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arXiv 2108.01909math.NAcs.NA
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随机Allen--Cahn方程自适应时间步进格式的强收敛性

Strong convergence of adaptive time-stepping schemes for the stochastic Allen--Cahn equation

Chuchu Chen, Tonghe Dang, Jialin Hong

AI总结:

针对随机Allen--Cahn方程标准显式Euler格式可能发散的问题,提出自适应时间步进格式,通过调整步长控制稳定性,证明了时间阶β/2、空间阶β/d的强收敛性,且计算成本更低。

摘要:

已知在文献[beccari]中,具有均匀时间步长的标准显式Euler型格式(如指数Euler和线性隐式Euler格式)虽然计算效率高,但对于随机Allen--Cahn方程可能发散。为克服发散问题,本文提出并分析了自适应时间步进格式,该格式在每次迭代时调整时间步长以控制数值解的不稳定性。在自适应时间步长函数适当有界的条件下,建立了数值解在$\mathcal{C}(\mathcal{O})$范数和$\dot{H}^β(\mathcal{O})$范数中的先验估计,这在收敛性分析中起关键作用。我们证明了自适应时间步进格式在时间上以阶$\frac{β}{2}$、在空间上以阶$\frac{β}{d}$强收敛,其中$d$($d=1,2,3$)为维度,$β\in(0,2]$。数值实验表明,自适应时间步进格式实现简单,且计算成本低于均匀时间步长格式。

英文摘要:

It is known in \cite{beccari} that the standard explicit Euler-type scheme (such as the exponential Euler and the linear-implicit Euler schemes) with a uniform timestep, though computationally efficient, may diverge for the stochastic Allen--Cahn equation. To overcome the divergence, this paper proposes and analyzes adaptive time-stepping schemes, which adapt the timestep at each iteration to control numerical solutions from instability. The \textit{a priori} estimates in $\mathcal {C}(\mathcal {O})$-norm and $\dot{H}^β(\mathcal{O})$-norm of numerical solutions are established provided the adaptive timestep function is suitably bounded, which plays a key role in the convergence analysis. We show that the adaptive time-stepping schemes converge strongly with order $\fracβ{2}$ in time and $\fracβ{d}$ in space with $d$ ($d=1,2,3$) being the dimension and $β\in(0,2]$. Numerical experiments show that the adaptive time-stepping schemes are simple to implement and at a lower computational cost than a scheme with the uniform timestep.

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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