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A coupled system of nonlinear mixed-type equations modeling early stages of angiogenesis is analyzed in a bounded domain. The system consists of stochastic differential equations describing the movement of the positions of the tip and stalk…

Analysis of PDEs · Mathematics 2022-06-24 Markus Fellner , Ansgar Jüngel

Stationary distributions of multivariate diffusion processes have recently been proposed as probabilistic models of causal systems in statistics and machine learning. Motivated by these developments, we study stationary multivariate…

Statistics Theory · Mathematics 2024-08-02 Tobias Boege , Mathias Drton , Benjamin Hollering , Sarah Lumpp , Pratik Misra , Daniela Schkoda

We develop an inertial coupling method for modeling the dynamics of point-like 'blob' particles immersed in an incompressible fluid, generalizing previous work for compressible fluids. The coupling consistently includes excess (positive or…

Soft Condensed Matter · Physics 2015-08-06 F. Balboa Usabiaga , R. Delgado-Buscalioni , B. E. Griffith , A. Donev

We solve two long standing problems for stochastic descriptions of open quantum system dynamics. First, we find the classical stochastic processes corresponding to non-Markovian quantum state diffusion and non-Markovian quantum jumps in…

Quantum Physics · Physics 2020-10-14 Kimmo Luoma , Walter T. Strunz , Jyrki Piilo

In this article we study a class of stochastic functional differential equations driven by L\'{e}vy processes (in particular, $\alpha$-stable processes), and obtain the existence and uniqueness of Markov solutions in small time intervals.…

Probability · Mathematics 2012-11-30 Xicheng Zhang

In this work we analyze the stability and convergence properties of a loosely-coupled scheme, called the kinematically coupled scheme, for interaction between an incompressible viscous fluid and a thin structure. We consider a benchmark…

Numerical Analysis · Mathematics 2014-06-16 Martina Bukac

In this paper, we are concerned with centered Markov Additive Processes $\{(X_t,Y_t)\}_{t\in\T}$ where the driving Markov process $\{X_t\}_{t\in\T}$ has a finite state space. Under suitable conditions, we provide a local limit theorem for…

Probability · Mathematics 2013-06-25 Loïc Hervé , James Ledoux

We study robust nonlinear filtering for stochastic models driven by L\'evy processes, where the signal and observation processes are coupled through common Brownian and jump noise. Robustness, defined as the continuous dependence of the…

Probability · Mathematics 2026-04-30 Sharan Srinivasan , Vijay Gupta , Harsha Honnappa

The main objective of this paper is a study of the asymptotic behavior of distributional solutions to the one-dimensional repulsive pressureless Euler-Poisson system. The system is a model for the dynamics of a mass distribution evolving on…

Analysis of PDEs · Mathematics 2026-05-08 Nicholas Biglin , Joseph Crachiola , Jack Curtis , Thomas Kunz , Omkar Maralappanavar , Adrian Tudorascu

Ising models, and the physical systems described by them, play a central role in generating entangled states for use in quantum metrology and quantum information. In particular, ultracold atomic gases, trapped ion systems, and Rydberg atoms…

We study the properties of a refined weak coupling limit that preserves complete positivity in order to describe non-Markovian dynamics in the spin-boson model. With this tool, we show the system presents a rich and new non-Markovian…

Quantum Physics · Physics 2017-04-10 Ángel Rivas

In this paper we introduce a constructive approach to study well-posedness of solutions to stochastic fluid-structure interaction with stochastic noise. We focus on a benchmark problem in stochastic fluid-structure interaction, and prove…

Analysis of PDEs · Mathematics 2022-03-31 Jeffrey Kuan , Sunčica Čanić

A maximal coupling of two diffusion processes makes two diffusion particles meet as early as possible. We study the uniqueness of maximal couplings under a sort of "reflection structure" which ensures the existence of such couplings. In…

Probability · Mathematics 2007-05-23 Kazumasa Kuwada

Identification of nonlinear dynamical systems is crucial across various fields, facilitating tasks such as control, prediction, optimization, and fault detection. Many applications require methods capable of handling complex systems while…

Machine Learning · Statistics 2024-11-05 Luc Brogat-Motte , Riccardo Bonalli , Alessandro Rudi

We construct a stochastic process whose drift is a function of the process's local time at a reflecting barrier. The process arose as a model of the interactions of a Brownian particle and an inert particle in (Knight, 2001). Interesting…

Probability · Mathematics 2007-05-23 David White

We describe stochastic calculus in the context of processes that are driven by an adapted point process of locally finite intensity and are differentiable between jumps. This includes Markov chains as well as non-Markov processes. By…

Probability · Mathematics 2016-07-26 Eric Foxall

Semilinear stochastic evolution equations with multiplicative L\'evy noise and monotone nonlinear drift are considered. Unlike other similar works, we do not impose coercivity conditions on coefficients. We establish the continuous…

Probability · Mathematics 2014-06-17 Erfan Salavati , Bijan Z. Zangeneh

We present a simple and efficient variational finite difference method for simulating time-dependent Stokes flow in the presence of irregular free surfaces and moving solid boundaries. The method uses an embedded boundary approach on…

Computational Physics · Physics 2011-05-25 Christopher Batty , Robert Bridson

Computational topology is a vibrant contemporary subfield and this article integrates knot theory and mathematical visualization. Previous work on computer graphics developed a sequence of smooth knots that were shown to converge point wise…

Geometric Topology · Mathematics 2016-03-29 J. Li , T. J. Peters , K. E. Jordan , P. Zaffetti

Complex networks are a successful framework to describe collective behaviour in many applications, but a notable gap remains in the current literature, that of proving asymptotic convergence in networks of piecewise-smooth systems. Indeed,…

Systems and Control · Computer Science 2020-12-03 Marco Coraggio , Pietro DeLellis , Mario di Bernardo