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We present geometric numerical integrators for contact flows that stem from a discretization of Herglotz' variational principle. First we show that the resulting discrete map is a contact transformation and that any contact map can be…

Numerical Analysis · Mathematics 2019-11-04 Mats Vermeeren , Alessandro Bravetti , Marcello Seri

The dynamics of evolving fluid films in the viscous Stokes limit is relevant to various applications, such as the modeling of lipid bilayers in cells. While the governing equations were formulated by Scriven in 1960, solving for the flow of…

Fluid Dynamics · Physics 2025-01-29 Cuncheng Zhu , David Saintillan , Albert Chern

In this paper we consider reduction of the stochastic Hamilton-Pontryagin principle formulated on the Pontryagin bundle of a manifold $Q$. We prove that a stochastic action invariant under the free and proper action of a Lie group $G$ drops…

Mathematical Physics · Physics 2026-01-15 Archishman Saha

We prove pathwise large deviation principles of slow variables in slow-fast systems in the limit of time-scale separation tending to infinity. In the limit regime we consider, the convergence of the slow variable to its deterministic limit…

Probability · Mathematics 2020-11-25 Richard C. Kraaij , Mikola C. Schlottke

While modern representation learning relies heavily on global error signals, decentralized algorithms driven by local interactions offer a fundamental distributed alternative. However, the macroscopic convergence properties of these…

Machine Learning · Computer Science 2026-04-21 Zilin Li , Weiwei Xu , Xuchun Tong , Xuanbo Lu , Xuanqi Zhao

The numerical analysis of variational integrators relies on variational error analysis, which relates the order of accuracy of a variational integrator with the order of approximation of the exact discrete Lagrangian by a computable…

Numerical Analysis · Mathematics 2011-02-15 Melvin Leok , Tatiana Shingel

Holm (Proc. Roy. Soc 2015) introduced a variational framework for stochastically parametrising unresolved scales of hydrodynamic motion. This variational framework preserves fundamental features of fluid dynamics, such as Kelvin's…

Fluid Dynamics · Physics 2021-03-03 Darryl D Holm , Erwin Luesink

We formulate a class of stochastic partial differential equations based on Kelvin's circulation theorem for ideal fluids. In these models, the velocity field is randomly transported by white-noise vector fields, as well as by its own…

Mathematical Physics · Physics 2020-02-19 Theodore D. Drivas , Darryl D. Holm , James-Michael Leahy

This paper is devoted to discrete mechanical systems subject to external forces. We introduce a discrete version of systems with Rayleigh-type forces, obtain the equations of motion and characterize the equivalence for these systems.…

Mathematical Physics · Physics 2022-05-03 Manuel de León , Manuel Lainz , Asier López-Gordón

We use a new variational method --based on the theory of anti-selfdual Lagrangians developed in [2] and [3]-- to establish the existence of solutions of convex Hamiltonian systems that connect two given Lagrangian submanifolds in $\R^{2N}$.…

Analysis of PDEs · Mathematics 2007-05-23 Nassif Ghoussoub , Abbas Moameni

In this work, we introduce a theory of stochastic integration with respect to symmetric $\alpha$-stable cylindrical L\'evy processes. Since $\alpha$-stable cylindrical L\'evy processes do not enjoy a semi-martingale decomposition, our…

Probability · Mathematics 2022-11-21 Gergely Bodó , Markus Riedle

We develop a theory of Hilbert-space valued stochastic integration with respect to cylindrical martingale-valued measures. As part of our construction, we expand the concept of quadratic variation, introduced by Veraar and Yaroslavtsev…

Probability · Mathematics 2025-06-17 Santiago Cambronero , David Campos , C. A. Fonseca-Mora , Darío Mena

Stochastic hybrid inclusions (SHIs) address situations with the stochastic continuous evolution in a stochastic differential inclusions and random jumps in the difference inclusions due to the forced (the state reaching a boundary in the…

Systems and Control · Electrical Eng. & Systems 2025-09-08 Hongye Su , Dandan Zhang

We consider distributed stochastic variational inequalities (VIs) on unbounded domains with the problem data that is heterogeneous (non-IID) and distributed across many devices. We make a very general assumption on the computational network…

Spike variation technique plays a crucial role in deriving Pontryagin's type maximum principle of optimal controls for differential equations of several types, including ordinary differential equations (ODEs), partial differential equations…

Optimization and Control · Mathematics 2022-09-13 Tianxiao Wang , Jiongmin Yong

In this paper, we develop a structure-preserving discretization of the Lagrangian framework for electromagnetism, combining techniques from variational integrators and discrete differential forms. This leads to a general family of…

Numerical Analysis · Mathematics 2015-11-05 Ari Stern , Yiying Tong , Mathieu Desbrun , Jerrold E. Marsden

This paper presents a Lie-Trotter splitting for inertial Langevin equations (Geometric Langevin Algorithm) and analyzes its long-time statistical properties. The splitting is defined as a composition of a variational integrator with an…

Numerical Analysis · Mathematics 2010-04-05 Nawaf Bou-Rabee , Houman Owhadi

Non-spherical particles transported by an anisotropic turbulent flow preferentially align with the mean shear and intermittently tumble when the local strain fluctuates. Such an intricate behaviour is here studied for inertialess,…

Soft Condensed Matter · Physics 2022-12-27 Lorenzo Campana , Mireille Bossy , Jeremie Bec

For the linearized setting of the dynamics of complex bodies we construct variational integrators and prove their convergence by making use of BV estimates on the rate fields. We allow for peculiar substructural inertia and internal…

Mathematical Physics · Physics 2008-03-12 Matteo Focardi , Paolo Maria Mariano

In this paper, we present a stochastic augmented Lagrangian approach on (possibly infinite-dimensional) Riemannian manifolds to solve stochastic optimization problems with a finite number of deterministic constraints.We investigate the…

Optimization and Control · Mathematics 2025-04-01 Caroline Geiersbach , Tim Suchan , Kathrin Welker
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