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We investigate the dynamics of an inertial active Ornstein-Uhlenbeck particle suspended in a non-Markovian environment. The particle is additionally subjected to external forces, such as harmonic confinement and a magnetic field. Motivated…

Soft Condensed Matter · Physics 2025-10-15 Sanju S Pillai , M Muhsin , M Sahoo

The dynamics of compressible liquid-vapor flow depends sensitively on the microscale behavior at the phase boundary. We consider a sharp-interface approach, and propose a multiscale model to describe liquid-vapor flow accurately, without…

Numerical Analysis · Mathematics 2022-09-14 Jim Magiera , Christian Rohde

Accurately and stably solving the incompressible Navier--Stokes equations with physics-informed neural networks (PINNs) remains challenging, particularly for sparse or noisy observations and for flow regimes in which the local balance among…

Fluid Dynamics · Physics 2026-03-31 Ke Xu , Ze Tao , Fujun Liu

Stochastic chemical systems with diffusion are modeled with a reaction-diffusion master equation. On a macroscopic level, the governing equation is a reaction-diffusion equation for the averages of the chemical species. On a mesoscopic…

Numerical Analysis · Mathematics 2009-03-06 Stefan Engblom , Lars Ferm , Andreas Hellander , Per Lötstedt

Temporal coherence-persistent alignment across time-can arise between agents with fundamentally distinct dynamics, a behavior that classical diffusion models (e.g., Brownian motion, fractional Brownian motion, generalized Langevin equation)…

Statistical Mechanics · Physics 2025-05-19 Aranyak Sarkar

We introduce a diffuse interface model describing the evolution of a mixture of two different viscous incompressible fluids of equal density. The main novelty of the present contribution consists in the fact that the effects of temperature…

Analysis of PDEs · Mathematics 2014-01-15 Michela Eleuteri , Elisabetta Rocca , Giulio Schimperna

We discuss the two-dimensional motion of a Brownian particle that is confined to a harmonic trap and driven by a shear flow. The surrounding medium induces memory effects modelled by a linear, typically nonreciprocal coupling of the…

Statistical Mechanics · Physics 2024-04-26 Lea Fernandez , Siegfried Hess , Sabine H. L. Klapp

This paper presents a novel methodology for the direct numerical modeling and simulation of turbulent flows. The kinetic model equation is firstly extended to turbulent flow with the account of coupled evolution of kinetic, thermal, and…

Computational Physics · Physics 2025-03-11 Xiaojian Yang , Kun Xu

We explore the diffusion process in the non-Markovian spatio-temporal noise.%the escape rate problem in the non-Markovian spatio-temporal random noise. There is a non-trivial short memory regime, i.e., the Markovian limit characterized by a…

Statistical Mechanics · Physics 2009-11-13 Takaaki Monnai , Ayumu Sugita , Katsuhiro Nakamura

In the mechanics of inviscid conservative fluids, it is classical to generate the equations of dynamics by formulating with adequate variables, that the pressure integral calculated in the time-space domain corresponding to the motion of…

Classical Physics · Physics 2008-07-23 Henri Gouin , Jean-François Debieve

A stochastic representation of the dynamics of open quantum systems, suitable for non-perturbative system-reservoir interaction, non-Markovian effects and arbitrarily driven systems is presented. It includes the case of driving on…

Statistical Mechanics · Physics 2016-10-05 Jürgen T. Stockburger

Non-Markovian quantum state diffusion (NMQSD) is an exact method for calculating the reduced density matrix of an arbitrary subsystem interacting linearly with the radiation field. Applications of the theory have however been few due to the…

Quantum Physics · Physics 2007-05-23 Joshua Wilkie , Ray Ng

We provide a quantitative description of the evolution of memory from the apparently random Markovian dynamics of a pair of optically trapped colloidal microparticles in water. The particles are trapped in very close proximity of each other…

Soft Condensed Matter · Physics 2018-08-15 Shuvojit Paul , Randhir Kumar , Ayan Banerjee

We consider a multiscale approach based on immersed methods for the efficient computational modeling of tissues composed of an elastic matrix (in two or three-dimensions) and a thin vascular structure (treated as a co-dimension two…

Numerical Analysis · Mathematics 2021-11-18 Luca Heltai , Alfonso Caiazzo

An exact description of the statistical motion of active particles in three dimension is presented in the framework of a generalized diffusion equation. Such a generalization contemplates a non-local, in time and space, connecting (memory)…

Statistical Mechanics · Physics 2023-07-20 Francisco J Sevilla

The stochastic theory of non-relativistic quantum mechanics presented here relies heavily upon the theory of stochastic processes, with its definitions, theorems and specific vocabulary as well. Its main hypothesis states indeed that the…

Quantum Physics · Physics 2014-04-01 Maurice J. M. L. O. Godart

The authors present a study of the non equilibrium statistical properties of a one dimensional hard-rod fluid dissipating energy via inelastic collisions and subject to the action of a Gaussian heat bath, simulating an external driving…

Materials Science · Physics 2009-11-13 Umberto Marini-Bettolo-Marconi , Pedro Tarazona , Fabio Cecconi

Continuous-time Markov chains are used to model stochastic systems where transitions can occur at irregular times, e.g., birth-death processes, chemical reaction networks, population dynamics, and gene regulatory networks. We develop a…

Machine Learning · Statistics 2022-12-13 Majerle Reeves , Harish S. Bhat

The diffusion/relaxation behavior of polarized spins of pore filling fluid, as often probed by NMR relaxometry, is widely used to extract information on the pore-geometry. Such information is further interpreted as an indicator of the key…

Soft Condensed Matter · Physics 2016-09-13 Seungoh Ryu , Weishu Zhao , Gabriela Leu , Philip M. Singer , Hyung Joon Cho , Youngseuk Keehm

Bayesian inference for nonlinear diffusions, observed at discrete times, is a challenging task that has prompted the development of a number of algorithms, mainly within the computational statistics community. We propose a new direction,…

Computation · Statistics 2022-01-11 Matthew M. Graham , Alexandre H. Thiery , Alexandros Beskos
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