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We revisit the evolution of generalised parton distributions (GPDs) in momentum space. We formulate the evolution kernels at one-loop in perturbative QCD (pQCD) in a form suitable for numerical implementation and that allows for an accurate…

High Energy Physics - Phenomenology · Physics 2022-10-12 Valerio Bertone , Hervé Dutrieux , Cédric Mezrag , José M. Morgado , Hervé Moutarde

QCD evolution equations in $\text{MS}$-like schemes can be recovered from the same equations in a modified theory, QCD in non-integer $d=4-2\epsilon$ dimensions, which enjoys exact scale and conformal invariance at the critical point.…

High Energy Physics - Phenomenology · Physics 2015-06-22 V. M. Braun , A. N. Manashov

A generalization of a recently introduced recursive numerical method for the exact evaluation of integrals of regular solid harmonics and their normal derivatives over simplex elements in $\mathbb{R}^3$ is presented. The original Quadrature…

Numerical Analysis · Mathematics 2023-07-25 Shoken Kaneko , Ramani Duraiswami

I report on a numerical program for the evolution of parton distributions. The program uses the Mellin-transform method with an optimized contour. Due to this optimized contour the program needs only a few evaluations of the integrand and…

High Energy Physics - Phenomenology · Physics 2009-11-07 Stefan Weinzierl

We derive a generalized form of Altarelli-Parisi equations to decribe the time evolution of parton distributions in a nuclear medium. In the framework of the leading logarithmic approximation, we obtain a set of coupled integro-…

High Energy Physics - Phenomenology · Physics 2010-03-25 Klaus Geiger , Berndt Mueller

The development of improved algorithms for QCD on the lattice has enabled us to do calculations at small quark masses and get control over the chiral extrapolation. Also finer lattices have become possible, however, a severe slowing down…

High Energy Physics - Phenomenology · Physics 2011-07-28 Stefan Schaefer

The subject of this work is a new stochastic Galerkin method for second-order elliptic partial differential equations with random diffusion coefficients. It combines operator compression in the stochastic variables with tree-based spline…

Numerical Analysis · Mathematics 2022-06-02 Markus Bachmayr , Igor Voulis

The numerical optimization of continuous functions is a fundamental task in many scientific and engineering domains, ranging from mechanical design to training of artificial intelligence models. Among the most effective and widely used…

Neural and Evolutionary Computing · Computer Science 2026-05-13 Gerardo Altamirano-Gomez , Álvaro Gallardo , Carlos Ignacio Hernández Castellanos

This paper uses the Modified Projection Method to examine the errors in solving the boundary integral equation from Laplace equation. The analysis uses weighted norms, and parallel algorithms help solve the independent linear systems. By…

Numerical Analysis · Mathematics 2024-11-04 Akshay Rane , Kunalkumar Shelar

A QCD analysis of the world data on polarized deep inelastic scattering is presented in leading and next-to-leading order. New parameterizations are derived for the quark and gluon distributions for the kinematic range $x \epsilon…

High Energy Physics - Phenomenology · Physics 2016-09-06 J. Blümlein , H. Böttcher

QCD in non-integer $d=4-2\epsilon$ space-time dimensions enjoys conformal invariance at the special fine-tuned value of the coupling. Counterterms for composite operators in minimal subtraction schemes do not depend on $\epsilon$ by…

High Energy Physics - Phenomenology · Physics 2019-03-27 V. M. Braun , A. N. Manashov , S. Moch , M. Strohmaier

We introduce an effective algorithmic method for the computation of a lower bound for uniform expansion in one-dimensional dynamics. The approach employs interval arithmetic and thus provides a rigorous numerical result (computer-assisted…

Dynamical Systems · Mathematics 2026-01-28 Paweł Pilarczyk , Michał Palczewski , Stefano Luzzatto

When an external field is applied across a liquid-crystal cell, the twist and tilt distributions cannot be calculated analytically and must be extracted numerically. In the standard approach, the Euler-Lagrange equations are derived from…

Computational Physics · Physics 2025-11-18 Alicia Sit , Francesco Di Colandrea , Alessio D'Errico , Ebrahim Karimi

We present the benchmark of the polynomial expansion Monte Carlo method to a Kondo lattice model with classical localized spins on a geometrically frustrated lattice. The method enables to reduce the calculation amount by using the…

Strongly Correlated Electrons · Physics 2014-01-24 Hiroaki Ishizuka , Masafumi Udagawa , Yukitoshi Motome

We present a technique that enables the evaluation of perturbative expansions based on one-loop-renormalized vertices up to large expansion orders. Specifically, we show how to compute large-order corrections to the random phase…

Strongly Correlated Electrons · Physics 2020-11-19 Fedor Šimkovic , Riccardo Rossi , Michel Ferrero

We develop a new type of orthogonal polynomial, the modified discrete Laguerre (MDL) polynomials, designed to accelerate the computation of bosonic Matsubara sums in statistical physics. The MDL polynomials lead to a rapidly convergent…

Numerical Analysis · Mathematics 2021-01-06 Guanpeng Xu , Steven G. Johnson

A finite difference algorithm based on the integral Laguerre transform in time for solving a three-dimensional one-way wave equation is proposed. This allows achieving high accuracy of calculation results. In contrast to the Fourier method,…

Numerical Analysis · Mathematics 2022-01-12 Andrew V. Terekhov

The extension of the method [arXiv:hep-ph/0503109] for solving the leading order evolution equation for Generalized Parton Distributions (GPDs) is presented. We obtain the solution of the evolution equation both for the flavor nonsinglet…

High Energy Physics - Phenomenology · Physics 2009-11-11 M. Kirch , A. Manashov , A. Schafer

We present a proximal augmented Lagrangian based solver for general convex quadratic programs (QPs), relying on semismooth Newton iterations with exact line search to solve the inner subproblems. The exact line search reduces in this case…

Optimization and Control · Mathematics 2020-04-02 Ben Hermans , Andreas Themelis , Panagiotis Patrinos

We develop and analyze stochastic optimization algorithms for problems in which the expected loss is strongly convex, and the optimum is (approximately) sparse. Previous approaches are able to exploit only one of these two structures,…

Machine Learning · Statistics 2012-07-19 Alekh Agarwal , Sahand Negahban , Martin J. Wainwright