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Symplectic Numerical Schemes for Stochastic Systems Preserving Hamiltonian Functions

机译:保留哈密顿函数的随机系统的辛数值格式

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We present high-order symplectic schemes for stochastic Hamiltonian systems preserving Hamiltonian functions. The approach is based on the generating function method, and we show that for the stochastic Hamiltonian systems, the coefficients of the generating function are invariant under permutations. As a consequence, the high-order symplectic schemes have a simpler form than the explicit Taylor expansion schemes with the same order. Moreover, we demonstrate numerically that the symplectic schemes are effective for long time simulations.
机译:我们提出了保留汉密尔顿函数的随机汉密尔顿系统的高阶辛格式。该方法基于生成函数方法,并且证明了对于随机哈密顿系统,在置换条件下,生成函数的系数是不变的。结果,高阶辛格方案具有比具有相同阶次的显式泰勒展开方案更简单的形式。此外,我们通过数值证明了辛方案对于长时间的仿真是有效的。

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