English
Related papers

Related papers: The gradient flow at higher orders in perturbation…

200 papers

The present notes provide an extended version of a small lecture course given at the Humboldt Universit\"at zu Berlin in the Winter Term 2022/23 (of 36 hours). The material starting in Section 5.4 was added afterwards. The aim of these…

Mathematical Physics · Physics 2023-06-09 Alexander Mielke

We establish conditions under which the worldsheet beta-functions of logarithmic conformal field theories can be derived as the gradient of some scalar function on the moduli space of running coupling constants. We derive a renormalization…

High Energy Physics - Theory · Physics 2009-10-31 Nick E. Mavromatos , Richard J. Szabo

A closure theory is developed for inhomogeneous turbulent flow, which enables a systematic derivation of the turbulence constitutive relations without relying on any empirical parameters. Renormalized-perturbation approximation is performed…

Fluid Dynamics · Physics 2019-06-26 Taketo Ariki

The Yang--Mills gradient flow and its extension to the fermion field provide a very general method to obtain renormalized observables in gauge theory. The method is applicable also with non-perturbative regularization such as lattice. The…

High Energy Physics - Lattice · Physics 2016-06-29 Hiroshi Suzuki

Despite the widespread use of gradient-based algorithms for optimizing high-dimensional non-convex functions, understanding their ability of finding good minima instead of being trapped in spurious ones remains to a large extent an open…

A continuous sequence of infinitesimal unitary transformations is used to diagonalize the quantum sine-Gordon model for \beta^2\in(2\pi,\infty). This approach can be understood as an extension of perturbative scaling theory since it links…

Statistical Mechanics · Physics 2009-10-31 Stefan Kehrein

We present a short overview on the strongest variational formulation for gradient flows of geodesically $\lambda$-convex functionals in metric spaces, with applications to diffusion equations in Wasserstein spaces of probability measures.…

Classical Analysis and ODEs · Mathematics 2010-09-21 Sara Daneri , Giuseppe Savaré

We investigate the effects of given pressure gradients on hydrodynamic flow equations. We obtain results in terms of implicit solutions and also in the framework of an extra-dimensional formalism involving the diffusion/Schrodinger…

Mathematical Physics · Physics 2008-11-26 Thomas Curtright , David Fairlie

Invariant parameterization schemes for the eddy-vorticity flux in the barotropic vorticity equation on the beta-plane are constructed and then applied to turbulence modeling. This construction is realized by the exhaustive description of…

Mathematical Physics · Physics 2013-12-12 Alexander Bihlo , Elsa Dos Santos Cardoso-Bihlo , Roman O. Popovych

Tseytlin has recently proposed that an action functional exists whose gradient generates to all orders in perturbation theory the Renormalization Group (RG) flow of the target space metric in the worldsheet sigma model. The gradient is…

High Energy Physics - Theory · Physics 2008-11-26 T. Oliynyk , V. Suneeta , E. Woolgar

The gradient flow is a valuable tool for the lattice community, with applications from scale-setting to implementing chiral fermions. Here I focus on the gradient flow as a means to suppress power-divergent mixing. Power-divergent mixing…

High Energy Physics - Lattice · Physics 2015-12-02 Christopher Monahan

The gradient flow method is a renormalization scheme in which the gauge field is flowed by the diffusion equation. The gradient flow scheme has benefits that the observables composed of flowed gauge fields do not require further…

High Energy Physics - Lattice · Physics 2025-01-31 Hironori Takei , Ken-Ichi Ishikawa , Masanori Okawa

Higher order conformal perturbation theory is studied for theories with and without boundaries. We identify systematically the universal quantities in the beta function equations, and we give explicit formulae for the universal coefficients…

High Energy Physics - Theory · Physics 2009-02-27 Matthias R. Gaberdiel , Anatoly Konechny , Cornelius Schmidt-Colinet

This article is devoted to presenting an abstract theory on time-fractional gradient flows for nonconvex energy functionals in Hilbert spaces. Main results consist of local and global in time existence of (continuous) strong solutions to…

Analysis of PDEs · Mathematics 2025-01-15 Goro Akagi , Yoshihito Nakajima

A computational study of higher-order derivative ratios on a time interval leading to the enstrophy peak is presented in the case of the 3D Taylor-Green vortex, a benchmark problem in the simulation of turbulent flows. The main finding is…

Analysis of PDEs · Mathematics 2026-05-22 Zoran Grujić , Muhammad Mohebujjaman

The gradient-flow dynamics of an arbitrary geometric quantity is derived using a generalization of Darcy's Law. We consider flows in both Lagrangian and Eulerian formulations. The Lagrangian formulation includes a dissipative modification…

Adaptation and Self-Organizing Systems · Physics 2008-04-28 Darryl D. Holm , Vakhtang Putkaradze , Cesare Tronci

We utilize the fluid-gravity duality to investigate the large order behavior of hydrodynamic gradient expansion of the dynamics of a gauge theory plasma system. This corresponds to the inclusion of dissipative terms and transport…

High Energy Physics - Theory · Physics 2013-05-27 Michal P. Heller , Romuald A. Janik , Przemyslaw Witaszczyk

Total variation gradient flows are important in several applied fields, including image analysis and materials science. In this paper, we review a few basic topics including definition of a solution, explicit examples and the notion of…

Analysis of PDEs · Mathematics 2024-01-31 Yoshikazu Giga , Hirotoshi Kuroda , Michał Łasica

We study a large deviation functional of density fluctuation by analyzing stochastic non-linear diffusion equations driven by the difference between the densities fixed at the boundaries. By using a fundamental equality that yields the…

Statistical Mechanics · Physics 2009-11-13 Shin-ichi Sasa

Gradient-based algorithms are effective for many machine learning tasks, but despite ample recent effort and some progress, it often remains unclear why they work in practice in optimising high-dimensional non-convex functions and why they…

Machine Learning · Computer Science 2020-04-02 Stefano Sarao Mannelli , Giulio Biroli , Chiara Cammarota , Florent Krzakala , Lenka Zdeborová