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The usual mathematical formalism of quantum field theory is non-rigorous because it contains divergences that can only be renormalized by non-rigorous mathematical methods. The purpose of this paper is to present a method of subtraction of…

Mathematical Physics · Physics 2012-03-29 Juan Sebastián Ardenghi , Mario Castagnino

We study exclusive quarkonium production in the dipole picture at next-to-leading order (NLO) accuracy, using the non-relativistic expansion for the quarkonium wavefunction. This process offers one of the best ways to obtain information…

High Energy Physics - Phenomenology · Physics 2020-03-09 Miguel Ángel Escobedo , Tuomas Lappi

The perturbative QCD approach to quarkonium decay into a photon and hadrons is reconsidered. It is shown that a consistent treatment within perturbative QCD calls for the introduction of a fragmentation contribution which has been neglected…

High Energy Physics - Phenomenology · Physics 2009-10-28 S. Catani , F. Hautmann

It is shown how strictly four-dimensional integration by parts combined with differential renormalization and its infrared analogue can be applied for calculation of Feynman diagrams.

High Energy Physics - Theory · Physics 2009-10-30 V. A. Smirnov

When adopting a model-based formulation, solving inverse problems encountered in multiband imaging requires to define spatial and spectral regularizations. In most of the works of the literature, spectral information is extracted from the…

Image and Video Processing · Electrical Eng. & Systems 2023-07-03 Min Zhao , Nicolas Dobigeon , Jie Chen

Various prescriptions employed for regulating gauged Nambu--Jona-Lasinio type models such as the top-quark condensate model are discussed. The use of dimensional regularization maintains gauge invariance but destroys the quadratic…

High Energy Physics - Phenomenology · Physics 2009-10-28 Tony Gherghetta

Diffusive representations of fractional derivatives have proven to be useful tools in the construction of fast and memory efficient numerical methods for solving fractional differential equations. A common challenge in many of the known…

Numerical Analysis · Mathematics 2022-04-11 Kai Diethelm

We study the transverse-momentum spectrum of quarkonium production from single light-parton fragmentation mechanism. In the case of semi-inclusive deep inelastic scattering, we observe that there are two possible initiating processes,…

High Energy Physics - Phenomenology · Physics 2020-10-29 Miguel G. Echevarria , Yiannis Makris , Ignazio Scimemi

We investigate the possibility of generalizing differential renormalization of D.Z.Freedman, K.Johnson and J.I.Latorre in an invariant fashion to theories with infrared divergencies via an infrared $\tilde{R}$ operation. Two-dimensional…

High Energy Physics - Theory · Physics 2009-10-22 L. V. Avdeev , D. I. Kazakov , I. N. Kondrashuk

The Radon transform is a fundamental tool for analyzing data in tomographic imaging, optimal transport, crystallography, and geometric analysis. Numerical computations require an accurate discretization. To deal with voxelized images and…

Numerical Analysis · Mathematics 2026-03-17 Robert Beinert , Jonas Bresch , Michael Quellmalz

We present a method to numerically evaluate infrared-finite one- and two-loop integrals within the Four-Dimensional Regularization/Renormalization approach, in which a small mass serves as regulator. Typical integrals exhibit a logarithmic…

High Energy Physics - Phenomenology · Physics 2016-02-08 Tom Zirke

The use of orthogonal projections on high-dimensional input and target data in learning frameworks is studied. First, we investigate the relations between two standard objectives in dimension reduction, preservation of variance and of…

Ultrasound computed tomography (USCT) holds great promise for breast cancer screening. Waveform inversion-based image reconstruction methods account for higher order diffraction effects and can produce high-resolution USCT images, but are…

Medical Physics · Physics 2017-08-25 Thomas P. Matthews , Kun Wang , Cuiping Li , Neb Duric , Mark A. Anastasio

Separable nonlinear least squares problems appear in many inverse problems, including semi-blind image deblurring. The variable projection (VarPro) method provides an efficient approach for solving such problems by eliminating linear…

Numerical Analysis · Mathematics 2026-01-09 Delfina B. Comerso Salzer , Malena I. Español , Gabriela Jeronimo

The variational method and the Hamiltonian formalism of QCD are used to derive relativistic, momentum space integral equations for a quark-antiquark system with an arbitrary number of gluons present. As a first step, the resulting infinite…

High Energy Physics - Phenomenology · Physics 2009-10-31 L. Di Leo , J. W. Darewych

A regularization renormalization method ($RRM$) in quantum field theory ($QFT$) is discussed with simple rules: Once a divergent integral $I$ is encountered, we first take its derivative with respect to some mass parameter enough times,…

Quantum Physics · Physics 2010-07-20 Guang-jiong Ni , Jianjun Xu , Senyue Lou

Tomography is a central tool in medical applications, allowing doctors to investigate patients' interior features. The Radon transform (in two dimensions) is commonly used to model the measurement process in parallel-beam CT. Suitable…

Numerical Analysis · Mathematics 2026-02-27 Richard Huber

We investigate the real-time evolution of quarkonium bound states in a quark-gluon plasma in one dimension using an improved QCD based stochastic potential model. This model describes the quarkonium dynamics in terms of a Schr\"odinger…

Nuclear Theory · Physics 2018-02-07 Shiori Kajimoto , Yukinao Akamatsu , Masayuki Asakawa , Alexander Rothkopf

Coherent diffraction imaging is a high-resolution imaging technique whose potential can be greatly enhanced by applying the extrapolation method presented here. We demonstrate enhancement in resolution of a non-periodical object…

In this paper, we study the effect of different regularizers and their implications in high dimensional image classification and sparse linear unmixing. Although kernelization or sparse methods are globally accepted solutions for processing…

Machine Learning · Statistics 2016-11-03 Devis Tuia , Remi Flamary , Michel Barlaud