并行算法应用于具有守恒量的随机微分方程
Parareal algorithms applied to stochastic differential equations with conserved quantities
AI总结：
本文将并行算法与轨迹投影方法结合，用于保持微分方程的守恒量。通过粗细传播器和修正步骤中的投影方法，进行数值实验以展示迭代收敛性和守恒量的保持性。
摘要：
在本文中，我们结合并行算法与轨迹在特定流形上的投影方法，该流形由微分方程的某些守恒量的保持定义。首先，投影方法被介绍为粗细传播器。其次，我们还将投影方法应用于具有守恒量的系统，在原始并行算法的修正步骤中使用。最后，通过不同类型的算法进行三种数值实验，以展示迭代中的收敛性和模型系统的守恒量保持性。
英文摘要：
In this papers, we couple the parareal algorithm with projection methods of the trajectory on a specific manifold, defined by the preservation of some conserved quantities of the differential equations. First, projection methods are introduced as the coarse and fine propagators. Second, we also apply the projection methods for systems with conserved quantities in the correction step of original parareal algorithm. Finally, three numerical experiments are performed by different kinds of algorithms to show the property of convergence in iteration, and preservation in conserved quantities of model systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
