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Related papers: A Renormalization Group Approach to Spontaneous St…

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We consider fluctuating Sabra models of turbulence, which exhibit the phenomenon of spontaneous stochasticity: their solutions converge to a stochastic process in the ideal limit, when both viscosity and small-scale noise vanish. In this…

Chaotic Dynamics · Physics 2026-03-06 Alexei A. Mailybaev

We present a renormalization-group perspective on spontaneous stochasticity in hydrodynamic turbulence, viewed through the lens of multiscale dynamical systems. Building on previously established results for a solvable multiscale Arnold's…

Chaotic Dynamics · Physics 2026-03-02 Alexei A. Mailybaev , Luca Moriconi

We present a renormalization group (RG) approach to explain universal features of extreme statistics, applied here to independent, identically distributed variables. The outlines of the theory have been described in a previous Letter, the…

Statistical Mechanics · Physics 2015-05-18 G. Gyorgyi , N. R. Moloney , K. Ozogany , Z. Racz , M. Droz

The renormalization group (RG) method is one of the singular perturbation methods which is used in search for asymptotic behavior of solutions of differential equations. In this article, time-independent vector fields and time (almost)…

Dynamical Systems · Mathematics 2015-05-14 Hayato Chiba

We show with several examples that renormalization group (RG) theory can be used to understand singular and reductive perturbation methods in a unified fashion. Amplitude equations describing slow motion dynamics in nonequilibrium phenomena…

Condensed Matter · Physics 2009-10-22 Lin-Yuan Chen , Nigel Goldenfeld , Y. Oono

Discretization of continuous stochastic processes is needed to numerically simulate them or to infer models from experimental time series. However, depending on the nature of the process, the same discretization scheme, if not accurate…

Machine Learning · Statistics 2022-05-04 Federica Ferretti , Victor Chardès , Thierry Mora , Aleksandra M Walczak , Irene Giardina

In this paper, we study the stability and bifurcations of spontaneous stochasticity using an approach reminiscent of the Feigenbaum renormalization group (RG). We consider dynamical models on a self-similar space-time lattice as toy models…

Mathematical Physics · Physics 2025-04-30 Alexei A. Mailybaev

We consider an initial value problem for shell models that mimic turbulent velocity fluctuations over a geometric sequence of scales. Our goal is to study the convergence of solutions in the inviscid (more generally, vanishing…

Analysis of PDEs · Mathematics 2025-08-07 Alexei A. Mailybaev

These notes provide a concise introduction to important applications of the renormalization group (RG) in statistical physics. After reviewing the scaling approach and Ginzburg-Landau theory for critical phenomena, Wilson's momentum shell…

Statistical Mechanics · Physics 2015-03-19 Uwe C. Tauber

We look at the limit distributions of sums of deterministic chaotic variables in unimodal maps and find a remarkable renormalization group (RG) structure associated to the operation of increment of summands and rescaling. In this structure…

Statistical Mechanics · Physics 2015-05-14 Miguel Angel Fuentes , Alberto Robledo

The renormalization group (RG) method is extended for global asymptotic analysis of discrete systems. We show that the RG equation in the discretized form leads to difference equations corresponding to the Stuart-Landau or Ginzburg-Landau…

patt-sol · Physics 2009-10-30 T. Kunihiro , J. Matsukidaira

A generalization of the Renormalization Group, which describes order-parameter fluctuations in finite systems, is developed in the specific context of percolation. This ``Stochastic Renormalization Group'' (SRG) expresses statistical…

Statistical Mechanics · Physics 2009-11-07 Martin Z. Bazant

The paper discusses extensions of the renormalization group (RG) formalism for 3D incompressible Euler equations, which can be used for describing singularities developing in finite (blowup) or infinite time from smooth initial conditions…

Fluid Dynamics · Physics 2012-05-23 Alexei A. Mailybaev

We develop a renormalization group (RG) description of the localization properties of onedimensional (1D) quasiperiodic lattice models. The RG flow is induced by increasing the unit cell of subsequent commensurate approximants. Phases of…

Disordered Systems and Neural Networks · Physics 2023-10-10 Miguel Gonçalves , Bruno Amorim , Eduardo V. Castro , Pedro Ribeiro

We present a numerical implementation of the renormalization group (RG) for partial differential equations, constructing similarity solutions and travelling waves. We show that for a large class of well-localized initial conditions,…

chao-dyn · Physics 2009-10-22 Lin-Yuan Chen , Nigel Goldenfeld

The field theoretic renormalization group (RG) is applied to the model of a near-equilibrium fluid coupled to a scalar field (like temperature or density of an impurity) which is active, that is, influencing the dynamics of the fluid…

Statistical Mechanics · Physics 2021-09-15 N. V. Antonov , M. M. Kostenko

It has long been known that particles with short-range repulsive interactions in spatial dimension d=1 form universal quantum liquids in the low density limit: all properties can be related to those of the spinless free Fermi gas. Previous…

Superconductivity · Physics 2011-07-19 Predrag Nikolic , Subir Sachdev

We develop a Renormalization Group (RG) approach to the study of existence and uniqueness of solutions to stochastic partial differential equations driven by space-time white noise. As an example we prove well-posedness and independence of…

Probability · Mathematics 2015-02-20 Antti Kupiainen

Scaling concepts and renormalization group (RG) methods are applied to a simple linear model of human posture control consisting of a trembling or quivering string subject to damping and restoring forces. The string is driven by…

Condensed Matter · Physics 2009-10-31 Francisco Alonso-Sanchez , David Hochberg

In this thesis we investigate the Renormalization Group (RG) approach in finite-dimensional glassy systems, whose critical features are still not well-established, or simply unknown. We focus on spin and structural-glass models built on…

Disordered Systems and Neural Networks · Physics 2015-04-02 Michele Castellana
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