We propose a novel algorithm based on inexact GMRES methods for linear response calculations in density functional theory. Such calculations require iteratively solving a nested linear problem $\mathcal{E} \delta\rho = b$ to obtain the variation of the electron density $\delta \rho$. Notably each application of the dielectric operator $\mathcal{E}$ in turn requires the iterative solution of multiple linear systems, the Sternheimer equations. We develop computable bounds to estimate the accuracy of the density variation given the tolerances to which the Sternheimer equations have been solved. Based on this result we suggest reliable strategies for adaptively selecting the convergence tolerances of the Sternheimer equations, such that each application of $\mathcal{E}$ is no more accurate than needed. Experiments on challenging materials systems of practical relevance demonstrate our strategies to achieve superlinear convergence as well as a reduction of computational time by about 40% while preserving the accuracy of the returned response solution. Our algorithm seamlessly combines with standard preconditioning approaches known from the context of self-consistent field problems making it a promising framework for efficient response solvers based on Krylov subspace techniques.
翻译:我们提出了一种基于非精确GMRES方法的新算法,用于密度泛函理论中的线性响应计算。此类计算需要迭代求解嵌套线性问题 $\mathcal{E} \delta\rho = b$ 以获得电子密度变化 $\delta \rho$。值得注意的是,介电算子 $\mathcal{E}$ 的每次应用又需要迭代求解多个线性系统,即Sternheimer方程。我们建立了可计算的界来估计密度变化的精度,该估计基于Sternheimer方程的求解容差。基于这一结果,我们提出了可靠的自适应策略来选择Sternheimer方程的收敛容差,使得 $\mathcal{E}$ 的每次应用精度恰好满足需求。在具有实际意义的挑战性材料体系上的实验表明,我们的策略实现了超线性收敛,并在保持返回响应解精度的同时,将计算时间减少了约40%。该算法与自洽场问题中已知的标准预处理方法无缝结合,使其成为基于Krylov子空间技术的高效响应求解器的有前景框架。