Iterative Implementation of the Dipole Interaction Model for Atomic Polarizabilities

IF 4.8 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Raphael F. Ligorio, Leonardo H. R. Dos Santos, Anna Krawczuk
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引用次数: 0

Abstract

Despite its name, the dipole interaction model (DIM) serves not only to adjust dipole moments due to atomic interactions but also to assess polarizabilities. Traditionally, polarizability calculations via DIM rely on matrix inversion, posing constraints on memory usage and computational time. Recent implementations have shown significant performance boosts by employing an iterative inversion solver, albeit reducing accuracy. In this paper, we present a direct approach for computing polarizabilities via iterative cycles, eliminating the need for matrix inversion. This allows for scaling up the model to hundreds of thousands of atoms without sacrificing precision, as often happens when simplifying the standard inversion procedure to reduce computational costs. Additionally, we have addressed memory issues associated with storing extensive arrays in standard implementations. Our advancement holds promise for diverse applications, providing an efficient method for exploring polarizabilities in various systems.

Abstract Image

原子极化率的偶极相互作用模型的迭代实现
尽管它的名字,偶极相互作用模型(DIM)不仅用于调整由于原子相互作用引起的偶极矩,而且还用于评估极化率。传统上,通过DIM计算极化率依赖于矩阵反演,这对内存使用和计算时间造成了限制。最近的实现通过使用迭代反演求解器显示出显著的性能提升,尽管降低了精度。在本文中,我们提出了一种通过迭代循环计算极化率的直接方法,消除了对矩阵反演的需要。这允许在不牺牲精度的情况下将模型扩展到数十万个原子,这通常发生在简化标准反演过程以减少计算成本时。此外,我们还解决了在标准实现中与存储扩展数组相关的内存问题。我们的进展为各种应用提供了希望,为探索各种系统的极化性提供了有效的方法。
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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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