Gabbie’s paper on analytic nuclear energy gradients in multicomponent CCSD has been published in JCTC! Of course, analytic gradients and multicomponent methods are Kurt’s two favorite niche parts of quantum chemistry, so he is especially happy to see this paper published. Rotational constants computed with multicomponent CCSD are competitive with VPT2-CCSD accuracy wise, but with no need to compute any higher-order derivatives.
This paper is also noteworthy as it is our group’s first time using AI to help write code. We are still a little cautious about using AI, but an analytic gradient presented itself as a good first choice as we could check the final results numerically. We are now firm believers that because of AI, the field of electronic structure theory is going to fundamentally change in the next two years.

