Skip to main content
Log in

Computational complexity of one-step methods for a scalar autonomous differential equation

Rechnerische Komplexität von Ein-Schritt-Verfahren für eine skalare autonome Differentialgleichung

  • Published:
Computing Aims and scope Submit manuscript

Abstract

The problem is to calculate an approximate solution of an initial value problem for a scalar autonomous differential equation. A generalized notion of a nonlinear Runge-Kutta (NRK) method is defined. We show that the order of anys-stage NRK method cannot exceed 2s−1; hence, the family of NRK methods due to Brent has the maximal order possible. Using this result, we derive complexity bounds on the problem of finding an approximate solution with error not exceeding ε. We also compute the order which minimizes these bounds, and show that this optimal order increases as ε decreases, tending to infinity as ε tends to zero.

Zusammenfassung

Es wird das Problem behandelt, die Näherungslösung für ein Anfangswertproblem für eine skalare autonome Differentialgleichung abzuschätzen. Eine Verallgemeinerung eines nichtlinearen Runge-Kutta-(NRK-) Verfahrens wird definiert. Es wird gezeigt, daß die Ordnung irgendeiners-wertigen NRK-Methode nicht größer als 2s−1 sein kann; deshalb hat die Familie der NRK-Verfahren von Brent die maximale mögliche Ordnung. Unter Benutzung dieser Resultate werden Schranken angegeben zum Problem des Auffindens von Näherungslösungen, deren Fehler nicht größer als ε ist. Es wird ebenfalls die Ordnung berechnet, welche die Schranken minimiert, und es wird gezeigt, daß die optimale Ordnung wächst, falls ε abnimmt; sie geht nach unendlich, wenn ε gegen Null geht.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Abramowitz and Stegun [64]: Abramowitz, M., Stegun, I. A.: Handbook of mathematical functions with formulas, graphs and mathematical tables. Washington, D. C.: National Bureau of Standards 1964.

    Google Scholar 

  • Ahlfors [66]: Ahlfors, L. V.: Complex analysis, 2nd ed. New York: McGraw-Hill 1966.

    Google Scholar 

  • Borodin and Munro [75]: Borodin, A., Munro, I.: The computational complexity of algebraic and numeric problems. New York: American Elsevier 1975.

    Google Scholar 

  • Brent [74]: Brent, R. P.: Efficient methods for finding zeros of functions whose derivatives are easy to evaluate. Report, Computer Science Department, Carnegie-Mellon University 1974.

  • Brent [76]: Brent, R. P.: A class of optimal-order zero finding methods using derivative evaluations, in: Analytic computational complexity (Traub, J. F., ed.). New York: Academic Press 1976.

    Google Scholar 

  • Buck [65]: Buck, R. C.: Advanced calculus, 2nd ed. New York: McGraw-Hill 1965.

    Google Scholar 

  • Henrici [62]: Henrici, P.: Discrete variable methods in ordinary differential equations. New York: Wiley 1962.

    Google Scholar 

  • Meersman [76]: Meersman, R.: On maximal order of families of iterations for nonlinear equations. Doctoral Thesis, Vrije Universiteit Brussel, Brussels 1976.

    Google Scholar 

  • Stetter [73]: Stetter, H. J.: Analysis of discretization methods for ordinary differential equations. Berlin-Heidelberg-New York: Springer 1972.

    Google Scholar 

  • Szegö [59]: Szegö, G.: Orthogonal polynomials. Amer. Math. Soc. Colloquium Publications, Vol. 23. New York: Amer. Math. Soc. 1959.

    Google Scholar 

  • Traub [64]: Traub, J. F.: Iterative methods for the solution of equations. Englewood Cliffs, N. J.: Prentice-Hall 1964.

    Google Scholar 

  • Traub and Woźniakowski [76]: Traub, J. F., Woźniakowski, H.: Strict lower and upper bounds on iterative complexity, in: Analytic computational complexity (Traub, J. F., ed.), New York: Academic Press 1976.

    Google Scholar 

  • Werschulz [76a]: Werschulz, A. G.: Computational complexity of one-step methods for systems of differential equations. Report, Computer Science Department, Carnegie-Mellon University 1976. (To appear in Mathematics of Computation.)

  • Werschulz [76b]: Werschulz, A. G.: Optimal order and minimal complexity of one-step methods for initial value problems. Report, Computer Science Department, Carnegie-Mellon University 1976.

Download references

Author information

Authors and Affiliations

Authors

Additional information

This research was supported in part by the National Science Foundation under Grant MCS75-222-55 and the Office of Naval Research under Contract N00014-76-C-0370 NR 044-422

Rights and permissions

Reprints and permissions

About this article

Cite this article

Werschulz, A.G. Computational complexity of one-step methods for a scalar autonomous differential equation. Computing 23, 345–355 (1979). https://doi.org/10.1007/BF02254863

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02254863

Keywords

Navigation