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We present a status report on a discrete approach to the the near-equilibrium statistical theory of three-dimensional turbulence, which generalizes earlier work by no longer requiring that the vorticity field be a union of discrete vortex…

Numerical Analysis · Mathematics 2025-10-20 G. I. Barenblatt , A. J. Chorin

We present a generalized picture of intermittency in turbulence that is based on the theory of stochastic processes. To this end, we rely on the experimentally and numerically verified finding by R.~Friedrich and J.~Peinke [Phys. Rev. Lett.…

Fluid Dynamics · Physics 2020-08-18 J. Friedrich , R. Grauer

Control barrier functions are widely used to synthesize safety-critical controls. However, the presence of Gaussian-type noise in dynamical systems can generate unbounded signals and potentially result in severe consequences. Although…

Systems and Control · Electrical Eng. & Systems 2023-12-21 Chuanzheng Wang , Yiming Meng , Jun Liu , Stephen Smith

In this paper, enlightened by the asymptotic expansion methodology developed by Li(2013b) and Li and Chen (2016), we propose a Taylor-type approximation for the transition densities of the stochastic differential equations (SDEs) driven by…

Computational Finance · Quantitative Finance 2020-03-16 Fan Jiang , Xin Zang , Jingping Yang

For the generalized statistical mechanics based on the Tsallis entropy, a variational perturbation approximation method with the principle of minimal sensitivity is developed by calculating the generalized free energy up to the third order…

Statistical Mechanics · Physics 2007-05-23 Wen-Fa Lu

We study the long time behavior of isentropic compressible Euler equations with linear damping driven by a white-in-time noise, on a one-dimensional torus. We prove the existence of a statistically stationary solution in the class of weak…

Analysis of PDEs · Mathematics 2025-11-03 Jeffrey Kuan , Krutika Tawri , Konstantina Trivisa

In uncertainty quantification, a stochastic modelling is often applied, where parameters are substituted by random variables. We investigate linear dynamical systems of ordinary differential equations with a quantity of interest as output.…

Numerical Analysis · Mathematics 2019-09-23 Roland Pulch , Akil Narayan

We apply the methods of Field Theory to study the turbulent regimes of statistical systems. First we show how one can find their probability densities. For the case of the theory of wave turbulence with four-wave interaction we calculate…

High Energy Physics - Theory · Physics 2009-10-28 V. Gurarie

We give a new proof of the large deviation principle from the hydrodynamic limit for the Ginzberg-Landau model studied in Donsker and Varadhan (1989) using techniques from the theory of stochastic control and weak convergence methods. The…

Probability · Mathematics 2018-03-28 Sayan Banerjee , Amarjit Budhiraja , Michael Perlmutter

We propose a simple model for the phenomenon of Eulerian spontaneous stochasticity in turbulence. This model is solved rigorously, proving that infinitesimal small-scale noise in otherwise a deterministic multi-scale system yields a…

Chaotic Dynamics · Physics 2022-01-19 Alexei A. Mailybaev , Artem Raibekas

Stochastic approximation (SA) is a method for finding the root of an operator perturbed by noise. There is a rich literature establishing the asymptotic normality of rescaled SA iterates under fairly mild conditions. However, these…

Machine Learning · Statistics 2026-02-17 Shaan Ul Haque , Zedong Wang , Zixuan Zhang , Siva Theja Maguluri

We consider a generic Hamiltonian system of nonlinear interacting waves with 3-wave interactions. In the kinetic regime of wave turbulence, which assumes weak nonlinearity and large system size, the relevant observable associated with the…

Statistical Mechanics · Physics 2022-09-07 Jules Guioth , Freddy Bouchet , Gregory L. Eyink

We establish a diffusion approximation for a class of multi-agent controlled queueing systems, demonstrating their convergence to a system of interacting reflected Ornstein--Uhlenbeck (OU) processes. The limiting process captures essential…

Probability · Mathematics 2026-01-12 Thoa Thieu , Roderick Melnik

The dynamics of interacting quantum systems in the presence of disorder is studied and an exact representation for disorder-averaged quantities via Ito stochastic calculus is obtained. The stochastic integral representation affords many…

Quantum Physics · Physics 2018-09-13 Ivana Kurecic , Tobias J. Osborne

Recently it has been shown by the present author [H. Hasegawa, Phys. Rev. E (in press): arXiv:0904.2399] that the interpolation approximation (IA) to the generalized Bose-Einstein and Femi-Dirac distributions yields results in agreement…

Statistical Mechanics · Physics 2015-05-13 Hideo Hasegawa

We propose a simple modification, the Gaussian truncation, of the probability density function which was obtained by Beck (2001) to fit the experimental distribution of fluid particle acceleration component from fully developed fluid…

Statistical Mechanics · Physics 2007-05-23 A. K. Aringazin , M. I. Mazhitov

This paper presents a nonlinear model predictive control strategy for stochastic systems with general (state and input dependent) disturbances subject to chance constraints. Our approach uses an online computed stochastic tube to ensure…

Systems and Control · Electrical Eng. & Systems 2022-07-19 Henning Schlüter , Frank Allgöwer

We extend collisional quantum thermometry schemes to allow for stochasticity in the waiting time between successive collisions. We establish that introducing randomness through a suitable waiting time distribution, the Weibull distribution,…

Quantum Physics · Physics 2021-12-15 Eoin O'Connor , Bassano Vacchini , Steve Campbell

A generalization of the $3D$ Euler-Voigt-$\alpha$ model is obtained by introducing derivatives of arbitrary order $\beta$ (instead of $2$) in the Helmholtz operator. The $\beta \to \infty$ limit is shown to correspond to Galerkin truncation…

Fluid Dynamics · Physics 2015-07-30 Giuseppe Di Molfetta , Giorgio Krstlulovic , Marc Brachet

The present research proposes a new memory-efficient method using diffusion models to inject turbulent inflow conditions into Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) for various flow problems. A guided diffusion…