在从头算理论中嵌入参数以开发基于分子相似性的近似
Embedding parameters in ab initio theory to develop approximations based on molecular similarity
摘要：
探讨了一种利用分子相似性降低电子结构理论计算成本的方法，即将参数嵌入低成本的低水平（LL）从头算模型中，并调整参数使其与高水平（HL）从头算模型的结果一致.参数化LL（pLL）模型通过将哈密顿算子的选定矩阵元素乘以取决于元素类型的缩放因子来创建。各种方案应用的比例因子进行了比较，以及影响的比例因子的线性函数的变量相关的键长，原子电荷，和键级。该模型在乙烷和乙烯上进行训练，用-NH 2，-OH和-F取代，并在取代的丙烷，丙烯和叔丁烷上进行测试。训练和测试数据集是通过扭曲分子几何形状和施加均匀的电场来创建的。拟合的性质包括由几何畸变或外加场引起的总能量的变化，以及前线轨道能量。包括额外的训练数据，如分解的能量由运营商或相互作用的电子密度与外部电荷的影响，也进行了探讨。性能最佳的模型形式将训练数据中HL和LL能量预测之间的均方根（RMS）差异减少了85%以上，将测试数据中的均方根（RMS）差异减少了75%以上。这种方法有可能提供一种灵活和系统改进的手段，利用量子化学中的分子相似性。
英文摘要：
A means to take advantage of molecular similarity to lower the computational cost of electronic structure theory is explored, in which parameters are embedded into a low-cost, low-level (LL) ab initio model and adjusted to obtain agreement with results from a higher-level (HL) ab initio model. A parametrized LL (pLL) model is created by multiplying selected matrix elements of the Hamiltonian operators by scaling factors that depend on element types. Various schemes for applying the scaling factors are compared, along with the impact of making the scaling factors linear functions of variables related to bond lengths, atomic charges, and bond orders. The models are trained on ethane and ethylene, substituted with -NH2, -OH and -F, and tested on substituted propane, propylene and t-butane. Training and test datasets are created by distorting the molecular geometries and applying uniform electric fields. The fitted properties include changes in total energy arising from geometric distortions or applied fields, and frontier orbital energies. The impacts of including additional training data, such as decomposition of the energy by operator or interaction of the electron density with external charges, are also explored. The best-performing model forms reduce the root mean square (RMS) difference between the HL and LL energy predictions by over 85% on the training data and over 75% on the test data. The argument is made that this approach has the potential to provide a flexible and systematically-improvable means to take advantage of molecular similarity in quantum chemistry.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
