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We give an introduction to several regularization schemes that deal with ultraviolet and infrared singularities appearing in higher-order computations in quantum field theories. Comparing the computation of simple quantities in the various…

We propose and investigate efficient numerical methods for inverse problems related to Magnetic Resonance Imaging (MRI). Our goal is to extend the recent convergence results for the Landweber-Kaczmarz method obtained in [Haltmeier, Leitao,…

Numerical Analysis · Mathematics 2020-12-22 A. Leitao , J. Zubelli

The dual formulation of empirical risk minimization with f-divergence regularization (ERM-fDR) is introduced. The solution of the dual optimization problem to the ERM-fDR is connected to the notion of normalization function introduced as an…

Machine Learning · Statistics 2025-08-06 Francisco Daunas , Iñaki Esnaola , Samir M. Perlaza

We review the techniques used to renormalize quantum field theories at several loop orders. This includes the techniques to systematically extract the infinities in a Feynman integral and the implementation of the algorithm within computer…

High Energy Physics - Theory · Physics 2007-05-23 J. A. Gracey

Implicit regularization (IR) has been shown as an useful momentum space tool for perturbative calculations in dimension specific theories, such as chiral gauge, topological and supersymmetric quantum field theoretical models at one loop…

High Energy Physics - Theory · Physics 2009-11-11 C. R. Pontes , A. P. Baeta Scarpelli , Marcos Sampaio , M. C. Nemes

Owing to the edge preserving ability and low computational cost of the total variation (TV), variational models with the TV regularization have been widely investigated in the field of multiplicative noise removal. The key points of the…

Computer Vision and Pattern Recognition · Computer Science 2015-03-18 Dai-Qiang Chen , Li-Zhi Cheng

In view of various field-theoretic reasons, in the present work, we study the question of if the usual dimensional regularization can be extended to quantum field theories with an ultraviolet cutoff (Poincare-breaking scale) in a way…

High Energy Physics - Theory · Physics 2024-02-08 Durmus Demir , Canan Karahan , Ozan Sargın

Neural Networks have been widely used to solve Partial Differential Equations. These methods require to approximate definite integrals using quadrature rules. Here, we illustrate via 1D numerical examples the quadrature problems that may…

Numerical Analysis · Mathematics 2022-03-09 Jon A. Rivera , Jamie M. Taylor , Ángel J. Omella , David Pardo

We complete the derivation of the conservative dynamics of binary systems to fourth Post-Newtonian (4PN) order in the effective field theory (EFT) approach. We present a self-contained (ambiguity-free) computation of the renormalized…

General Relativity and Quantum Cosmology · Physics 2019-07-31 Stefano Foffa , Rafael A. Porto , Ira Rothstein , Riccardo Sturani

We introduce a method for fast estimation of data-adapted, spatio-temporally dependent regularization parameter-maps for variational image reconstruction, focusing on total variation (TV)-minimization. Our approach is inspired by recent…

This revisit gives a survey on the analytical methods for the inverse exponential Radon transform which has been investigated in the past three decades from both mathematical interests and medical applications such as nuclear medicine…

Image and Video Processing · Electrical Eng. & Systems 2020-02-06 Jason You

The necessity of renormalization arises from the infinite integrals which are caused by the discrepancy between the orders of differential and integral operators in the four dimensional QFTs. Therefore in view of the fact that finiteness…

General Physics · Physics 2021-05-19 F. Ghaboussi

Inverse problems are fundamental in fields like medical imaging, geophysics, and computerized tomography, aiming to recover unknown quantities from observed data. However, these problems often lack stability due to noise and…

Numerical Analysis · Mathematics 2024-06-26 Andrea Ebner , Matthias Schwab , Markus Haltmeier

We describe the equivalence at one loop between constrained differential renormalization and regularization by dimensional reduction in the MS scheme. To illustrate it, we reexamine the calculation of supergravity corrections to (g-2)_l.

High Energy Physics - Phenomenology · Physics 2007-05-23 F. del Aguila , M. Perez-Victoria

This paper summarizes some of the major calibration and image reconstruction techniques used in radio interferometry and describes them in a common mathematical framework. The use of this framework has a number of benefits, ranging from…

Instrumentation and Methods for Astrophysics · Physics 2009-11-26 U. Rau , S. Bhatnagar , M. A. Voronkov , T. J. Cornwell

We compute the perturbative short-time expansion for the transition amplitude of a particle in curved space time, by employing Dimensional Regularization (DR) to treat the divergences which occur in some Feynman diagrams. The present work…

High Energy Physics - Theory · Physics 2022-02-09 Olindo Corradini , Luigi Crispo , Maurizio Muratori

This is a tutorial and survey paper on various methods for Sufficient Dimension Reduction (SDR). We cover these methods with both statistical high-dimensional regression perspective and machine learning approach for dimensionality…

Methodology · Statistics 2021-10-20 Benyamin Ghojogh , Ali Ghodsi , Fakhri Karray , Mark Crowley

We study the IR/UV connection of the four-dimensional non-commutative phi^4 theory by using the Wilsonian Renormalization Group equation. Extending the usual formulation to the non-commutative case we are able to prove UV renormalizability…

High Energy Physics - Theory · Physics 2009-11-07 Luca Griguolo , Massimo Pietroni

We investigate the regularization-scheme dependent treatment of $\gamma_{5}$ in the framework of dimensional regularization, mainly focusing on the four-dimensional helicity scheme (FDH). Evaluating distinctive examples, we find that for…

High Energy Physics - Phenomenology · Physics 2018-05-16 C. Gnendiger , A. Signer

Existing facial image super-resolution (SR) methods focus mostly on improving artificially down-sampled low-resolution (LR) imagery. Such SR models, although strong at handling artificial LR images, often suffer from significant performance…

Computer Vision and Pattern Recognition · Computer Science 2020-01-01 Zhiyi Cheng , Xiatian Zhu , Shaogang Gong