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The method of potential solutions of Fokker-Planck equations is used to develop a transport equation for the joint probability of N coupled stochastic variables with the Dirichlet distribution as its asymptotic solution. To ensure a bounded…

Mathematical Physics · Physics 2013-03-05 J. Bakosi , J. R. Ristorcelli

In this paper we study the problem of computing the effective diffusivity for a particle moving in chaotic and stochastic flows. In addition we numerically investigate the residual diffusion phenomenon in chaotic advection. The residual…

Numerical Analysis · Mathematics 2017-11-28 Zhongjian Wang , Jack Xin , Zhiwen Zhang

By combining the ideas of Cartan's equivalence method and the method of the equivariant moving frame for pseudo-groups, we develop an efficient method for solving equivalence problems arising from horizontal Lie pseudo-group actions. The…

Differential Geometry · Mathematics 2018-11-02 Orn Arnaldsson

In this work we develop a stochastic algorithm to integrate the Cahn-Hilliard equations. The algorithm is based on Gillespie's stochastic simulation algorithm, also known as kinetic Monte Carlo. The deterministic integration of the phase…

Statistical Mechanics · Physics 2024-02-14 Qianran Yu , Nicholas Julian , Jaime Marian , Enrique Martinez

We give a short and elementary introduction to Lie group methods. A selection of applications of Lie group integrators are discussed. Finally, a family of symplectic integrators on cotangent bundles of Lie groups is presented and the notion…

Numerical Analysis · Mathematics 2014-01-22 Elena Celledoni , Håkon Marthinsen , Brynjulf Owren

Nonequilibrium flows have been frequently encountered in various aerospace engineering applications. To understand nonequilibrium physics, multiscale effects, and the dynamics in these applications, an effective and reliable multiscale…

Fluid Dynamics · Physics 2024-07-23 Wenpei Long , Yufeng Wei , Kun Xu

We establish Ecalle's mould calculus in an abstract Lie-theoretic setting and use it to solve a normalization problem, which covers several formal normal form problems in the theory of dynamical systems. The mould formalism allows us to…

Dynamical Systems · Mathematics 2018-01-17 Thierry Paul , David Sauzin

This report investigates the fitting of the Hessian or its inverse for stochastic optimizations using a Hessian fitting criterion derived from the preconditioned stochastic gradient descent (PSGD) method. This criterion is closely related…

Machine Learning · Statistics 2025-12-02 Xi-Lin Li

A mathematical model for description of the viscous fingering induced by a chemical reaction is under study. This complicated five-component model is reduced to a three-component diffusive Lotka-Volterra system with convection by…

Mathematical Physics · Physics 2025-12-19 Roman Cherniha , Vasyl' Davydovych

We show that an interesting class of functionals of stochastic differential equations can be approximated by a Chen-Fliess series of iterated stochastic integrals and give a L^{2} error estimate, thus generalizing the standard stochastic…

Probability · Mathematics 2011-11-10 Christian Litterer , Harald Oberhauser

A Skeleton-stabilized ImmersoGeometric Analysis technique is proposed for incompressible viscous flow problems with moderate Reynolds number. The proposed formulation fits within the framework of the finite cell method, where essential…

Via a Bismut-Elworthy-Li formula from [KPP23], we derive uniform gradient estimates for transition semigroups associated with stochastic differential equations driven by a large class of cylindrical L\'{e}vy processes which includes the…

Probability · Mathematics 2025-09-09 Thanh Dang , Lingjiong Zhu

Simulating turbulent fluid flows is a computationally prohibitive task, as it requires the resolution of fine-scale structures and the capture of complex nonlinear interactions across multiple scales. This is particularly the case in direct…

Fluid Dynamics · Physics 2026-04-22 Ismaël Zighed , Nicolas Thome , Patrick Gallinari , Taraneh Sayadi

We develop Riemannian approaches to variational autoencoders (VAEs) for PDE-type ambient data with regularizing geometric latent dynamics, which we refer to as VAE-DLM, or VAEs with dynamical latent manifolds. We redevelop the VAE framework…

Machine Learning · Computer Science 2026-01-21 Andrew Gracyk

The construction of discontinuous Galerkin (DG) methods for the compressible Euler or Navier-Stokes equations (NSE) includes the approximation of non-linear flux terms in the volume integrals. The terms can lead to aliasing and stability…

Numerical Analysis · Mathematics 2020-08-26 Nico Krais , Gero Schnücke , Thomas Bolemann , Gregor Gassner

A Lie system is a non-autonomous system of ordinary differential equations describing the integral curves of a $t$-dependent vector field taking values in a finite-dimensional Lie algebra of vector fields. Lie systems have been generalised…

Mathematical Physics · Physics 2023-04-25 J. F. Cariñena , J. de Lucas , C. Sardón

Uncertainties have become a major concern in integrated circuit design. In order to avoid the huge number of repeated simulations in conventional Monte Carlo flows, this paper presents an intrusive spectral simulator for statistical circuit…

Computational Engineering, Finance, and Science · Computer Science 2016-11-18 Zheng Zhang , Tarek A. El-Moselhy , Ibrahim , M. Elfadel , Luca Daniel

We introduce exponential numerical integration methods for stiff stochastic dynamical systems of the form $d\mathbf{z}_t = L(t)\mathbf{z}_tdt + \mathbf{f}(t)dt + Q(t)d\mathbf{W}_t$. We consider the setting of time-varying operators $L(t),…

Numerical Analysis · Mathematics 2022-12-20 Dev Jasuja , P. J. Atzberger

Standard Eulerian--Lagrangian (EL) methods generally employ drag force models that only represent the mean hydrodynamic force acting upon a particle-laden suspension. Consequently, higher-order drag force statistics, arising from…

Fluid Dynamics · Physics 2021-03-22 Aaron M. Lattanzi , Vahid Tavanashad , Shankar Subramaniam , Jesse Capecelatro

Using the concept of self-decomposable subordinators introduced in Gardini et al. [11], we build a new bivariate Normal Inverse Gaussian process that can capture stochastic delays. In addition, we also develop a novel path simulation scheme…

Computational Finance · Quantitative Finance 2020-11-10 Matteo Gardini , Piergiacomo Sabino , Emanuela Sasso
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