论文标题

适应原子群集扩展描述符的完整和独立的基础

Permutation-adapted complete and independent basis for atomic cluster expansion descriptors

论文作者

Goff, James M., Sievers, Charles, Wood, Mitchell A., Thompson, Aidan P.

论文摘要

原子聚类扩展(ACE)方法提供了一种系统的方法来描述粒子的本地环境。对于实际应用,通常要求将群集函数的基础相对于旋转和排列对称。现有方法产生过度完整的对称函数的集合。因此,这些方法需要一个额外的数值过程,例如单数值分解(SVD),以消除冗余功能。在这项工作中,显示出,可以使用广义Wigner符号的递归和置换属性得出集群函数子集的分析线性关系。从这些关系中,可以选择集群函数的子集(块),以便在每个块中保证函数是线性独立的。据推测,这一构成块独立的置换式旋转和排列不变(PA-RPI)函数构成了ACE的完整,独立的基础。除了ACE群集函数和其他理论参数的块线性依赖性的第一个分析证明外,还提供了数值结果来证明这一点。该方法的效用在诱使的ACE间潜力的发展中得到了证明。使用新的基础函数与贝叶斯压缩感应稀疏回归结合使用,观察到一些高级描述符可以持续存在并有助于实现高精度模型。

Atomic cluster expansion (ACE) methods provide a systematic way to describe particle local environments of arbitrary body order. For practical applications it is often required that the basis of cluster functions be symmetrized with respect to rotations and permutations. Existing methodologies yield sets of symmetrized functions that are over-complete. These methodologies thus require an additional numerical procedure, such as singular value decomposition (SVD), to eliminate redundant functions. In this work, it is shown that analytical linear relationships for subsets of cluster functions may be derived using recursion and permutation properties of generalized Wigner symbols. From these relationships, subsets (blocks) of cluster functions can be selected such that, within each block, functions are guaranteed to be linearly independent. It is conjectured that this block-wise independent set of permutation-adapted rotation and permutation invariant (PA-RPI) functions forms a complete, independent basis for ACE. Along with the first analytical proofs of block-wise linear dependence of ACE cluster functions and other theoretical arguments, numerical results are offered to demonstrate this. The utility of the method is demonstrated in the development of an ACE interatomic potential for tantalum. Using the new basis functions in combination with Bayesian compressive sensing sparse regression, some high degree descriptors are observed to persist and help achieve high-accuracy models.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源