# Linear Multistep Methods (LMMs) and A-stability

## Contents

## Introduction

Note: Since all multistep methods considered in the course are linear, the course notes speak of 'multistep methods' instead of 'linear multistep methods'. Hopefully this should cause no confusion.

This GUI aims to demonstrate and contrast:

- the root condition for LMMs
- A-stability for more general methods including LMMs.

We consider a general LMM of the form

(where and )

## Theory

The role of the **root condition** for LMMs is covered in the course notes in `5.3.2 The convergence of multistep methods`.

*Quick review:* we consider the roots of the polynomial with coefficients : the **root condition** is obeyed if these lie within the closed unit disc and all roots on the boundary are simple. By the **Dahlquist Equivalence Theorem**, a method of order is convergent iff satisfies the root condition.

The role of **A-stability** is covered in the course notes in `"6.2 Linear stability"`.

*Quick review:* it is desirable for the numerical solution produced by a method to tend to zero if the exact solution does. It turns out that for linear problems it is enough to consider the solution of the simple scalar equation with fixed step-size . Whether the numerical solution tends to zero will be a function of . The region where this does occur is called the **linear stability domain**. If the linear stability domain contains all complex numbers with negative real part, then we say that the method in question is **A-stable**.

We restrict our attention to the linear stability domain of LMMs and a certain class of one-step methods.

For LMMs the linear stability domain has a boundary that can be written in a simple fashion in terms of the coefficient polynomials of the method ( and ).

For many one-step methods, we will typically be able to write

where is the numerical solution of with fixed step-size . In this case the function tells us everything we need to know about the linear stability domain: as iff .

*More details about how the plotting is done can be found in [1] - Section 7.6 starting on page 262*

## The GUI

stability_gui

**The Plot**

The plot displays the linear stability domain of a method (shaded in blue with black boundary). A black dashed line marks the imaginary axis.

For LMMs the unit circle is also plotted (dashed magenta curve), and the roots of the polynomial are plotted as empty red points. The root condition may then be inspected by eye (but beware of repeated roots).

**Controls**

To switch between the LMM and one-step modes, use the radio buttons in the bottom centre of the GUI. The maximum range covered by the plot can also be set using the controls just below. The 'resolution' control determines how many points are used to produce the plot - increase this if the curves are jagged and decrease it if plotting takes an excessive amount of time.

**Specifying methods**

LMMs are entered by specifying their coefficients ( and ) as row vectors.

One-step methods are entered by specifying .

In either case, there are preset methods that can be selected using the drop-down box above the entry fields.

## LMM Presets

- BDF1 to BDF 6 are the BDF methods of orders 1 through 6 (see notes
`5.3.5 BDF methods`). - AB1 to AB5 are the Adams-Bashforth methods of orders 1 through 5 (see notes
`5.3.4 Adams Methods`). - AM0 to AM4 are the Adams-Moulton methods of orders 1 through 5 (see notes
`5.3.4 Adams Methods`).

## One-step Presets

- RK2E is an explicit two-stage Runge-Kutta method (order two). All explicit RK methods of a given order have the same .
- RK2I is the two-stage implicit Runge-Kutta method (order three) described in
`Stiffness and Runge-Kutta`in`6.3 Overcoming the Dahlquist barrier` - GL2 is the two-stage implicit Gauss-Legendre method (order four) described in the example in
`6.3 Overcoming the Dahlquist barrier`

## Code

- stability_gui.m (Run this)
- stability_gui.fig (Required)

All files as .zip archive: a_stability_all.zip

## References

**[1]** Finite Difference Methods for Ordinary and Partial Differential Equations: Steady-State and Time-Dependent Problems by Randall J. LeVeque [SIAM, Philadelphia, 2007]