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Related papers: Functional renormalisation group for turbulence

200 papers

Separating turbulent fluctuations from coherent large-scale background flows is a longstanding challenge in the analysis of numerical simulations and astronomical observations. Traditional approaches commonly rely on decomposition-based…

Fluid Dynamics · Physics 2026-05-27 Ji-Hoon Ha , Elena S. Volnova

The so-called renormalization group (RG) method is applied to derive kinetic and transport equations from the respective microscopic equations. The derived equations include Boltzmann equation in classical mechanics, Fokker-Planck equation,…

High Energy Physics - Theory · Physics 2009-11-07 Y. Hatta , T. Kunihiro

The Gaussian-filtered Navier-Stokes equations are examined theoretically and a generalized theory of their numerical stability is proposed. Using the exact expansion series of subfilter-scale stresses or integration by parts, the terms…

Fluid Dynamics · Physics 2007-05-23 Masato Ida , Nobuyuki Oshima

Fluid turbulence is characterized by strong coupling across a broad range of scales. Furthermore, besides the usual local cascades, such coupling may extend to interactions that are non-local in scale-space. As such the computational…

The pseudofermion functional renormalization group (pf-FRG) is one of the few numerical approaches that has been demonstrated to quantitatively determine the ordering tendencies of frustrated quantum magnets in two and three spatial…

Strongly Correlated Electrons · Physics 2018-02-21 Finn Lasse Buessen , Dietrich Roscher , Sebastian Diehl , Simon Trebst

Magnetohydrodynamic (MHD) turbulence is a crucial component of the current paradigms of star formation, dynamo theory, particle transport, magnetic reconnection and evolution of structure in the interstellar medium (ISM) of galaxies.…

Astrophysics of Galaxies · Physics 2021-10-27 Blakesley Burkhart

Data-driven turbulence modeling has been considered an effective method for improving the prediction accuracy of Reynolds-averaged Navier-Stokes equations. Related studies aimed to solve the discrepancy of traditional turbulence modeling by…

Fluid Dynamics · Physics 2020-10-19 Yuhui Yin , Pu Yang , Yufei Zhang , Haixin Chen , Song Fu

Many theoretical predictions in fluctuating hydrodynamics under uniform shear flow have lacked precise quantitative verification due to analytical approximations whose quantitative impacts are difficult to assess a priori and the…

Statistical Mechanics · Physics 2026-04-08 Hiroyoshi Nakano , Yuki Minami

Cellular suspensions such as dense bacterial flows exhibit a turbulence-like phase under certain conditions. We study this phenomenon of "active turbulence" statistically by using numerical tools. Following Wensink et al. [Proc. Natl. Acad.…

Fluid Dynamics · Physics 2018-02-15 Martin James , Michael Wilczek

This thesis is about new methods of achieving RG transformations, in both a continuum spacetime background and on a lattice discretization thereof. The subject is explored from the point of view of euclidean quantum field theory. As a…

High Energy Physics - Lattice · Physics 2020-06-16 Andrea Carosso

We study steady vortex sheet solutions of the Navier-Stokes in the limit of vanishing viscosity at fixed energy flow. We refer to this as the turbulent limit. These steady flows correspond to a minimum of the Euler Hamiltonian as a…

Fluid Dynamics · Physics 2021-03-31 Alexander Migdal

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

The renormalization group (RG) is an essential technique in statistical physics and quantum field theory, which considers scale-invariant properties of physical theories and how these theories' parameters change with scaling. Deep learning…

Statistical Mechanics · Physics 2023-08-23 Kelsie Taylor

We analyze the renormalization-group (RG) flows of two effective Lagrangians, one for measurement induced transitions of monitored quantum systems and one for entanglement transitions in random tensor networks. These Lagrangians, previously…

Statistical Mechanics · Physics 2024-09-20 Adam Nahum , Kay Joerg Wiese

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

We present a model describing evolution of the small-scale Navier-Stokes turbulence due to its stochastic distortions by much larger turbulent scales. This study is motivated by numerical findings (laval, 2001) that such interactions of…

Fluid Dynamics · Physics 2009-11-10 B. Dubrulle , J. -P. Laval , S. Nazarenko , O. Zaboronski

Some important concepts in the nonstandard analysis theory of turbulence are presented in this article. The structure of point, on which differential equations are defined, is analyzed. The distinction between the uniform point and the…

Fluid Dynamics · Physics 2009-11-10 Feng Wu

Turbulence is a complex system exhibiting both universal statistical features and prominent coherent structures. We model turbulence using coherent vortices distributed within a multi-scale statistical framework, termed `woven turbulence'.…

Fluid Dynamics · Physics 2025-12-04 Zishuo Han , Weiyu Shen , Yue Yang

Following the Gallavotti's conjecture, Stationary states of Navier-Stokes fluids are proposed to be described equivalently by alternative equations besides the NS equation itself. We propose a model system symmetric under time-reversal…

Fluid Dynamics · Physics 2021-12-22 Alice Jaccod , Sergio Chibbaro

Shell models allow much greater scale separations than those presently achievable with direct numerical simulations of the Navier-Stokes equations. Consequently, they are an invaluable tool for testing new concepts and ideas in the theory…

Fluid Dynamics · Physics 2024-12-11 John D. Gibbon , Dario Vincenzi