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This paper presents a geometric-variational approach to continuous and discrete {\it second-order} field theories following the methodology of \cite{MPS}. Staying entirely in the Lagrangian framework and letting $Y$ denote the configuration…

Differential Geometry · Mathematics 2015-06-26 Shinar Kouranbaeva , Steve Shkoller

We present the validity of stochastic averaging principle for non-autonomous slow-fast stochastic differential equations (SDEs) whose fast motions admit random periodic solutions. Our investigation is motivated by some problems arising from…

Probability · Mathematics 2018-12-11 Kenneth Uda

We sketch the main features of the Noether Symmetry Approach, a method to reduce and solve dynamics of physical systems by selecting Noether symmetries, which correspond to conserved quantities. Specifically, we take into account the…

General Relativity and Quantum Cosmology · Physics 2023-08-24 Francesco Bajardi , Salvatore Capozziello , Tiziana Di Salvo , Francesca Spinnato

The last decades have seen growing interest in connecting principles of thermodynamics with methods from analytical mechanics. The thermodynamic formalism has become an inspiring framework in the study of smooth dynamical systems, and…

Statistical Mechanics · Physics 2025-10-23 Aaron Beyen , Christian Maes

This paper considers the initial value problem of general nonlinear stochastic fractional integro-differential equations with weakly singular kernels. Our effort is devoted to establishing some fine estimates to include all the cases of…

Numerical Analysis · Mathematics 2021-09-15 Xinjie Dai , Aiguo Xiao , Weiping Bu

Prior mathematical work of Constantin and Iyer (2008, 2011) has shown that incompressible Navier-Stokes solutions possess infinitely-many stochastic Lagrangian conservation laws for vorticity, backward in time, which generalize the…

Fluid Dynamics · Physics 2019-12-17 Gregory L. Eyink , Akshat Gupta , Tamer Zaki

Variational integrators are derived for structure-preserving simulation of stochastic forced Hamiltonian systems. The derivation is based on a stochastic discrete Hamiltonian which approximates a type-II stochastic generating function for…

Numerical Analysis · Mathematics 2020-02-07 Michael Kraus , Tomasz M. Tyranowski

We construct sub-grid scale models of incompressible fluids by considering expectations of semi-martingale Lagrangian particle trajectories. Our construction is based on the Lagrangian decomposition of flow maps into mean and fluctuation…

Mathematical Physics · Physics 2025-04-15 Theo Diamantakis , Ruiao Hu

Several aspects of the connection between conserved integrals (invariants) and symmetries are illustrated within a hybrid Lagrangian-Hamiltonian framework for dynamical systems. Three examples are considered: a nonlinear oscillator with…

Mathematical Physics · Physics 2026-03-30 Stephen C. Anco

In this paper we have chosen to work with two different approaches to solving the inverse problem of the calculus of variation. The first approach is based on an integral representation of the Lagrangian function that uses the first…

Classical Physics · Physics 2020-08-10 Basir Ahamed Khan , Supriya Chatterjee , Golam Ali Sekh , Benoy Talukdar

This paper is concerned with the rigorous analysis of a recently proposed model of Zheng et. al. for describing nematic liquid crystals within the dense regime, with the orientation distribution function as the variable. A key feature of…

Analysis of PDEs · Mathematics 2017-03-01 Jamie M. Taylor

Noether's First Theorem yields conservation laws for Lagrangians with a variational symmetry group. The explicit formulae for the laws are well known and the symmetry group is known to act on the linear space generated by the conservation…

Differential Geometry · Mathematics 2013-02-18 Tania M. N. Goncalves , Elizabeth L. Mansfield

In this paper, we investigate specific least action principles for laws of stochastic processes within a framework which stands on filtrations preserving variations. The associated Euler-Lagrange conditions, which we obtain, exhibit a…

Probability · Mathematics 2022-08-08 Rémi Lassalle

Strong existence and pathwise uniqueness of solutions with $L^{\infty}$-vorticity of 2D stochastic Euler equations is proved. The noise is multiplicative and involves first derivatives. A Lagrangian approach is implemented, where a…

Probability · Mathematics 2016-09-09 Zdzisław Brzeźniak , Franco Flandoli , Mario Maurelli

The Boltzmann distribution for an equilibrium system constrains the statistics of the system by the energetics. Despite the non-equilibrium generalization of the Boltzmann distribution being studied extensively, a unified framework valid…

Statistical Mechanics · Physics 2025-11-05 Atul Tanaji Mohite , Heiko Rieger

Noether's calculus of invariant variations yields exact identities from functional symmetries. The standard application to an action integral allows to identify conservation laws. Here we rather consider generating functionals, such as the…

Statistical Mechanics · Physics 2021-08-16 Sophie Hermann , Matthias Schmidt

Recent theoretical work has developed the Hamilton's-principle analog of Lie-Poisson Hamiltonian systems defined on semidirect products. The main theoretical results are twofold: (1) Euler-Poincar\'e equations (the Lagrangian analog of…

chao-dyn · Physics 2007-05-23 Darryl D. Holm , Jerrold E. Marsden , Tudor S. Ratiu

We develop a unified geometric framework for dissipative mechanical systems based on uniform $q$-contact manifolds, which provide an extended phase space equipped with multiple contact $1$-forms. Within this setting, we construct both…

Mathematical Physics · Physics 2026-04-09 Melvin Leok , Cristina Sardón , Xuefeng Zhao

When discussing consequences of symmetries of dynamical systems based on Noether's first theorem, most standard textbooks on classical or quantum mechanics present a conclusion stating that a global continuous Lie symmetry implies the…

Mathematical Physics · Physics 2021-10-04 Daddy Balondo Iyela , Jan Govaerts

Stochastic differential equations (SDEs) are one of the most important representations of dynamical systems. They are notable for the ability to include a deterministic component of the system and a stochastic one to represent random…

Machine Learning · Computer Science 2021-05-19 Noura Dridi , Lucas Drumetz , Ronan Fablet
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