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The Lagrangian approach is natural to study issues of turbulent dispersion and mixing. We propose in this work a general Lagrangian stochastic model including velocity and acceleration as dynamical variables for inhomogeneous turbulent…

Fluid Dynamics · Physics 2020-05-01 Alessio Innocenti , Nicolas Mordant , Nick Stelzenmuller , Sergio Chibbaro

Infrared asymptotic behaviour of a scalar field, passively advected by a random shear flow, is studied by means of the field theoretic renormalization group and the operator product expansion. The advecting velocity is Gaussian, white in…

Chaotic Dynamics · Physics 2011-12-30 N. V. Antonov , A. V. Malyshev

We consider the model of a transverse vector (e.g. magnetic) field with the most general form of the nonlinearity, known as the ${\cal A}$ model, passively advected by a strongly compressible turbulent flow, governed by the randomly stirred…

Fluid Dynamics · Physics 2021-12-21 Nikolai V. Antonov , Maria M. Tumakova

ODE solvers with randomly sampled timestep sizes appear in the context of chaotic dynamical systems, differential equations with low regularity, and, implicitly, in stochastic optimisation. In this work, we propose and study the stochastic…

Numerical Analysis · Mathematics 2024-08-05 Jonas Latz

The interplay of such cornerstones of modern nonlinear fiber optics as a nonlinearity, stochasticity and polarization leads to variety of the noise induced instabilities including polarization attraction and escape phenomena harnessing of…

Passive scalar mixing (metals, molecules, etc.) in the turbulent interstellar medium (ISM) is critical for abundance patterns of stars and clusters, galaxy and star formation, and cooling from the circumgalactic medium. However, the…

Astrophysics of Galaxies · Physics 2017-03-22 Matthew J. Colbrook , Xiangcheng Ma , Philip F. Hopkins , Jonathan Squire

We investigate stochastic averaging theory for locally Lipschitz discrete-time nonlinear systems with stochastic perturbation and its applications to convergence analysis of discrete-time stochastic extremum seeking algorithms. Firstly, by…

Optimization and Control · Mathematics 2015-02-18 Shu-Jun Liu , Miroslav Krstic

Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter…

Statistical Mechanics · Physics 2018-01-23 Jakub Ślęzak , Ralf Metzler , Marcin Magdziarz

We integrate in closed implicit form the Navier-Stokes equations for an incompressible fluid and the kinematical dynamo equation, in smooth manifolds and Euclidean space. This integration is carried out by applying Stochastic Differential…

Mathematical Physics · Physics 2007-05-23 Diego L. Rapoport

We perform a qualitative analysis of the critical equation associated with a stationary ergodic Hamiltonian through a stochastic version of the metric method, where the notion of closed random stationary set, issued from stochastic…

Analysis of PDEs · Mathematics 2016-02-10 Andrea Davini , Antonio Siconolfi

A linear dispersive mechanism for error focusing in polychromatic solutions is identified. This local error pile-up corresponds to the existence of spurious caustics, which are allowed by the dispersive nature of the numerical error. From…

Analysis of PDEs · Mathematics 2007-05-23 Claire David , Pierre Sagaut , Tapan Sengupta

We develop, simulate and extend an initial proposition by Chaves et al. concerning a random incompressible vector field able to reproduce key ingredients of three-dimensional turbulence in both space and time. In this article, we focus on…

The onset of stochasticity is measured in $\Lambda$CDM cosmological simulations using a set of classical observables. It is quantified as the local derivative of the logarithm of the dispersion of a given observable (within a set of…

Astrophysics · Physics 2009-11-13 Jerome Thiebaut , Christophe Pichon , Thierry Sousbie , Simon Prunet , D. Pogosyan

Time-resolved single-cell omics data offers high-throughput, genome-wide measurements of cellular states, which are instrumental to reverse-engineer the processes underpinning cell fate. Such technologies are inherently destructive,…

Machine Learning · Computer Science 2026-02-04 Stephen Zhang , Suryanarayana Maddu , Xiaojie Qiu , Victor Chardès

We study a system of stochastically forced infinite-dimensional coupled harmonic oscillators. Although this system formally conserves energy and is not explicitly dissipative, we show that it has a nontrivial invariant probability measure.…

Mathematical Physics · Physics 2009-11-11 Jonathan C. Mattingly , Toufic M. Suidan , Eric Vanden-Eijnden

We develop a stochastic model for the velocity gradients dynamics along a Lagrangian trajectory. Comparing with different attempts proposed in the literature, the present model, at the cost of introducing a free parameter known in…

Fluid Dynamics · Physics 2018-02-23 Rodrigo M. Pereira , Luca Moriconi , Laurent Chevillard

Stochastic averaging allows for the reduction of the dimension and complexity of stochastic dynamical systems with multiple time scales, replacing fast variables with statistically equivalent stochastic processes in order to analyze…

Probability · Mathematics 2015-02-25 William F. Thompson , Rachel A. Kuske , Adam H. Monahan

In this perspective, we consider the development of statistical hydrodynamics, focusing on the way in which the intrinsic stochasticity of turbulent phenomena was identified and is being explored. A major purpose of our discussion is to…

Fluid Dynamics · Physics 2026-01-01 Gregory L. Eyink , Nigel Goldenfeld

We consider potential type dynamical systems in finite dimensions with two meta-stable states. They are subject to two sources of perturbation: a slow external periodic perturbation of period $T$ and a small Gaussian random perturbation of…

Probability · Mathematics 2007-05-23 Samuel Herrmann , Peter Imkeller , Dierk Peithmann

As the hunt for an Earth-like exoplanets has intensified in recent years, so has the effort to characterise and model the stellar signals that can hide or mimic small planetary signals. Stellar variability arises from a number of sources,…

Solar and Stellar Astrophysics · Physics 2024-04-19 Niamh K. O'Sullivan , Suzanne Aigrain