In this work, we present approaches to rigorously certify A- and
A(α)-stability in Runge-Kutta methods through the solution of convex
feasibility problems defined by linear matrix inequalities. We adopt two
approaches. The first is based on sum-of-squares programming applied to the
Runge-Kutta E-polynomial and is applicable to both A- and
A(α)-stability. In the second, we sharpen the algebraic conditions for
A-stability of Cooper, Scherer, T{\"u}rke, and Wendler to incorporate the
Runge-Kutta order conditions. We demonstrate how the theoretical improvement
enables the practical use of these conditions for certification of
A-stability within a computational framework. We then use both approaches to
obtain rigorous certificates of stability for several diagonally implicit
schemes devised in the literature.Comment: 30 pages, 1 figur