Performant automatic differentiation of local coupled cluster theories: Response properties and <i>ab&nbsp;initio</i> molecular dynamics

<p>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&nbsp;initio LNO-CC molecular dynamics for a protonated water hexamer.</p>. Authors: Zhang, Xing (ORCID:0000000218921380); Li, Chenghan (ORCID:0000000160959318); Ye, Hong-Zhou (ORCID:0000000237142753); Berkelbach, Timothy (ORCID:0000000274452136); Chan, Garnet (ORCID:0000000180096038). DOE Contract: 89233218CNA000001. Subjects: Chemistry; Physics