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We develop a stochastic parametrization, based on a `simple' deterministic model for the dynamics of steady longshore currents, that produces ensembles that are statistically consistent with field observations of these currents. Unlike…

Data Analysis, Statistics and Probability · Physics 2016-12-06 Juan M. Restrepo , Shankar C. Venkataramani

Stochastic processes are proposed whose master equations coincide with classical wave, telegraph, and Klein-Gordon equations. Similar to predecessors based on the Goldstein-Kac telegraph process, the model describes the motion of particles…

Statistical Mechanics · Physics 2015-05-18 A. V. Plyukhin

Markov processes with stochastic resetting towards the origin generically converge towards non-equilibrium steady-states. Long dynamical trajectories can be thus analyzed via the large deviations at Level 2.5 for the joint probability of…

Statistical Mechanics · Physics 2021-05-07 Cecile Monthus

We study a system whose dynamics are governed by predictions of its future states. A general formalism and concrete examples are presented. We find that the dynamical characteristics depend on how to shape the predictions as well as on how…

Other Condensed Matter · Physics 2015-06-25 Toru Ohira

The macroscopic behavior of dissipative stochastic partial differential equations usually can be described by a finite dimensional system. This article proves that a macroscopic reduced model may be constructed for stochastic…

Mathematical Physics · Physics 2008-12-11 Wei Wang , A. J. Roberts

The problem of determining the mathematical model of the dynamics of multi-dimensional control systems in the presence of noise under the condition that the correlation functions cannot be found. Known statistical dynamics of linear systems…

General Mathematics · Mathematics 2013-01-29 V. N. Tibabishev

Predictive statistical mechanics is a form of inference from available data, without additional assumptions, for predicting reproducible phenomena. By applying it to systems with Hamiltonian dynamics, a problem of predicting the macroscopic…

Statistical Mechanics · Physics 2015-09-22 Domagoj Kuic

The basic strategy underlying models of spontaneous wave function collapse (collapse models) is to modify the Schroedinger equation by including nonlinear stochastic terms, which tend to localize wave functions in space in a dynamical…

Quantum Physics · Physics 2015-06-18 A. Bassi , H. Ulbricht

The dynamics of Lagrangian particles in turbulence play a crucial role in mixing, transport, and dispersion in complex flows. Their trajectories exhibit highly non-trivial statistical behavior, motivating the development of surrogate models…

Linearly stable shear flows first transition to turbulence in the form of localised patches. At low Reynolds numbers, these turbulent patches tend to suddenly decay, following a memoryless process typical of rare events. How far in advance…

Fluid Dynamics · Physics 2025-07-10 Daniel Morón , Alberto Vela-Martín , Marc Avila

Modelling stochastic systems has many important applications. Normal form coordinate transforms are a powerful way to untangle interesting long term macroscale dynamics from detailed microscale dynamics. We explore such coordinate…

Dynamical Systems · Mathematics 2009-11-13 A. J. Roberts

By modeling the interaction of a system with an environment through a renewal approach, we demonstrate that completely positive non-Markovian dynamics may develop some unexplored non-standard statistical properties. The renewal approach is…

Quantum Physics · Physics 2009-08-07 Adrian A. Budini Paolo Grigolini

The identification of nonlinear dynamics from observations is essential for the alignment of the theoretical ideas and experimental data. The last, in turn, is often corrupted by the side effects and noise of different natures, so…

Machine Learning · Computer Science 2020-06-08 Anna Shalova , Ivan Oseledets

Stochastic exclusion processes play an integral role in the physics of non-equilibrium statistical mechanics. These models are Markovian processes, described by a classical master equation. In this paper a quantum mechanical version of a…

Quantum Physics · Physics 2015-03-13 Kristan Temme , Michael M. Wolf , Frank Verstraete

We characterize the dynamical behavior of continuous-time, Markovian quantum systems with respect to a subsystem of interest. Markovian dynamics describes a wide class of open quantum systems of relevance to quantum information processing,…

Quantum Physics · Physics 2010-12-08 Francesco Ticozzi , Lorenza Viola

We consider a class of growth models and models of turbulence based on the randomly stirred fluid. The similarity between the predictions of these models, noted a decade earlier, is understood on the basis of a stochastic quantization…

Statistical Mechanics · Physics 2007-05-23 Himadri S. Samanta , J. K. Bhattacharjee , D. Gangopadhyay

A novel probabilistic framework for modelling anomalous diffusion is presented. The resulting process is Markovian, non-homogeneous, non-stationary, non-ergodic, and state-dependent. The fundamental law governing this process is driven by…

Mathematical Physics · Physics 2025-03-07 Nestor Barraza , Gabriel Pena , Juliana Gambini , Florencia Carusela

A simple analytical model for a turbulent flow is proposed, which considers the flow as a collection of localized spatial structures that are composed of elementary "cells" in which the state of the particles (atoms or molecules) is…

Fluid Dynamics · Physics 2013-04-09 Sergei F. Chekmarev

The formalism of the particle dynamics in the space-time, where motion of free particles is primordially stochastic, is considered. The conventional dynamic formalism, obtained for the space-time, where the motion of free particles is…

General Physics · Physics 2011-03-21 Yuri A. Rylov

Many unsteady flows exhibiting complex dynamics are nevertheless characterized by emergent large-scale coherence in space and time. Reduced-order models based on Galerkin projection of the governing equations onto an orthogonal modal basis…

Fluid Dynamics · Physics 2022-06-28 Jared L. Callaham , Jean-Christophe Loiseau , Steven L. Brunton
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