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Related papers: Gaussian-weighted Parton Quasi-distribution

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We present a new method, based on Gaussian process regression, for reconstructing the continuous $x$-dependence of parton distribution functions (PDFs) from quasi-PDFs computed using lattice QCD. We examine the origin of the unphysical…

High Energy Physics - Lattice · Physics 2020-11-25 Constantia Alexandrou , Giovanni Iannelli , Karl Jansen , Floriano Manigrasso

Majorization theory is a powerful mathematical tool to compare the disorder in distributions, with wide-ranging applications in many fields including mathematics, physics, information theory, and economics. While majorization theory…

Using our formalism of parton virtuality distribution functions (VDFs) we establish a connection between the transverse momentum dependent distributions (TMDs) ${\cal F} (x, k_\perp^2)$ and quasi-distributions $Q(y,P_z)$ introduced recently…

High Energy Physics - Phenomenology · Physics 2017-02-15 Anatoly Radyushkin

In computational and applied statistics, it is of great interest to get fast and accurate calculation for the distributions of the quadratic forms of Gaussian random variables. This paper presents a novel approximation strategy that…

Methodology · Statistics 2023-12-29 Hong Zhang , Judong Shen , Zheyang Wu

We consider Gaussian distributions on certain Riemannian symmetric spaces. In contrast to the Euclidean case, it is challenging to compute the normalization factors of such distributions, which we refer to as partition functions. In some…

Statistics Theory · Mathematics 2021-05-18 Simon Heuveline , Salem Said , Cyrus Mostajeran

We construct a class of real-valued nonnegative binary functions on a set of jointly distributed random variables, which satisfy the triangle inequality and vanish at identical arguments (pseudo-quasi-metrics). These functions are useful in…

Probability · Mathematics 2016-02-12 Ehtibar N. Dzhafarov , Janne V. Kujala

Gluon parton distribution functions (PDFs) in the proton can be calculated directly on Euclidean lattices using large momentum effective theory (LaMET). To realize this goal, one has to find renormalized gluon quasi-PDFs in which power…

High Energy Physics - Phenomenology · Physics 2019-04-11 Jian-Hui Zhang , Xiangdong Ji , Andreas Schäfer , Wei Wang , Shuai Zhao

We introduce a framework for quasi-Newton forward--backward splitting algorithms (proximal quasi-Newton methods) with a metric induced by diagonal $\pm$ rank-$r$ symmetric positive definite matrices. This special type of metric allows for a…

Optimization and Control · Mathematics 2018-11-27 Stephen Becker , Jalal Fadili , Peter Ochs

In this article we introduce a quasiprobability distribution of work that is based on the Wigner function. This construction rests on the idea that the work done on an isolated system can be coherently measured by coupling the system to a…

Quantum Physics · Physics 2023-11-03 Federico Cerisola , Franco Mayo , Augusto J. Roncaglia

In this paper, an alternative mixed Poisson distribution is proposed by amalgamating Poisson distribution and a modification of the Quasi Lindley distribution. Some fundamental structural properties of the new distribution, namely the shape…

Methodology · Statistics 2021-10-26 Ramajeyam Tharshan , Pushpakanthie Wijekoon

We develop a general framework to investigate fluctuations of non-commuting observables. To this end, we consider the Keldysh quasi-probability distribution (KQPD). This distribution provides a measurement-independent description of the…

Quantum Physics · Physics 2017-10-13 Patrick P. Hofer

Nonparametric Bayesian models are used routinely as flexible and powerful models of complex data. Many times, a statistician may have additional informative beliefs about data distribution of interest, e.g., its mean or subset components,…

Methodology · Statistics 2022-11-08 Bingjing Tang , Vinayak Rao

Quasi parton distributions (quasi-PDFs) are currently under intense investigation. Quasi-PDFs are defined through spatial correlation functions and are thus accessible in lattice QCD. They gradually approach their corresponding standard…

High Energy Physics - Phenomenology · Physics 2020-09-30 Shohini Bhattacharya , Christopher Cocuzza , Andreas Metz

Semi- and non-parametric mixture of regressions are a very useful flexible class of mixture of regressions in which some or all of the parameters are non-parametric functions of the covariates. These models are, however, based on the…

Methodology · Statistics 2026-01-21 Peterson Mambondimumwe , Sphiwe B. Skhosana , Najmeh Nakhaei Rad

Although equivalent in the infinite-momentum limit, large-momentum effective theory (LaMET) and short-distance operator product expansion (SD-OPE) are two different approaches to extract parton distribution functions (PDFs) from…

High Energy Physics - Lattice · Physics 2022-09-21 Xiangdong Ji

Parton physics, when formulated as light-front correlations, are difficult to study non-perturbatively, despite the promise of light-front quantization. Recently an alternative approach to partons have been proposed by re-visiting original…

High Energy Physics - Phenomenology · Physics 2014-04-29 Xiangdong Ji

We establish the limiting distribution (in total variation) of the quasi posteriors based on moment conditions, which only partially identify the parameters of interest. Some examples are discussed.

Statistics Theory · Mathematics 2016-10-07 Wenxin Jiang

Generalized Parton Distribution functions (GPDs) are off-diagonal light-cone matrix elements that encode the internal structure of hadrons in terms of quark and gluon degrees of freedom. In this work, we present the first nonperturbative…

High Energy Physics - Lattice · Physics 2025-11-25 Sebastian Grieninger , Jake Montgomery , Felix Ringer , Ismail Zahed

Within the soft collinear effective theory (SCET), we derive a factorization theorem which resums Sudakov logarithms $(\alpha_s\ln^2(-t))^n$ to all orders in the quark-in-quark generalized parton distribution (GPD) at large momentum…

High Energy Physics - Phenomenology · Physics 2025-11-12 Yoshitaka Hatta , Jakob Schoenleber

We introduce a class of semiparametric time series models by assuming a quasi-likelihood approach driven by a latent factor process. More specifically, given the latent process, we only specify the conditional mean and variance of the time…

Methodology · Statistics 2021-04-02 Gisele O. Maia , Wagner Barreto-Souza , Fernando S. Bastos , Hernando Ombao