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A formalism of arithmetic partial differential equations (PDEs) is being developed in which one considers several arithmetic differentiations at one fixed prime. In this theory solutions can be defined in algebraically closed p-adic fields.…

Number Theory · Mathematics 2021-04-01 Alexandru Buium , Lance Edward Miller

When using dimensional regularization, the bare couplings are expressed as a power series in (2 - n/2)^{-1} where n is the number of dimensions. It is shown how the renormalization group can be used to sum the leading pole, next to leading…

High Energy Physics - Theory · Physics 2009-12-10 D. G. C. McKeon

We carry out the complete group classification of the class of (1+1)-dimensional linear Schr\"odinger equations with complex-valued potentials. After introducing the notion of uniformly semi-normalized classes of differential equations, we…

Mathematical Physics · Physics 2018-03-07 Célestin Kurujyibwami , Peter Basarab-Horwath , Roman O. Popovych

We investigate the one-dimensional polaron problem and calculate the ground state energy and the effective mass. We use a real-time renormalization group method and compare our results with first and second order perturbation theory, with…

Statistical Mechanics · Physics 2009-10-31 Markus Keil , Herbert Schoeller

This work deals with singular stochastic PDEs driven by non-translation invariant differential operators. We describe the renormalized equation for a very large class of spacetime dependent renormalization schemes. Our approach bypasses in…

Analysis of PDEs · Mathematics 2024-06-05 I. Bailleul , Y. Bruned

Neural operators have emerged as promising surrogate models for solving partial differential equations (PDEs), but struggle to generalise beyond training distributions and are often constrained to a fixed temporal discretisation. This work…

A simple criterion to optimise coarse-grainings for exact renormalisation group equations is given. It is aimed at improving the convergence of approximate solutions of flow equations. The optimisation criterion is generic, as it refers…

High Energy Physics - Theory · Physics 2009-07-09 Daniel F. Litim

A kernel-based approach for the learning of the solution operator of general nonhomogeneous partial differential equations (PDEs) is proposed. The method incorporates physical priors, typically encoded through the PDE operator, into a…

Numerical Analysis · Mathematics 2026-05-12 Jianyu Hu , Juan-Pablo Ortega

Based on our studies done on two-dimensional autonomous systems, forced non-autonomous systems and time-delayed systems, we propose a unified methodology - that uses renormalization group theory - for finding out existence of periodic…

Chaotic Dynamics · Physics 2015-05-19 Amartya Sarkar , J. K. Bhattacharjee , Sagar Chakraborty , Dhruba Banerjee

Mixed dimensional partial differential equations (PDEs) are equations coupling unknown fields defined over domains of differing topological dimension. Such equations naturally arise in a wide range of scientific fields including geology,…

Mathematical Software · Computer Science 2019-11-05 Cécile Daversin-Catty , Chris N. Richardson , Ada J. Ellingsrud , Marie E. Rognes

We define the renormalization group flow for a renormalizable interacting quantum field in curved spacetime via its behavior under scaling of the spacetime metric, $\g \to \lambda^2 \g$. We consider explicitly the case of a scalar field,…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Stefan Hollands , Robert M. Wald

Modeling real-world problems with partial differential equations (PDEs) is a prominent topic in scientific machine learning. Classic solvers for this task continue to play a central role, e.g. to generate training data for deep learning…

Machine Learning · Computer Science 2024-06-10 Tim Weiland , Marvin Pförtner , Philipp Hennig

The renormalization group (RG) method as a powerful tool for reduction of evolution equations is formulated in terms of the notion of invariant manifolds. We start with derivation of an exact RG equation which is analogous to the Wilsonian…

High Energy Physics - Theory · Physics 2016-09-06 S. -I. Ei , K. Fujii , T. Kunihiro

Learning underlying dynamics from data is important and challenging in many real-world scenarios. Incorporating differential equations (DEs) to design continuous networks has drawn much attention recently, however, most prior works make…

Machine Learning · Computer Science 2023-02-03 Yesom Park , Jaemoo Choi , Changyeon Yoon , Chang hoon Song , Myungjoo Kang

Solving partial differential equations (PDEs) using an annealing-based approach involves solving generalized eigenvalue problems. Discretizing a PDE yields a system of linear equations (SLE). Solving an SLE can be formulated as a general…

Numerical Analysis · Mathematics 2026-05-11 Kazue Kudo

Renormalization is a powerful technique in statistical physics to extract the large-scale behavior of interacting many-body models. These notes aim to give an introduction to perturbative methods that operate on the level of the stochastic…

Statistical Mechanics · Physics 2023-03-09 Nikos Papanikolaou , Thomas Speck

The renormalization group (RG) is a powerful theoretical framework developed to consistently transform the description of configurations of systems with many degrees of freedom, along with the associated model parameters and coupling…

Statistical Mechanics · Physics 2026-04-20 Andrea Gabrielli , Diego Garlaschelli , Subodh P. Patil , M. Ángeles Serrano

We continue the study of the renormalization group and decoupling of massive fields in curved space, started in the previous article and analyse the higher derivative sector of the vacuum metric-dependent action of the Standard Model. The…

High Energy Physics - Phenomenology · Physics 2009-11-10 Eduard V. Gorbar , Ilya L. Shapiro

For any given algebra of local observables in Minkowski space an associated scaling algebra is constructed on which renormalization group (scaling) transformations act in a canonical manner. The method can be carried over to arbitrary…

High Energy Physics - Theory · Physics 2015-06-26 Detlev Buchholz , Rainer Verch

We present a framework for solving a broad class of ill-posed inverse problems governed by partial differential equations (PDEs), where the target coefficients of the forward operator are recovered through an iterative regularization scheme…