Enhancing structure relaxations for first-principles codes: an approximate Hessian approach

Abstract

We present a method for improving the speed of geometry relaxation by using a harmonic approximation for the interaction potential between nearest neighbor atoms to construct an initial Hessian estimate. The model is quite robust, and yields approximately a 30% or better reduction in the number of calculations compared to an optimized diagonal initialization. Convergence with this initializer approaches the speed of a converged BFGS Hessian, therefore it is close to the best that can be achieved. Hessian preconditioning is discussed, and it is found that a compromise between an average condition number and a narrow distribution in eigenvalues produces the best optimization.

9 pages, 3 figures, added references, expanded optimization section

References in corpus (2)

• Model Hessian for accelerating first-principles structure optimizations
• Linear scaling relaxation of the atomic positions in nano structures

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