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Related papers: Lagrangian and Hamiltonian two-scale reduction

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We consider a general approach for the process of Lagrangian and Hamiltonian reduction by symmetries in chiral gauge models. This approach is used to show the complete integrability of several one dimensional texture equations arising in…

Dynamical Systems · Mathematics 2015-06-19 François Gay-Balmaz , Michael Monastyrsky , Tudor S. Ratiu

Learning and predicting the dynamics of physical systems requires a profound understanding of the underlying physical laws. Recent works on learning physical laws involve generalizing the equation discovery frameworks to the discovery of…

Machine Learning · Statistics 2023-10-11 Tapas Tripura , Souvik Chakraborty

We consider the Hamiltonian and Lagrangian embedding of a first-order, massive spin-one, gauge non-invariant theory involving anti-symmetric tensor field. We apply the BFV-BRST generalised canonical approach to convert the model to a first…

High Energy Physics - Theory · Physics 2009-11-07 E. Harikumar , M. Sivakumar

In this paper, some of formulations of Hamilton-Jacobi equations for Hamiltonian system and regular reduced Hamiltonian systems are given. At first, an important lemma is proved, and it is a modification for the corresponding result of…

Symplectic Geometry · Mathematics 2017-04-07 Hong Wang

The aim of the present text is twofold: to provide a compendium of Lagrangian and Hamiltonian geometries and to introduce and investigate new analytical Mechanics: Finslerian, Lagrangian and Hamiltonian. The fundamental equations (or…

Differential Geometry · Mathematics 2012-03-20 Radu Miron

Lattice quantum field theory calculations may potentially combine the advantages of Hamiltonian formulations with the scalability and control of conventional Lagrangian frameworks. However, such hybrid approaches need to consider (1) the…

High Energy Physics - Lattice · Physics 2024-11-05 Artur Avkhadiev , Lena Funcke , Karl Jansen , Stefan Kühn , Phiala E. Shanahan

We consider the question of existence of Hamiltonians for autonomous non-holonomic mechanical systems in this paper. The approach is elementary in the sense that the existence of a Hamiltonian for a given non-holonomic system is considered…

Classical Physics · Physics 2008-10-20 Christofer Cronstrom , Tommi Raita

Physical systems with symmetry arise abundantly in applications, and are endowed with interesting mathematical structures. The present paper focusses on linear reciprocal and input-output Hamiltonian systems. Their characterization is…

Optimization and Control · Mathematics 2025-04-07 Arjan van der Schaft , Rodolphe Sepulchre , Tom Chaffey

We develop a constructive procedure for arriving at the Hamilton-Jacobi framework for the so-called affine in acceleration theories by analysing the canonical constraint structure. We find two scenarios in dependence of the order of the…

High Energy Physics - Theory · Physics 2021-06-30 Alejandro Aguilar-Salas , Efraín Rojas

In this study, Lagrangian and Hamiltonian systems, which are mathematical models of mechanical systems, were introduced on the horizontal and the vertical distributions of tangent and cotangent bundles. Finally, some geometrical and…

Mathematical Physics · Physics 2009-01-12 Mehmet Tekkoyun

This work is devoted to review the modern geometric description of the Lagrangian and Hamiltonian formalisms of the Hamilton--Jacobi theory. The relation with the "classical" Hamiltonian approach using canonical transformations is also…

Mathematical Physics · Physics 2021-01-12 Narciso Román-Roy

Patterns arise spontaneously in a range of systems spanning the sciences, and their study typically focuses on mechanisms to understand their evolution in space-time. Increasingly, there has been a transition towards controlling these…

Soft Condensed Matter · Physics 2024-10-17 Vishaal Krishnan , Sumit Sinha , L. Mahadevan

The emergence of scanning probe and electron beam imaging techniques have allowed quantitative studies of atomic structure and minute details of electronic and vibrational structure on the level of individual atomic units. These microscopic…

Statistical Mechanics · Physics 2020-01-22 Sai Mani Prudhvi Valleti , Lukas Vlcek , Maxim Ziatdinov , Rama K. Vasudevan , Sergei V. Kalinin

In this paper, for a variety of nonholonomic (reducible) Hamiltonian systems, we first give to various distributional Hamiltonian systems, by analyzing carefully the dynamics and structures of the nonholonomic Hamiltonian systems. Secondly,…

Symplectic Geometry · Mathematics 2021-06-17 Manuel de León , Hong Wang

This paper presents a structure-preserving model reduction approach applicable to large-scale, nonlinear port-Hamiltonian systems. Structure preservation in the reduction step ensures the retention of port-Hamiltonian structure which, in…

Numerical Analysis · Mathematics 2016-01-05 Saifon Chaturantabut , Chris Beattie , Serkan Gugercin

We show that classical particle mechanics (Hamiltonian and Lagrangian consistent with relativistic electromagnetism) can be derived from three fundamental assumptions: infinite reducibility, deterministic and reversible evolution, and…

Classical Physics · Physics 2015-03-17 Gabriele Carcassi

Realistic models of physical world rely on differentiable symmetries that, in turn, correspond to conservation laws. Recent works on Lagrangian and Hamiltonian neural networks show that the underlying symmetries of a system can be easily…

Machine Learning · Computer Science 2021-10-13 Ravinder Bhattoo , Sayan Ranu , N. M. Anoop Krishnan

It is well known that the Lagrangian and Hamiltonian descriptions of field theories are equivalent at the discrete time level when variational integrators are used. Besides the symplectic Hamiltonian structure, many physical systems exhibit…

Numerical Analysis · Mathematics 2024-01-18 Andrea Brugnoli , Volker Mehrmann

This work concerns control-oriented and structure-preserving learning of low-dimensional approximations of high-dimensional physical systems, with a focus on mechanical systems. We investigate the integration of neural autoencoders in model…

Machine Learning · Computer Science 2023-12-12 Marco Lepri , Davide Bacciu , Cosimo Della Santina

Accurate models of the world are built upon notions of its underlying symmetries. In physics, these symmetries correspond to conservation laws, such as for energy and momentum. Yet even though neural network models see increasing use in the…

Machine Learning · Computer Science 2020-07-31 Miles Cranmer , Sam Greydanus , Stephan Hoyer , Peter Battaglia , David Spergel , Shirley Ho