Vol. 14, No. 1, 2019

Download this article
Download this article For screen
For printing
Recent Issues
Volume 18, Issue 1
Volume 17, Issue 1
Volume 16, Issue 2
Volume 16, Issue 1
Volume 15, Issue 2
Volume 15, Issue 1
Volume 14, Issue 2
Volume 14, Issue 1
Volume 13, Issue 2
Volume 13, Issue 1
Volume 12, Issue 1
Volume 11, Issue 2
Volume 11, Issue 1
Volume 10, Issue 2
Volume 10, Issue 1
Volume 9, Issue 2
Volume 9, Issue 1
Volume 8, Issue 1
Volume 7, Issue 2
Volume 7, Issue 1
Volume 6, Issue 1
Volume 5, Issue 2
Volume 5, Issue 1
Volume 4, Issue 1
Volume 3, Issue 1
Volume 2, Issue 1
Volume 1, Issue 1
The Journal
About the Journal
Editorial Board
Submission Guidelines
Submission Form
Policies for Authors
Ethics Statement
ISSN: 2157-5452 (e-only)
ISSN: 1559-3940 (print)
Author Index
To Appear
Other MSP Journals
This article is available for purchase or by subscription. See below.
On the convergence of spectral deferred correction methods

Mathew F. Causley and David C. Seal

Vol. 14 (2019), No. 1, 33–64

In this work we analyze the convergence properties of the spectral deferred correction (SDC) method originally proposed by Dutt et al. (BIT 40 (2000), no. 2, 241–266). The framework for this high-order ordinary differential equation (ODE) solver is typically described as a low-order approximation (such as forward or backward Euler) lifted to higher-order accuracy by applying the same low-order method to an error equation and then adding in the resulting defect to correct the solution. Our focus is not on solving the error equation to increase the order of accuracy, but on rewriting the solver as an iterative Picard integral equation solver. In doing so, our chief finding is that it is not the low-order solver that picks up the order of accuracy with each correction, but it is the underlying quadrature rule of the right-hand-side function that is solely responsible for picking up additional orders of accuracy. Our proofs point to a total of three sources of errors that SDC methods carry: the error at the current time point, the error from the previous iterate, and the numerical integration error that comes from the total number of quadrature nodes used for integration. The second of these two sources of errors is what separates SDC methods from Picard integral equation methods; our findings indicate that as long as the difference between the current and previous iterates always gets multiplied by at least a constant multiple of the time step size, then high-order accuracy can be found even if the underlying ODE “solver” is inconsistent. From this vantage, we solidify the prospects of extending spectral deferred correction methods to a larger class of solvers, of which we present some examples.

PDF Access Denied

We have not been able to recognize your IP address as that of a subscriber to this journal.
Online access to the content of recent issues is by subscription, or purchase of single articles.

Please contact your institution's librarian suggesting a subscription, for example by using our journal-recom­mendation form. Or, visit our subscription page for instructions on purchasing a subscription.

You may also contact us at contact@msp.org
or by using our contact form.

Or, you may purchase this single article for USD 40.00:

initial-value problems, spectral deferred correction, Picard integral, semi-implicit methods
Mathematical Subject Classification 2010
Primary: 65L05, 65L20
Received: 19 June 2017
Revised: 7 November 2018
Accepted: 2 December 2018
Published: 9 February 2019
Mathew F. Causley
Mathematics Department
Kettering University
Flint, MI
United States
David C. Seal
Department of Mathematics
United States Naval Academy
Annapolis, MD
United States