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Energy methods for constructing time-stepping algorithms are of increased interest in application to nonlinear problems, since numerical stability can be inferred from the conservation of the system energy. Alternatively, symplectic…

Computational Physics · Physics 2020-08-24 Vasileios Chatziioannou

This work proposes a suite of numerical techniques to facilitate the design of structure-preserving integrators for nonlinear dynamics. The celebrated LaBudde-Greenspan integrator and various energy-momentum schemes adopt a difference…

Numerical Analysis · Mathematics 2023-05-17 Ju Liu

Recently, continuous-time dynamical systems have proved useful in providing conceptual and quantitative insights into gradient-based optimization, widely used in modern machine learning and statistics. An important question that arises in…

Optimization and Control · Mathematics 2021-04-29 Guilherme França , Michael I. Jordan , René Vidal

We develop a unified geometric framework for mechanical systems that combine conservative and dissipative dynamics by formulating them on contact manifolds. Within this setting, we identify the Reeb vector field as the intrinsic generator…

Mathematical Physics · Physics 2025-12-16 Vinesh Vijayan , Pasupuleti Thejasree , P Satish Kumar , K Suganya

Variational integrators are derived for structure-preserving simulation of stochastic Hamiltonian systems with a certain type of multiplicative noise arising in geometric mechanics. The derivation is based on a stochastic discrete…

Numerical Analysis · Mathematics 2019-07-31 Darryl D. Holm , Tomasz M. Tyranowski

In this paper, we develop a framework to construct energy-preserving methods for multi-components Hamiltonian systems, combining the exponential integrator and the partitioned averaged vector field method. This leads to numerical schemes…

Numerical Analysis · Mathematics 2021-11-08 X. Gu , C. Jiang , Y. Wang , W. Cai

We reconsider the fundamental problem of coarse-graining infinite-dimensional Hamiltonian dynamics to obtain a macroscopic system which includes dissipative mechanisms. In particular, we study the thermodynamical implications concerning…

Mathematical Physics · Physics 2025-06-06 Alexander Mielke , Mark A. Peletier , Johannes Zimmer

Symplectic integrators offer many advantages for the numerical solution of Hamiltonian differential equations, including bounded energy error and the preservation of invariant sets. Two of the central Hamiltonian systems encountered in…

Plasma Physics · Physics 2018-05-23 C. Leland Ellison , John M. Finn , Joshua W. Burby , Michael Kraus , Hong Qin , William M. Tang

Reduced basis methods are popular for approximately solving large and complex systems of differential equations. However, conventional reduced basis methods do not generally preserve conservation laws and symmetries of the full order model.…

Numerical Analysis · Mathematics 2018-03-20 Babak Maboudi Afkham , Jan S. Hesthaven

We address the problem of constructing numerical integrators for nonholonomic Lagrangian systems that enjoy appropriate discrete versions of the geometric properties of the continuous flow, including the preservation of energy. Building on…

Numerical Analysis · Mathematics 2025-10-20 Jorge Cortes

In this work, we study long-time numerical integration of Hamiltonian systems subject to linear perturbations. By introducing an energy-induced metric, we establish a straightforward, coordinate-free criterion for dissipativity that ensures…

Numerical Analysis · Mathematics 2026-03-03 Lu Li , Xiaoli Li , Zaijiu Shang , Quanquan Xu

We introduce a novel numerical method to integrate partial differential equations representing the Hamiltonian dynamics of field theories. It is a multi-symplectic integrator that locally conserves the stress-energy tensor with an excellent…

Numerical Analysis · Mathematics 2017-02-23 Hugo Ricateau , Leticia F. Cugliandolo

Recently, a whole class of evergy-preserving integrators has been derived for the numerical solution of Hamiltonian problems. In the mainstream of this research, we have defined a new family of symplectic integrators depending on a real…

Numerical Analysis · Mathematics 2010-09-30 Luigi Brugnano , Felice Iavernaro , Donato Trigiante

Hamiltonian systems of ordinary and partial differential equations are fundamental mathematical models spanning virtually all physical scales. A critical property for the robustness and stability of computational methods in such systems is…

Quantum Physics · Physics 2025-02-25 Hsuan-Cheng Wu , Xiantao Li

We introduce energy-preserving integrators for nonholonomic mechanical systems. We will see that the nonholonomic dynamics is completely determined by a triple $({\mathcal D}^*, \Pi, \mathcal{H})$, where ${\mathcal D}^*$ is the dual of the…

Numerical Analysis · Mathematics 2016-05-11 Elena Celledoni , Marta Farré Puiggalí , Eirik Hoel Høiseth , David Martín de Diego

A variational formulation for non-equilibrium thermodynamics was developed by Gay-Balmaz and Yoshimura. In a recent article, the first two authors of the present paper introduced partially cosymplectic structures as a geometric framework…

Mathematical Physics · Physics 2026-02-03 Jaime Bajo , Manuel de León , Asier López-Gordón

A fixed time-step variational integrator cannot preserve momentum, energy, and symplectic form simultaneously for nonintegrable systems. This barrier can be overcome by treating time as a discrete dynamic variable and deriving adaptive…

Numerical Analysis · Mathematics 2022-08-17 Harsh Sharma , Jeff Borggaard , Mayuresh Patil , Craig Woolsey

Numerical methods that preserve geometric invariants of the system, such as energy, momentum or the symplectic form, are called geometric integrators. Variational integrators are an important class of geometric integrators. The general idea…

Systems and Control · Electrical Eng. & Systems 2022-02-04 Leonardo Colombo , Manuela Gamonal Fernández , David Martín de Diego

Numerical models of weather and climate critically depend on long-term stability of integrators for systems of hyperbolic conservation laws. While such stability is often obtained from (physical or numerical) dissipation terms, physical…

Numerical Analysis · Mathematics 2021-12-01 Rüdiger Brecht , Werner Bauer , Alexander Bihlo , François Gay-Balmaz , Scott MacLachlan

We develop a method to learn physical systems from data that employs feedforward neural networks and whose predictions comply with the first and second principles of thermodynamics. The method employs a minimum amount of data by enforcing…

Machine Learning · Computer Science 2020-11-16 Quercus Hernández , Alberto Badias , David Gonzalez , Francisco Chinesta , Elias Cueto
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