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Explicit symplectic algorithms based on generating functions for charged particle dynamics

机译:基于带电粒子动力学生成函数的显式辛算法

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摘要

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 accuracy and fidelity. For long-term simulations with high efficiency, explicit symplectic algorithms are desirable. However, it is generally believed that explicit symplectic algorithms are only available for sum-separable Hamiltonians, and this restriction limits the application of explicit symplectic algorithms to charged particle dynamics. To overcome this difficulty, we combine the familiar sum-split method and a generating function method to construct second- and third-order explicit symplectic algorithms for dynamics of charged particle. The generating function method is designed to generate explicit symplectic algorithms for product-separable Hamiltonian with form of H(x,p) = p(i) f (x) or H(x, p) = x(i) g(p). Applied to the simulations of charged particle dynamics, the explicit symplectic algorithms based on generating functions demonstrate superiorities in conservation and efficiency.
机译:典型坐标中带电粒子的动力学是哈密顿系统,并且众所周知的辛算法由于其长期的准确性和逼真度,被认为是哈密顿系统数值积分的事实上的方法。对于高效率的长期仿真,需要显式辛算法。然而,通常认为显式辛算法仅可用于和可分离的哈密顿量,并且该限制限制了显式辛算法在带电粒子动力学中的应用。为了克服这个困难,我们结合了熟悉的求和分解方法和生成函数方法来构造带电粒子动力学的二阶和三阶显式辛算法。设计生成函数方法以生成形式为H(x,p)= p(i)f(x)或H(x,p)= x(i)g(p)的乘积可分解哈密顿量的显式辛算法。应用于带电粒子动力学的仿真中,基于生成函数的显式辛算法显示了守恒和效率方面的优势。

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