Zhang Xing, Li Chenghan, Ye Hong-Zhou, Berkelbach Timothy C, Chan Garnet Kin-Lic
Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA.
Department of Chemistry, Columbia University, New York, New York 10027, USA.
J Chem Phys. 2024 Jul 7;161(1). doi: 10.1063/5.0212274.
In this work, we introduce a differentiable implementation of the local natural orbital coupled cluster (LNO-CC) method within the automatic differentiation framework of the PySCFAD package. The implementation is comprehensively tuned for enhanced performance, which enables the calculation of first-order static response properties on medium-sized molecular systems using coupled cluster theory with single, double, and perturbative triple excitations [CCSD(T)]. We evaluate the accuracy of our method by benchmarking it against the canonical CCSD(T) reference for nuclear gradients, dipole moments, and geometry optimizations. In addition, we demonstrate the possibility of property calculations for chemically interesting systems through the computation of bond orders and Mössbauer spectroscopy parameters for a [NiFe]-hydrogenase active site model, along with the simulation of infrared spectra via ab initio LNO-CC molecular dynamics for a protonated water hexamer.
在这项工作中，我们在PySCFAD软件包的自动微分框架内引入了局部自然轨道耦合簇（LNO-CC）方法的可微实现。该实现针对性能提升进行了全面优化，能够使用含单、双和微扰三激发的耦合簇理论[CCSD(T)]，对中等规模分子体系计算一阶静态响应性质。我们通过将我们的方法与用于核梯度、偶极矩和几何优化的标准CCSD(T)参考进行基准测试，来评估我们方法的准确性。此外，我们通过计算[NiFe]-氢化酶活性位点模型的键级和穆斯堡尔光谱参数，以及通过质子化水六聚体的从头算LNO-CC分子动力学模拟红外光谱，展示了对具有化学意义的体系进行性质计算的可能性。
