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arXiv 2102.02524math.NAcs.NAmath-phmath.MPmath.OC
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指数积分器的有效自适应步长控制

Efficient adaptive step size control for exponential integrators

Pranab Jyoti Deka, Lukas Einkemmer

摘要:

传统的步长控制器默认时间步长的代价与步长无关。这对于使用直接求解器的显式和隐式积分器是合理的。然而,在指数积分器的上下文中,通常采用迭代方法,例如Krylov方法或多项式插值来计算所需矩阵函数的作用。在这种情况下,不变成本的假设是不成立的。这对于高阶指数积分器来说尤其是个问题,高阶指数积分器能够基于精度考虑采取相对较大的时间步长。在本文中,我们考虑一个自适应步长控制器的指数Rosenbrock方法,确定步长的前提下,最小化计算成本。由精度考虑给出的最大允许步长仅作为约束。我们测试这种方法的范围内的非线性偏微分方程。我们的研究结果表明显着的改进(高达4倍的计算成本减少)在传统的步长控制器的公差范围很广。

英文摘要:

Traditional step size controllers make the tacit assumption that the cost of a time step is independent of the step size. This is reasonable for explicit and implicit integrators that use direct solvers. In the context of exponential integrators, however, an iterative approach, such as Krylov methods or polynomial interpolation, to compute the action of the required matrix functions is usually employed. In this case, the assumption of constant cost is not valid. This is, in particular, a problem for higher-order exponential integrators, which are able to take relatively large time steps based on accuracy considerations. In this paper, we consider an adaptive step size controller for exponential Rosenbrock methods that determines the step size based on the premise of minimizing computational cost. The largest allowed step size, given by accuracy considerations, merely acts as a constraint. We test this approach on a range of nonlinear partial differential equations. Our results show significant improvements (up to a factor of 4 reduction in the computational cost) over the traditional step size controller for a wide range of tolerances.

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。

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