Center for Computing Research, Sandia National Laboratories, Albuquerque, New Mexico 87185, USA.
J Chem Phys. 2018 Jun 28;148(24):241721. doi: 10.1063/1.5017641.
The Spectral Neighbor Analysis Potential (SNAP) is a classical interatomic potential that expresses the energy of each atom as a linear function of selected bispectrum components of the neighbor atoms. An extension of the SNAP form is proposed that includes quadratic terms in the bispectrum components. The extension is shown to provide a large increase in accuracy relative to the linear form, while incurring only a modest increase in computational cost. The mathematical structure of the quadratic SNAP form is similar to the embedded atom method (EAM), with the SNAP bispectrum components serving as counterparts to the two-body density functions in EAM. The effectiveness of the new form is demonstrated using an extensive set of training data for tantalum structures. Similar to artificial neural network potentials, the quadratic SNAP form requires substantially more training data in order to prevent overfitting. The quality of this new potential form is measured through a robust cross-validation analysis.
谱邻居分析势（SNAP）是一种经典的原子间势，它将每个原子的能量表示为所选邻居原子的双谱分量的线性函数。本文提出了 SNAP 形式的扩展，其中包括双谱分量的二次项。扩展表明，与线性形式相比，它可以大大提高准确性，而计算成本仅略有增加。二次 SNAP 形式的数学结构类似于嵌入原子方法（EAM），其中 SNAP 双谱分量作为 EAM 中两体密度函数的对应物。通过大量的钽结构训练数据证明了新形式的有效性。与人工神经网络势类似，二次 SNAP 形式需要更多的训练数据，以防止过拟合。通过稳健的交叉验证分析来衡量这种新的势形式的质量。
