论文标题

计算相位晶体模型的固定状态的有效数值方法

Efficient numerical methods for computing the stationary states of phase field crystal models

论文作者

Jiang, Kai, Si, Wei, Chang, Chen, Bao, Chenglong

论文摘要

在自由能函数的固定状态中找到相位场晶体(PFC)模型中的重要问题。许多努力都致力于设计具有耗能和质量保护特性的数值方案。但是,由于需要较小的有效步骤尺寸,大多数现有方法都是耗时的。在本文中,我们将能量功能离散化,并提出有效的数值算法来解决约束的非凸最小化问题。提出了一类基于梯度的方法,即所谓的自适应加速Bregman近端梯度(AA-BPG)方法,提出了,并且在没有全球Lipschitz恒定需求的情况下建立了收敛属性。一种实用的牛顿方法还旨在进一步加速局部收敛,并提供融合保证。我们的算法的一个关键特征是迭代过程中的能量耗散和质量保护特性。此外,我们开发了一个混合加速框架,以通过与实用的牛顿方法结合来​​加速AA-BPG方法和大多数现有方法。广泛的数值实验,包括Landau-Brazovskii(LB)模型中的两个三维周期晶体和Lifshitz-Petrich(LP)模型中的二维准晶体模型中的二维准晶体,这表明我们的方法表明,我们的方法具有适应性的步骤尺寸,从而在计算复杂结构时会导致许多现有方法的大量加速。

Finding the stationary states of a free energy functional is an important problem in phase field crystal (PFC) models. Many efforts have been devoted for designing numerical schemes with energy dissipation and mass conservation properties. However, most existing approaches are time-consuming due to the requirement of small effective step sizes. In this paper, we discretize the energy functional and propose efficient numerical algorithms for solving the constrained non-convex minimization problem. A class of gradient based approaches, which is the so-called adaptive accelerated Bregman proximal gradient (AA-BPG) methods, is proposed and the convergence property is established without the global Lipschitz constant requirements. A practical Newton method is also designed to further accelerate the local convergence with convergence guarantee. One key feature of our algorithms is that the energy dissipation and mass conservation properties hold during the iteration process. Moreover, we develop a hybrid acceleration framework to accelerate the AA-BPG methods and most of existing approaches through coupling with the practical Newton method. Extensive numerical experiments, including two three dimensional periodic crystals in Landau-Brazovskii (LB) model and a two dimensional quasicrystal in Lifshitz-Petrich (LP) model, demonstrate that our approaches have adaptive step sizes which lead to a significant acceleration over many existing methods when computing complex structures.

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