Multidimensional derivative-free optimization. A case study on minimization of Hartree-Fock-Roothaan energy functionals
A. Bagci

TL;DR
This paper evaluates derivative-free optimization algorithms for minimizing Hartree-Fock-Roothaan energy functionals with noninteger Slater-type orbitals, demonstrating their effectiveness on challenging atomic energy minimization problems.
Contribution
It provides the first systematic comparison of derivative-free methods applied to Hartree-Fock energy minimization with non-integer orbitals.
Findings
Powell's method performs well on test functions.
Algorithms successfully minimize complex atomic energy functionals.
Non-convex optimization landscape challenges are addressed.
Abstract
This study presents an evaluation of derivative-free optimization algorithms for the direct minimization of Hartree-Fock-Roothaan energy functionals involving nonlinear orbital parameters and quantum numbers with noninteger order. The analysis focuses on atomic calculations employing noninteger Slater-type orbitals. Analytic derivatives of the energy functional are not readily available for these orbitals. Four methods are investigated under identical numerical conditions: Powell's conjugate-direction method, the Nelder-Mead simplex algorithm, coordinate-based pattern search, and a model-based algorithm utilizing radial basis functions for surrogate-model construction. Performance benchmarking is first performed using the Powell singular function, a well-established test case exhibiting challenging properties including Hessian singularity at the global minimum. The algorithms are then…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Chemical Physics Studies · Machine Learning in Materials Science · Cold Atom Physics and Bose-Einstein Condensates
