Rectifying drifts of symplectic algorithm
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摘要: 辛算法较RK(Runge-Kutta)方法,保持辛结构不变或保持哈密顿系统规律性不变是突出的优点,但点态数值精度并不理想.推导出了三阶、四阶辛算法的漂移量计算公式,通过补偿漂移量就能提高点态数值精度,既保辛结构又保证点态数值高精度,适合于工程应用.建立了分数步对称辛算法(即FSJS算法)的纠漂公式,制定了漂移的约束标准.相关算例的数值结果表明:三阶FSJS算法漂移量最小,点态数值精度更高.
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关键词:
- 辛算法 /
- Runge-Kutta法 /
- 相位漂移 /
- 哈密顿函数
Abstract: Symplectic algorithm preserves the symplectic structure and laws for Hamiltonian systems compared with Runge-Kutta(RK) methods, but the point-wise numerical precision is worse for elliptic Hamiltonian systems. In order to improve it, the average statistic drift formulae of the third-order symplectic method and the fourth-order scheme were deduced. The precision was improved through compensating the drifts and step segmentation. A standard was built to find a better symplectic scheme in phase drift. The results of examples show that the third-order fractional step and symmetric symplectic algorithm(FSJS3 algorithm) is higher than the fourth-order one in phase accuracy, which is recommended for engineering application.-
Key words:
- symplectic /
- Runge-Kutta methods /
- phase shift /
- Hamiltonian functions
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