论文标题
大规模密度功能计算的时间依赖的随机状态方法
A Time-Dependent Random State Approach for Large-scale Density Functional Calculations
论文作者
论文摘要
我们基于密度功能理论开发一种自洽的第一原理方法。使用时间依赖性的随机方法而没有对角线化，可以获得诸如状态，费米能和电子密度之类的物理量。计算全球变量或本地变量的数值错误始终缩放为$ 1/\ sqrt {sn_ {e}} $，其中$ n_ {e} $是电子的数量，$ s $是随机状态的数量，导致带有系统大小的套期值计算成本。在大型系统的限制下，一个随机状态可能足以达到合理的准确性。该方法的准确性和缩放属性在分析和数值上得出在不同的冷凝物质系统中。我们时间依赖的随机状态方法为大规模密度功能计算提供了强大的策略。
We develop a self-consistent first-principle method based on the density functional theory. Physical quantities, such as the density of states, Fermi energy and electron density are obtained using a time-dependent random state method without diagonalization. The numerical error for calculating either global or local variables always scales as $1/\sqrt{SN_{e}}$, where $N_{e}$ is the number of electrons and $S$ is the number of random states, leading to a sublinear computational cost with the system size. In the limit of large systems, one random state could be enough to achieve reasonable accuracy. The method's accuracy and scaling properties are derived analytically and verified numerically in different condensed matter systems. Our time-dependent random state approach provides a powerful strategy for large-scale density functional calculations.
