Guest Speaker – Physical (CHEM 781) – February 22, 2023

Bio
Samuel Slattery graduated from UNC Chapel Hill in 2016 with a double major in chemistry and mathematics. After a brief time in industry, he returned to chemistry working in the research group of Professor Yosuke Kanai. He is currently pursuing his PhD in chemistry at Virginia Tech under the supervision of Professor Edward Valeev. His research interests include exploration of density functional approximations and development of improved self-consistent field solvers. He is a contributor to the Massively Parallel Quantum Chemistry (MPQC) package.

Abstract
An efficient quasi-Newton orbital solver optimized to reduce the number of gradient (Fock matrix) evaluations is presented. The solver optimizes orthogonal orbitals by sequences of unitary rotations generated by the (preconditioned) limited-memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) algorithm incorporating trust-region step restriction. Low-rank structure of the inverse (approximate) Hessian is exploited not only in L-BFGS but also when solving the trust-region problem. The efficiency of the proposed method is compared to that of standard DIIS-accelerated eigensolver (Roothaan-Hall), and other exact and approximate Newton solvers for mean-field (Hartree-Fock and Kohn-Sham) problems.