English
Related papers

Related papers: A Priori Bounds for H\'enon-like Renormalization

200 papers

Renormalization procedure is generalized to be applicable for non renormalizable theories. It is shown that introduction of an extra expansion parameter allows to get rid of divergences and express physical quantities as series of finite…

High Energy Physics - Theory · Physics 2008-02-03 J. Gegelia , G. Japaridze , N. Kiknadze , K. Turashvili

We present a sufficient condition for irreducibility of forcing algebras and study the (non)-reducedness phenomenon. Furthermore, we prove a criterion for normality for forcing algebras over a polynomial base ring with coefficients in a…

Commutative Algebra · Mathematics 2017-07-28 Danny A. J. Gomez-Ramirez , Holger Brenner

We study the boundary regularity properties and derive a priori pointwise supremum estimates of weak solutions and their derivatives in terms of suitable weighted $L^2$-norms for a class of degenerate parabolic equations that satisfy…

Analysis of PDEs · Mathematics 2017-02-09 Charles L. Epstein , Camelia A. Pop

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

We prove existence of strong solutions to a family of some semilinear parabolic free boundary problems by means of elliptic regularization. Existence of solutions is obtained in two steps: we first show some uniform energy estimates and…

Analysis of PDEs · Mathematics 2023-06-12 Alessandro Audrito , Tomás Sanz-Perela

Let $\Omega \subset \mathbb R^N$, $N \geq 2$, be a smooth bounded domain. We consider a boundary value problem of the form $$-\Delta u = c_{\lambda}(x) u + \mu(x) |\nabla u|^2 + h(x), \quad u \in H^1_0(\Omega)\cap L^{\infty}(\Omega)$$ where…

Analysis of PDEs · Mathematics 2018-11-02 Colette De Coster , Antonio J. Fernández , Louis Jeanjean

Autoencoders are widely used for unsupervised learning and as a regularization scheme in semi-supervised learning. However, theoretical understanding of their generalization properties and of the manner in which they can assist supervised…

Machine Learning · Statistics 2019-02-06 Baruch Epstein , Ron Meir

Perturbative renormalization group theory is developed as a unified tool for global asymptotic analysis. With numerous examples, we illustrate its application to ordinary differential equation problems involving multiple scales, boundary…

High Energy Physics - Theory · Physics 2008-11-26 Lin-Yuan Chen , Nigel Goldenfeld , Y. Oono

We establish the theorems that give necessary and sufficient conditions for an arbitrary function defined in the unit disk of complex plane in order to has boundary values along classes of equivalencies of simple curves. Our results…

Complex Variables · Mathematics 2014-06-26 Zarko Pavicevic , Marijan Markovic

Normalizing flows are a powerful tool for generative modelling, density estimation and posterior reconstruction in Bayesian inverse problems. In this paper, we introduce proximal residual flows, a new architecture of normalizing flows.…

Machine Learning · Computer Science 2023-05-19 Johannes Hertrich

In this paper we prove two new abstract compactness criteria in normed spaces. To this end we first introduce the notion of an equinormed set using a suitable family of semi-norms on the given normed space satisfying some natural…

Functional Analysis · Mathematics 2023-06-23 Jacek Gulgowski , Piotr Kasprzak , Piotr Maćkowiak

An original regular approach to constructing special type symmetries for boundary value problems, namely renormgroup symmetries, is presented. Different methods of calculating these symmetries, based on modern group analysis are described.…

High Energy Physics - Theory · Physics 2009-10-30 V. F. Kovalev , V. V. Pustovalov , D. V. Shirkov

A new method, called the method of self-similar approximants, and its recent developments are described. The method is based on the ideas of renormalization group theory and optimal control theory. It allows for the effective extrapolation…

Mathematical Physics · Physics 2025-05-20 V. I. Yukalov , E. P. Yukalova

Optimal a priori estimates are derived for the population risk, also known as the generalization error, of a regularized residual network model. An important part of the regularized model is the usage of a new path norm, called the weighted…

Machine Learning · Computer Science 2019-06-03 Weinan E , Chao Ma , Qingcan Wang

Boundary conditions provide a simple and physically compelling Wilsonian renormalization method in coordinate space in the framework of effective field theory as applied to nucleon-nucleon interaction in the non perturbative regime,…

Nuclear Theory · Physics 2007-05-23 M. Pavon Valderrama , E. Ruiz Arriola

As applied to quantum theories, the program of renormalization is successful for `renormalizable models' but fails for `nonrenormalizable models'. After some conceptual discussion and analysis, an enhanced program of renormalization is…

High Energy Physics - Theory · Physics 2009-05-01 John R. Klauder

We prove global Lipschitz regularity for a wide class of convex variational integrals among all functions in $W^{1,1}$ with prescribed (sufficiently regular) boundary values, which are not assumed to satisfy any geometrical constraint (as…

Analysis of PDEs · Mathematics 2018-02-28 Miroslav Bulíček , Erika Maringová , Bianca Stroffolini , Anna Verde

Based on the needs of convergence proofs of preconditioned proximal point methods, we introduce notions of partial strong submonotonicity and partial (metric) subregularity of set-valued maps. We study relationships between these two…

Optimization and Control · Mathematics 2020-03-02 Tuomo Valkonen

If we want to deform a compact Riemannian manifold with boundary using Ricci flow, we first need to decide on appropriate boundary conditions. We would like these conditions to reflect the geometric nature of the flow and allow for a…

Differential Geometry · Mathematics 2024-03-15 Rasmus Jouttijärvi

Many imaging problems require solving an inverse problem that is ill-conditioned or ill-posed. Imaging methods typically address this difficulty by regularising the estimation problem to make it well-posed. This often requires setting the…

Methodology · Statistics 2020-08-17 Ana F. Vidal , Valentin De Bortoli , Marcelo Pereyra , Alain Durmus