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We describe a technique for constructing a symplectic transfer map for a charged particle moving through an accelerator component with arbitrary three-dimensional static magnetic field. The transfer map is constructed by symplectic…

Accelerator Physics · Physics 2012-06-29 Andy Wolski , Jonathan Gratus , Robin W. Tucker

We study the non-canonical symplectic structure, or K-symplectic structure inherited by the charged particle dynamics. Based on the splitting technique, we construct non-canonical symplectic methods which is explicit and stable for the…

Computational Physics · Physics 2015-09-28 Yang He , Yajuan Sun , Zhaoqi Zhou , Jian Liu , Hong Qin

Modified Hamiltonians are used in the field of geometric numerical integration to show that symplectic schemes for Hamiltonian systems are accurate over long times. For nonlinear systems the series defining the modified Hamiltonian usually…

Numerical Analysis · Mathematics 2018-11-14 Shami A Alsallami , Jitse Niesen , Frank W Nijhoff

We present a symplectic electromagnetic fully-kinetic particle-in-cell simulation of microinstabilities in plasma, using parameters from the Cyclone Base Case [Dimits, et al., Physics of Plasmas 7, 969 (2000)]. The results show that the…

Plasma Physics · Physics 2025-04-01 Jianyuan Xiao , Jian liu

Since variational symplectic integrators for the guiding center was proposed [1,2], structure-preserving geometric algorithms have become an active research field in plasma physics. We found that the slow manifolds of the classical Pauli…

Plasma Physics · Physics 2021-05-19 Jianyuan Xiao , Hong Qin

Symplectic integration of autonomous Hamiltonian systems is a well-known field of study in geometric numerical integration, but for non-autonomous systems the situation is less clear, since symplectic structure requires an even number of…

Numerical Analysis · Mathematics 2014-09-18 Håkon Marthinsen , Brynjulf Owren

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

Particle-based simulations of the Vlasov equation typically require a large number of particles, which leads to a high-dimensional system of ordinary differential equations. Solving such systems is computationally very expensive, especially…

Computational Physics · Physics 2023-07-19 Tomasz M. Tyranowski , Michael Kraus

A new geometric procedure to construct symplectic methods for constrained mechanical systems is developed in this paper. The definition of a map coming from the notion of retraction maps allows to adapt the continuous problem to the…

Numerical Analysis · Mathematics 2024-12-10 María Barbero Liñán , David Martín de Diego , Rodrigo T. Sato Martín de Almagro

A recently proposed method for computer simulations in the isothermal-isobaric (NPT) ensemble, based on Langevin-type equations of motion for the particle coordinates and the ``piston'' degree of freedom, is re-derived by straightforward…

Soft Condensed Matter · Physics 2016-08-31 A. Kolb , B. Duenweg

This article considers Hamiltonian mechanical systems with potential functions admitting jump discontinuities. The focus is on accurate and efficient numerical approximations of their solutions, which will be defined via the laws of…

Numerical Analysis · Mathematics 2022-01-05 Molei Tao , Shi Jin

We propose a variational symplectic numerical method for the time integration of dynamical systems issued from the least action principle. We assume a quadratic internal interpolation of the state and we approximate the action in a small…

Numerical Analysis · Mathematics 2024-06-25 François Dubois , Juan Antonio Rojas-Quintero

Many important physical systems can be described as the evolution of a Hamiltonian system, which has the important property of being conservative, that is, energy is conserved throughout the evolution. Physics Informed Neural Networks and…

Machine Learning · Computer Science 2025-12-10 Harsh Choudhary , Chandan Gupta , Vyacheslav Kungurtsev , Melvin Leok , Georgios Korpas

Symplectic maps can provide a straightforward and accurate way to visualize and quantify the dynamics of conservative systems with two degrees of freedom. These maps can be easily iterated from the simplest computers to obtain trajectories…

Chaotic Dynamics · Physics 2023-01-18 Felipe G. Souza , Gabriel C. Grime , Iberê L. Caldas

Particle-in-Cell (PIC) simulation is the most important numerical tool in plasma physics. However, its long-term accuracy has not been established. To overcome this difficulty, we developed a canonical symplectic PIC method for the…

The AMAS group at the Paul Scherrer Institute developed an object oriented library for high performance simulation of high intensity ion beam transport with space charge. Such particle-in-cell (PIC) simulations require a method to generate…

Data Analysis, Statistics and Probability · Physics 2012-05-17 Christian Baumgarten

The usual explicit finite-difference method of solving partial differential equations is limited in stability because it approximates the exact amplification factor by power-series. By adapting the same exponential-splitting method of…

Numerical Analysis · Mathematics 2012-06-11 Siu A. Chin

Recent development of structure-preserving geometric particle-in-cell (PIC) algorithms for Vlasov-Maxwell systems is summarized. With the arriving of 100 petaflop and exaflop computing power, it is now possible to carry out direct…

Plasma Physics · Physics 2019-06-26 Jianyuan Xiao , Hong Qin , Jian Liu

Simulation of many-particle system evolution by molecular dynamics takes to decrease integration step to provide numerical scheme stability on the sufficiently large time interval. It leads to a significant increase of the volume of…

Numerical Analysis · Mathematics 2016-05-19 Eduard G. Nikonov

The growing amount of data produced by simulations and observations of space physics processes encourages the use of methods rooted in Machine Learning for data analysis and physical discovery. We apply a clustering method based on…

Plasma Physics · Physics 2023-04-27 Sophia Köhne , Elisabetta Boella , Maria Elena Innocenti