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We implement several symplectic integrators, which are based on two part splitting, for studying the chaotic behavior of one- and two-dimensional disordered Klein-Gordon lattices with many degrees of freedom and investigate their numerical…

Computational Physics · Physics 2018-11-14 B. Senyange , Ch. Skokos

We propose new algorithms for numerical integration of the equations of motion for classical spin systems with fixed spatial site positions. The algorithms are derived on the basis of a mid-point scheme in conjunction with the multiple time…

Statistical Mechanics · Physics 2009-10-31 I. P. Omelyan , I. M. Mryglod , R. Folk

Hamilton's equations are fundamental for modeling complex physical systems, where preserving key properties such as energy and momentum is crucial for reliable long-term simulations. Geometric integrators are widely used for this purpose,…

Machine Learning · Computer Science 2026-03-17 Priscilla Canizares , Davide Murari , Carola-Bibiane Schönlieb , Ferdia Sherry , Zakhar Shumaylov

We present and compare different numerical schemes for the integration of the variational equations of autonomous Hamiltonian systems whose kinetic energy is quadratic in the generalized momenta and whose potential is a function of the…

Chaotic Dynamics · Physics 2015-03-17 Ch. Skokos , E. Gerlach

Furthering our understanding of many of today's interesting problems in plasma physics---including plasma based acceleration and magnetic reconnection with pair production due to quantum electrodynamic effects---requires large-scale kinetic…

Computational Physics · Physics 2020-10-28 Kyle G. Miller , Roman P. Lee , Adam Tableman , Anton Helm , Ricardo A. Fonseca , Viktor K. Decyk , Warren B. Mori

We investigate the use of extended phase-space symplectic integration for simulating two different classes of electron dynamics. The first one, with one and a half degrees of freedom, comes from plasma physics and describes the classical…

Computational Physics · Physics 2026-04-08 Francois Mauger , Cristel Chandre

Hamilton's equations of motion form a fundamental framework in various branches of physics, including astronomy, quantum mechanics, particle physics, and climate science. Classical numerical solvers are typically employed to compute the…

Machine Learning · Computer Science 2024-10-25 Priscilla Canizares , Davide Murari , Carola-Bibiane Schönlieb , Ferdia Sherry , Zakhar Shumaylov

We adapted the SWAP molecular dynamics algorithm for use in lattice Ising spin models. We dressed the spins with a randomly distributed length and we alternated long-range spin exchanges with conventional single spin flip Monte Carlo…

Statistical Mechanics · Physics 2025-10-14 Greivin Alfaro Miranda , Leticia F. Cugliandolo , Marco Tarzia

Long-term stability studies of nonlinear Hamiltonian systems require symplectic integration algorithms which are both fast and accurate. In this paper, we study a symplectic integration method wherein the symplectic map representing the…

Computational Physics · Physics 2007-05-23 Govindan Rangarajan

The high-performance scalable parallel algorithm for rigorous calculation of partition function of lattice systems with finite number Ising spins was developed. The parallel calculations run by C++ code with using of Message Passing…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-02-21 Alexey A. Peretyatko , Ivan A. Bogatyrev , Vitaliy Yu. Kapitan , Yury V. Kirienko , Konstantin V. Nefedev , Valery I. Belokon

Dynamics of a charged particle in the canonical coordinates is a Hamiltonian system, and the well-known symplectic algorithm has been regarded as the de facto method for numerical integration of Hamiltonian systems due to its long-term…

Plasma Physics · Physics 2016-07-27 Ruili Zhang , Hong Qin , Yifa Tang , Jian Liu , Yang He , Jianyuan Xiao

A parallelized quantum dynamics package using the Smolyak algorithm for general molecular simulation is introduced in this work. The program has no limitation of the Hamiltonian form and provides high flexibility on the simulation setup to…

Computational Physics · Physics 2021-12-06 Ahai Chen , André Nauts , David Lauvergnat

This article describes algorithms for the hybrid parallelization and SIMD vectorization of molecular dynamics simulations with short-range forces. The parallelization method combines domain decomposition with a thread-based parallelization…

Materials Science · Physics 2017-09-13 Chris M. Mangiardi , Ralf Meyer

We present a mathematical framework for constructing and analyzing parallel algorithms for lattice Kinetic Monte Carlo (KMC) simulations. The resulting algorithms have the capacity to simulate a wide range of spatio-temporal scales in…

Numerical Analysis · Mathematics 2015-05-28 Giorgos Arampatzis , Markos A. Katsoulakis , Petr Plechac , Michela Taufer , Lifan Xu

Symplectic integrators with long-term preservation of integrals of motion are introduced for the guiding-center model of plasma particles in toroidal magnetic fields of general topology. An efficient transformation to canonical coordinates…

Symplectic integration methods based on operator splitting are well established in many branches of science. For Hamiltonian systems which split in more than two parts, symplectic methods of higher order have been studied in detail only for…

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

In this article we introduce a novel coupled algorithm for massively parallel direct numerical simulations of electrophoresis in microfluidic flows. This multiphysics algorithm employs an Eulerian description of fluid and ions, combined…

Computational Engineering, Finance, and Science · Computer Science 2018-05-29 Dominik Bartuschat , Ulrich Rüde

Magnetic materials play a key role in the contemporary industry, providing unique features with a wide application potential. To study physical phenomena and design new materials, it is important to possess an appropriate tool, a model…

Materials Science · Physics 2026-01-13 Jakub Šebesta , Dominik Legut

This paper proposes a parallelizable algorithm for linear-quadratic model predictive control (MPC) problems with state and input constraints. The algorithm itself is based on a parallel MPC scheme that has originally been designed for…

Optimization and Control · Mathematics 2022-07-04 Jiahe Shi , Yuning Jiang , Juraj Oravec , Boris Houska