-valued functions of real matrices to the dual-valued functions of dual matrices with a foundation of the G\^ateaux derivative, is proposed. Theoretically, the general forms of…

Numerical Analysis · Mathematics 2024-11-14 Tong Wei , Weiyang Ding , Yimin Wei

We represent the Ising model of statistical physics by normal factor graphs in the primal and in the dual domains. By analogy with Kirchhoff's voltage and current laws, we show that in the primal normal factor graphs, the dependency among…

Information Theory · Computer Science 2018-07-24 Mehdi Molkaraie

Forecasting over graph-structured sensor networks demands models that capture both deterministic spatial trends and stochastic variability, while remaining efficient enough for repeated inference as new observations arrive. We propose…

Machine Learning · Computer Science 2026-04-02 Hanlin Dong , Arian Prabowo , Hao Xue , Ao Shuang , Tianyi Zhou , Flora D. Salim

This work presents a modular reconstruction of the transition generalized parton distribution (GPD) H_T(x,t) for the Delta(1232) resonance, based on digitized helicity amplitude data and dipole fits to A_1/2(Q^2). From the fitted amplitude,…

High Energy Physics - Phenomenology · Physics 2025-10-02 Ralph M. Marinaro

Graph signal processing (GSP) advances spectral analysis on irregular domains. However, existing two-dimensional graph fractional Fourier transform (2D-GFRFT) employs a single fractional order for both factor graphs, thereby limiting its…

Signal Processing · Electrical Eng. & Systems 2025-10-14 Mingzhi Wang , Zhichao Zhang

We propose a probability distribution for multivariate binary random variables. The probability distribution is expressed as principal minors of the parameter matrix, which is a matrix analogous to the inverse covariance matrix in the…

Methodology · Statistics 2025-12-08 Takashi Arai

Quasisymmetric functions have recently been used in time series analysis as polynomial features that are invariant under, so-called, dynamic time warping. We extend this notion to data indexed by two parameters and thus provide warping…

Combinatorics · Mathematics 2024-10-10 Joscha Diehl , Leonard Schmitz

We explore the role of parametrizations for nonperturbative QCD functions in global analyses, with a specific application to extending a phenomenological analysis of the parton distribution functions (PDFs) in the charged pion realized in…

High Energy Physics - Phenomenology · Physics 2024-04-17 Lucas Kotz , Aurore Courtoy , Pavel Nadolsky , Fredrick Olness , Maximiliano Ponce-Chavez

We investigate the behavior of spin-dependent parton distribution functions (PDFs) at large parton momentum fractions x in the context of global QCD analysis. We explore the constraints from existing deep-inelastic scattering data, and from…

High Energy Physics - Phenomenology · Physics 2015-06-19 P. Jimenez-Delgado , H. Avakian , W. Melnitchouk

Some scenarios require the computation of a predictive distribution of a new value evaluated on an objective function conditioned on previous observations. We are interested on using a model that makes valid assumptions on the objective…

Machine Learning · Computer Science 2021-01-21 Lucia Asencio-Martín , Eduardo C. Garrido-Merchán
‹ Prev 1 3 4 5 6 7 10 Next ›