Certification and the Potential Energy Landscape
For researchers using numerical optimization in potential energy landscapes, this method eliminates uncertainty about whether approximations correspond to true stationary points.
This work applies Smale's α-theory to certify that numerical approximations of stationary points on potential energy landscapes are actual solutions, providing a mathematical proof independent of computational precision.
Typically, there is no guarantee that a numerical approximation obtained using standard nonlinear equation solvers is indeed an actual solution, meaning that it lies in the quadratic convergence basin. Instead, it may lie only in the linear convergence basin, or even in a chaotic region, and hence not converge to the corresponding stationary point when further optimization is attempted. In some cases, these non-solutions could be misleading. Proving that a numerical approximation will quadratically converge to a stationary point is termed \textit{certification}. In this report, we provide details of how Smale's $α$-theory can be used to certify numerically obtained stationary points of a potential energy landscape, providing a \textit{mathematical proof} that the numerical approximation does indeed correspond to an actual stationary point, independent of the precision employed.