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In this work we propose a new, arbitrary order space-time finite element discretisation for Hamiltonian PDEs in multisymplectic formulation. We show that the new method which is obtained by using both continuous and discontinuous…

Numerical Analysis · Mathematics 2021-08-18 Elena Celledoni , James Jackaman

In this manuscript, we propose efficient stochastic semi-explicit symplectic schemes tailored for nonseparable stochastic Hamiltonian systems (SHSs). These semi-explicit symplectic schemes are constructed by introducing augmented…

Numerical Analysis · Mathematics 2024-05-24 Jialin Hong , Baohui Hou , Liying Sun

We present the symplectic algorithm in the Lagrangian formalism for the Hamiltonian systems by virtue of the noncommutative differential calculus with respect to the discrete time and the Euler--Lagrange cohomological concepts. We also show…

Computational Physics · Physics 2007-05-23 H. Y. Guo , Y. Q. Li , K. Wu

A simple pseudo-Hamiltonian formulation is proposed for the linear inhomogeneous systems of ODEs. In contrast to the usual Hamiltonian mechanics, our approach is based on the use of non-stationary Poisson brackets, i.e. corresponding…

Quantum Physics · Physics 2009-11-11 V. G. Kupriyanov , S. L. Lyakhovich , A. A. Sharapov

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

We provide several examples of dissipative systems that can be obtained from conservative ones through a simple, quadratic,change of time. A typical example is the curve-shortening flow in R^d, which is a particular case ofmean-curvature…

Analysis of PDEs · Mathematics 2017-09-13 Yann Brenier , Xianglong Duan

We propose explicit symplectic integrators of molecular dynamics (MD) algorithms for rigid-body molecules in the canonical and isothermal-isobaric ensembles. We also present a symplectic algorithm in the constant normal pressure and lateral…

Statistical Mechanics · Physics 2007-05-23 Hisashi Okumura , Satoru G. Itoh , Yuko Okamoto

Singular theories, characterised by the presence of degeneracies in their Lagrangian or Hamiltonian descriptions, require the systematic implementation of constraints in order to obtain well-defined dynamics. While the symplectic framework…

Mathematical Physics · Physics 2026-05-01 Callum Bell , David Sloan

In this article we numerically revisit the long-time solution behavior of the Camassa-Holm equation. The finite difference solution of this integrable equation is sought subject to the newly derived initial condition with Delta-function…

Numerical Analysis · Mathematics 2014-12-04 Chueh-Hsin Chang , Ching-Hao Yu , Tony Wen-Hann Sheu

In this work we propose a method to perform optimization on manifolds. We assume to have an objective function $f$ defined on a manifold and think of it as the potential energy of a mechanical system. By adding a momentum-dependent kinetic…

Numerical Analysis · Mathematics 2023-08-30 Marta Ghirardelli

This work presents two novel approaches for the symplectic model reduction of high-dimensional Hamiltonian systems using data-driven quadratic manifolds. Classical symplectic model reduction approaches employ linear symplectic subspaces for…

Numerical Analysis · Mathematics 2023-08-25 Harsh Sharma , Hongliang Mu , Patrick Buchfink , Rudy Geelen , Silke Glas , Boris Kramer

In this paper, we propose a distributed model predictive control (DMPC) scheme for linear time-invariant constrained systems which admit a separable structure. To exploit the merits of distributed computation algorithms, the stabilizing…

Optimization and Control · Mathematics 2018-03-22 Georgios Darivianakis , Annika Eichler , John Lygeros

We investigate dissipation-driven topological phase transitions in one-dimensional quantum open systems governed by the Lindblad equation with linear dissipation operators, which ensure the density matrix retains its Gaussian form…

Quantum Physics · Physics 2026-01-27 Tian-Shu Deng , Fan Yang

This paper introduces a robust reformulation of the incompressible Navier-Stokes equations, establishing a foundational framework for designing efficient, structure-preserving algorithms that strictly conserve the original energy…

Numerical Analysis · Mathematics 2025-08-12 Zihan Weng , Qi Hong , Chunwu Wang , Yuezheng Gong

So far, many control algorithms have been developed for singularly perturbed systems. However, in many industrial processes, enforcing closed-loop fast-slow dynamics for peculiarly non-separable ones is a prior request and a crucial issue…

Systems and Control · Electrical Eng. & Systems 2024-10-30 Xinglong Zhang , Wei Jiang , Shuyou Yu , Xin Xu , Zhizhong Li

The finite-difference time-domain (FDTD) algorithm is a popular numerical method for solving electromagnetic problems. FDTD simulations can suffer from instability due to the explicit nature of the method. Stability enforcement can be…

Computational Engineering, Finance, and Science · Computer Science 2018-12-26 Fadime Bekmambetova , Xinyue Zhang , Piero Triverio

In this paper we present a general framework that allows one to study discretization of certain dynamical systems. This generalizes earlier work on discretization of Lagrangian and Hamiltonian systems on tangent bundles and cotangent…

Dynamical Systems · Mathematics 2007-05-23 Vincent M. Guibout , Anthony M. Bloch

Port-Hamiltonian systems provide an energy-based modeling paradigm for dynamical input-state-output systems. At their core, they fulfill an energy balance relating stored, dissipated and supplied energy. To accurately resolve this energy…

Numerical Analysis · Mathematics 2024-12-17 Andreas Bartel , Manuel Schaller

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

This paper introduces a novel distributed optimization technique for networked systems, which removes the dependency on specific parameter choices, notably the learning rate. Traditional parameter selection strategies in distributed…

Optimization and Control · Mathematics 2024-04-23 Rodrigo Aldana-López , Alessandro Macchelli , Giuseppe Notarstefano , Rosario Aragüés , Carlos Sagüés