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Markovian diffusion processes yield a system of conservation laws which couple various conditional expectation values (local moments). Solutions of that closed system of deterministic partial differential equations stand for a regular…

Statistical Mechanics · Physics 2007-05-23 P. Garbaczewski

Estimating parameters of a diffusion process given continuous-time observations of the process via maximum likelihood approaches or, online, via stochastic gradient descent or Kalman filter formulations constitutes a well-established…

Methodology · Statistics 2025-03-17 Jan Albrecht , Sebastian Reich

This work is concerned with existence of weak solutions to discon- tinuous stochastic differential equations driven by multiplicative Gaus- sian noise and sliding mode control dynamics generated by stochastic differential equations with…

Optimization and Control · Mathematics 2015-04-27 Viorel Barbu , Stefano Bonaccorsi , Luciano Tubaro

The need to develop models to predict the motion of microrobots, or robots of a much smaller scale, moving in fluids in a low Reynolds number regime, and in particular, in non Newtonian fluids, cannot be understated. The article develops a…

Fluid Dynamics · Physics 2019-02-18 Yashaswini Murthy , Ravi Banavar

In this work, we discuss some points relevant for stochastic modelling of one- and two-phase turbulent flows. In the framework of stochastic modelling, also referred to PDF approach, we propose a new Langevin model including all viscosity…

Fluid Dynamics · Physics 2010-09-14 Sergio Chibbaro , Jean-Pierre Minier

The multiphase flow mechanism in miscible displacement through porous media is an important topic in various applications, such as petroleum engineering, low Reynolds number suspension flows, dusty gas dynamics, and fluidized beds. To…

Fluid Dynamics · Physics 2017-05-03 M. Jalal Ahammad , Jahrul M Alam

This thesis is dedicated to the study of stochastic processes; non-deterministic physical phenomena that can be well described by classical physics. The stochastic processes we are interested in are akin to Brownian Motion and can be…

Cosmology and Nongalactic Astrophysics · Physics 2023-06-06 Ashley Wilkins

Analytical (rational) mechanics is the mathematical structure of Newtonian deterministic dynamics developed by D'Alembert, Langrange, Hamilton, Jacobi, and many other luminaries of applied mathematics. Diffusion as a stochastic process of…

Mathematical Physics · Physics 2012-09-03 Hao Ge , Hong Qian

A new phenomenological model of turbulent fluctuations is constructed by considering the Lagrangian dynamics of 4 points (the tetrad). The closure of the equations of motion is achieved by postulating an anisotropic, i.e. tetrad shape…

chao-dyn · Physics 2009-10-31 Michael Chertkov , Alain Pumir , Boris I. Shraiman

This work is an analytical calculation of the path probability for random dynamics of mechanical system described by Langevin equation with Gaussian noise. The result shows an exponential dependence of the probability on the action. In the…

Statistical Mechanics · Physics 2015-10-27 Aziz El Kaabouchi , Qiuping A. Wang

In this paper, we address high-dimensional parametric estimation of the drift function in diffusion models, specifically focusing on a $d$-dimensional ergodic diffusion process observed at discrete time points. We consider both a general…

Statistics Theory · Mathematics 2025-10-09 Chiara Amorino , Francisco Pina , Mark Podolskij

Lagrangian particle tracking is essential for characterizing turbulent flows, but inferring particle acceleration from inherently noisy position data remains a significant challenge. Fluid particles in turbulence experience extreme,…

Data Analysis, Statistics and Probability · Physics 2026-02-27 Griffin M Kearney , Kasey M Laurent , Makan Fardad

This work is a numerical experiment of stochastic motion of conservative Hamiltonian system or weakly damped Brownian particles. The objective is to prove the existence of path probability and to compute its values. By observing a large…

Statistical Mechanics · Physics 2012-02-09 Lin Tongling , Pujos Cyril , Ou Congjie , Bi Wenping , Calvayrac Florent , Wang Qiuping A

The score function for the diffusion process, also known as the gradient of the log-density, is a basic concept to characterize the probability flow with important applications in the score-based diffusion generative modelling and the…

Numerical Analysis · Mathematics 2025-12-12 Yuanfei Huang , Chengyu Liu , Xiang Zhou

We study Max-Product and Max-Plus Systems with Markovian Jumps and focus on stochastic stability problems. At first, a Lyapunov function is derived for the asymptotically stable deterministic Max-Product Systems. This Lyapunov function is…

Systems and Control · Computer Science 2017-11-09 Ioannis Kordonis , Petros Maragos , George P. Papavassilopoulos

The functional method to derive the fractional Fokker-Planck equation for probability distribution from the Langevin equation with Levy stable noise is proposed. For the Cauchy stable noise we obtain the exact stationary probability density…

Statistical Mechanics · Physics 2008-10-07 A. A. Dubkov , B. Spagnolo

We consider the 2D incompressible Navier-Stokes equations driven by mildly degenerate noise that acts only on finitely many low Fourier modes, a setting that models large-scale stirring. For this system, we prove that the top Lyapunov…

Dynamical Systems · Mathematics 2026-05-15 Dengdi Chen , Yan Zheng

The purpose of this paper is to derive a critical link of parameters for the self-similar trajectories of jump-diffusions which are described as solutions of stochastic differential equations driven by $\alpha$-stable noise. This is done by…

Methodology · Statistics 2017-07-10 Jiao Song , Jiang-lun Wu

A position-dependent stochastic diffusion model of gating in ion channels is developed by considering the spatial variation of the diffusion coefficient between the closed and open states. It is assumed that a sensor which regulates the…

Mesoscale and Nanoscale Physics · Physics 2014-07-24 Samuel Robert Vaccaro

This paper presents a heuristic derivation of a geometric minimum action method that can be used to determine most-probable transition paths in noise-driven dynamical systems. Particular attention is focused on systems that violate detailed…

Statistical Mechanics · Physics 2018-03-06 John C. Neu , Akhil Ghanta , Stephen Teitsworth