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We study transverse-momentum-dependent (TMD) gluon distributions and factorization theorems for the gluon-initiated semi-inclusive processes at hadron colliders. Gauge-invariant TMD gluon distributions are defined, and their relations to…

High Energy Physics - Phenomenology · Physics 2009-11-11 Xiangdong Ji , Jian-Ping Ma , Feng Yuan

Evaluating the degree of partisan districting (Gerrymandering) in a statistical framework typically requires an ensemble of districting plans which are drawn from a prescribed probability distribution that adheres to a realistic and…

Computation · Statistics 2020-08-19 Gregory Herschlag , Jonathan C. Mattingly , Matthias Sachs , Evan Wyse

The evolution of transverse momentum dependent (TMD) distributions in Quantum Chromodynamics (QCD) can be formulated in a parton branching (PB) framework. We show that next-to-next-to-leading-logarithm (NNLL) accuracy can be achieved in…

High Energy Physics - Phenomenology · Physics 2025-09-15 A. Bermudez Martinez , F. Hautmann , L. Keersmaekers , A. Lelek , M. Mendizabal Morentin , S. Taheri Monfared , A. M. van Kampen

We review quark model calculations of the transverse momentum dependent parton distributions (TMDs). For the T-even TMDs, we discuss the physical origin of model relations which hold in a large class of quark models. For the T-odd TMDs we…

High Energy Physics - Phenomenology · Physics 2017-08-23 B. Pasquini , C. Lorce'

We derive relations between transverse momentum dependent distribution functions (TMDs) and the usual parton distribution functions (PDFs) in the 3D covariant parton model, which follow from Lorentz invariance and the assumption of a…

High Energy Physics - Phenomenology · Physics 2011-05-10 A. V. Efremov , P. Schweitzer , O. V. Teryaev , P. Zavada

We establish robust relations between Transverse Momentum Dependent distributions (TMDs) and collinear distributions. We define weighted integrals of TMDs that we call Transverse Momentum Moments (TMMs) and prove that TMMs are equal to…

High Energy Physics - Phenomenology · Physics 2025-01-27 Oscar del Rio , Alexei Prokudin , Ignazio Scimemi , Alexey Vladimirov

Recently there have been exciting developments in Monte Carlo methods, with the development of new MCMC and sequential Monte Carlo (SMC) algorithms which are based on continuous-time, rather than discrete-time, Markov processes. This has…

Computation · Statistics 2020-09-29 Paul Fearnhead , Joris Bierkens , Murray Pollock , Gareth O Roberts

We develop a novel Monte Carlo parton branching algorithm based on the Gribov-Levin-Ryskin (GLR) equation. The formulations of both forward evolution and backward evolution for the GLR equation are presented. The results from the Monte…

High Energy Physics - Phenomenology · Physics 2023-02-08 Yu Shi , Shu-Yi Wei , Jian Zhou

Markov chain Monte Carlo is a widely-used technique for generating a dependent sequence of samples from complex distributions. Conventionally, these methods require a source of independent random variates. Most implementations use…

Computation · Statistics 2012-04-17 Iain Murray , Lloyd T. Elliott

We present a new Monte Carlo algorithm for studying site or bond percolation on any lattice. The algorithm allows us to calculate quantities such as the cluster size distribution or spanning probability over the entire range of site or bond…

Statistical Mechanics · Physics 2009-10-31 M. E. J. Newman , R. M. Ziff

We study parton-branching solutions of QCD evolution equations and present a method to construct both collinear and transverse momentum dependent (TMD) parton densities from this approach. We work with next-to-leading-order (NLO) accuracy…

High Energy Physics - Phenomenology · Physics 2018-02-14 F. Hautmann , H. Jung , A. Lelek , V. Radescu , R. Zlebcik

The Transverse Momentum Dependent (TMD) Parton Branching (PB) method incorporates elements of TMD physics into a Monte Carlo (MC) framework to produce high-energy QCD predictions for collider processes. It derives TMDs from the PB evolution…

High Energy Physics - Phenomenology · Physics 2025-11-25 Aleksandra Lelek

Monte Carlo sampling techniques have broad applications in machine learning, Bayesian posterior inference, and parameter estimation. Often the target distribution takes the form of a product distribution over a dataset with a large number…

Methodology · Statistics 2019-09-19 Charles Matthews , Jonathan Weare

We reconsider the evolution equations for transverse momentum dependent distributions recently proposed by us and recast them in a form which allows the comparison with results recently appeared in the literature. We show under which…

High Energy Physics - Phenomenology · Physics 2018-05-09 Federico Alberto Ceccopieri , Luca Trentadue

We apply the joint threshold and transverse momentum dependent (TMD) factorization theorem to introduce new threshold-TMD distribution functions, including threshold-TMD parton distribution functions (PDFs) and fragmentation functions…

High Energy Physics - Phenomenology · Physics 2024-06-06 Zhong-Bo Kang , Kajal Samanta , Ding Yu Shao , Yang-Li Zeng

Computing systems interacting with real-world processes must safely and reliably process uncertain data. The Monte Carlo method is a popular approach for computing with such uncertain values. This article introduces a framework for…

We propose a modification, based on the RESTART (repetitive simulation trials after reaching thresholds) and DPR (dynamics probability redistribution) rare event simulation algorithms, of the standard diffusion Monte Carlo (DMC) algorithm.…

Probability · Mathematics 2014-04-10 Martin Hairer , Jonathan Weare

We discuss the recently proposed scheme for the evolution of Transverse Momentum Distributions using the so-called "D^R". We discuss a new method to separate perturbative and non-perturbative effects in the analysis of the evolution of…

High Energy Physics - Phenomenology · Physics 2013-11-08 Miguel G. Echevarria , Ahmad Idilbi , Ignazio Scimemi

Diffusion models enable the synthesis of highly accurate samples from complex distributions and have become foundational in generative modeling. Recently, they have demonstrated significant potential for solving Bayesian inverse problems by…

Machine Learning · Computer Science 2025-10-17 Yazid Janati , Alain Durmus , Jimmy Olsson , Eric Moulines

Transverse Momentum Dependent (TMD) parton distribution functions (PDFs) also take into account the transverse momentum ($p_T$) of the partons. The $p_T$-integrated analogues can be linked directly to quark and gluon matrix elements using…

High Energy Physics - Phenomenology · Physics 2014-04-02 P. J. Mulders , M. G. A. Buffing