# Optimal subsets in the stability regions of multistep methods

## TL;DR

This paper develops computational techniques to precisely analyze and optimize the stability regions of multistep numerical methods for differential equations, including exact calculations of stability angles and radii.

## Contribution

It introduces straightforward methods for exact stability region analysis and optimization within parametric families of multistep methods using algebraic and recursive techniques.

## Key findings

- Exact stability angles for BDF and second-derivative methods computed.
- Largest stability radius determined for BDF methods.
- Optimal methods identified within parametric families for stability angle and region.

## Abstract

In this work we study the stability regions of linear multistep or multiderivative multistep methods for initial-value problems by using techniques that are straightforward to implement in modern computer algebra systems. In many applications, one is interested in (i) checking whether a given subset of the complex plane (e.g. a sector, disk, or parabola) is included in the stability region of the numerical method, (ii) finding the largest subset of a certain shape contained in the stability region of a given method, or (iii) finding the numerical method in a parametric family of multistep methods whose stability region contains the largest subset of a given shape. First we describe a simple procedure to exactly calculate the stability angle $\alpha$ in the definition of $A(\alpha)$-stability. As an illustration, we consider two finite families of implicit multistep methods: we exactly compute the stability angles for the $k$-step BDF methods ($3\le k\le 6$) and for the $k$-step second-derivative multistep methods of Enright ($3\le k\le 7$). Next we determine the exact value of the stability radius in the BDF family for each $3\le k\le 6$, that is, the radius of the largest disk in the left half of the complex plane, symmetric with respect to the real axis, touching the imaginary axis and lying in the stability region of the corresponding method. Finally, we demonstrate how some Schur--Cohn-type theorems of recursive nature and not relying on the RLC method can be used to exactly solve some optimization problems within infinite parametric families of multistep methods. As an example, we choose a two-parameter family of implicit-explicit (IMEX) methods: we identify the unique method having the largest stability angle in the family, then we find the unique method in the same family whose stability region contains the largest parabola.