Papers for

computational molecular engineers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Device based quantum chemistry handles conical intersections with analytic gradients

Analytic Gradients and Nonadiabatic Couplings for Device-Resident DMRG-QD-NEVPT2 Through Conical Intersections on a Consumer GPU

Abstract: Nonadiabatic dynamics through a conical intersection needs both static and dynamic correlation and, at every geometry, an excited-state gradient and interstate nonadiabatic coupling (NACME); analytic multireference derivatives at this level have been cluster-scale. We report device-resident \mbox{DMRG-QD-NEVPT2} with analytic derivatives, on B2PLYP double-hybrid Kohn--Sham orbitals: a density-matrix-renormalization-group reference supplies the static correlation, and quasi-degenerate NEVPT2 adds the dynamic correlation through a multi-state effective Hamiltonian that stays valid \emph{through} the intersection, where single-state perturbation theory fails. Each gradient and NACME is one reverse-mode transpose of a contraction graph that carries the DMRG sweep as a gauge-free, tape-free node and reduces to active-space RDM contractions with Cholesky factors. The whole construction runs on a consumer 8\,GB GPU. The DMRG reference is FCI-in-active-space to $10^{-15}$ and the single-precision leg is spectroscopically inert ($<10^{-6}$\,eV); the correction yields smooth adiabats and a non-vanishing, $1/ΔE$-divergent NACME through the twisted-ethene intersection---where adiabatic linear-response TDDFT returns zero---and restores the dynamic correlation the ionic $ππ^*$ states require. DMRG-NEVPT2 and quasi-degenerate NEVPT2 are each established; the contribution is the entire stack---multi-state through a conical intersection, with analytic gradients and couplings---made device-resident on commodity hardware. Multireference companion to our density-functional realization of the same engine.

Wed 9 SeptHardware Architecture
The gist
Understanding how molecules behave when they change shape very fast, especially at points called conical intersections, requires complex calculations that combine different types of electron interactions. The authors present a new method that performs these calculations efficiently on common graphics cards (GPUs), making the process more accessible and faster than before. Their approach keeps track of subtle changes in energy and interactions precisely, even where simpler methods fail. This helps scientists better simulate important molecular processes like how light energy moves in molecules.
Open → 2609.09990v1