缩放比例
安萨茨
线性比例尺
计算机科学
统计物理学
边界(拓扑)
线性系统
算法
计算科学
数学
物理
量子力学
几何学
数学分析
大地测量学
地理
作者
Stephan Mohr,Laura E. Ratcliff,Luigi Genovese,Damien Caliste,P Boulanger,Stefan Goedecker,Thierry Deutsch
摘要
Density functional theory calculations are computationally extremely expensive for systems containing many atoms due to their intrinsic cubic scaling. This fact has led to the development of so-called linear scaling algorithms during the last few decades. In this way it becomes possible to perform ab initio calculations for several tens of thousands of atoms within reasonable walltimes. However, even though the use of linear scaling algorithms is physically well justified, their implementation often introduces some small errors. Consequently most implementations offering such a linear complexity either yield only a limited accuracy or, if one wants to go beyond this restriction, require a tedious fine tuning of many parameters. In our linear scaling approach within the BigDFT package, we were able to overcome this restriction. Using an ansatz based on localized support functions expressed in an underlying Daubechies wavelet basis - which offers ideal properties for accurate linear scaling calculations - we obtain an amazingly high accuracy and a universal applicability while still keeping the possibility of simulating large system with linear scaling walltimes requiring only a moderate demand of computing resources. We prove the effectiveness of our method on a wide variety of systems with different boundary conditions, for single-point calculations as well as for geometry optimizations and molecular dynamics.
科研通智能强力驱动
Strongly Powered by AbleSci AI