Ab initio molecular simulations with numeric atom-centered orbitals

分子轨道 原子轨道 从头算 计算化学 Atom(片上系统) 局域分子轨道 斯莱特型轨道 物理 分子轨道理论 分子物理学 原子物理学 化学 计算机科学 量子力学 分子 电子 并行计算
作者
Volker Blüm,Ralf Gehrke,Felix Hanke,P. Havu,Ville Havu,Xinguo Ren,Karsten Reuter,Matthias Scheffler
出处
期刊:Computer Physics Communications [Elsevier BV]
卷期号:180 (11): 2175-2196 被引量:2647
标识
DOI:10.1016/j.cpc.2009.06.022
摘要

We describe a complete set of algorithms for ab initio molecular simulations based on numerically tabulated atom-centered orbitals (NAOs) to capture a wide range of molecular and materials properties from quantum-mechanical first principles. The full algorithmic framework described here is embodied in the Fritz Haber Institute “ab initio molecular simulations” (FHI-aims) computer program package. Its comprehensive description should be relevant to any other first-principles implementation based on NAOs. The focus here is on density-functional theory (DFT) in the local and semilocal (generalized gradient) approximations, but an extension to hybrid functionals, Hartree–Fock theory, and MP2/GW electron self-energies for total energies and excited states is possible within the same underlying algorithms. An all-electron/full-potential treatment that is both computationally efficient and accurate is achieved for periodic and cluster geometries on equal footing, including relaxation and ab initio molecular dynamics. We demonstrate the construction of transferable, hierarchical basis sets, allowing the calculation to range from qualitative tight-binding like accuracy to meV-level total energy convergence with the basis set. Since all basis functions are strictly localized, the otherwise computationally dominant grid-based operations scale as O(N) with system size N. Together with a scalar-relativistic treatment, the basis sets provide access to all elements from light to heavy. Both low-communication parallelization of all real-space grid based algorithms and a ScaLapack-based, customized handling of the linear algebra for all matrix operations are possible, guaranteeing efficient scaling (CPU time and memory) up to massively parallel computer systems with thousands of CPUs.
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