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Consistency Techniques in Ordinary Differential Equations

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Abstract

This paper takes a fresh look at the application of interval analysis to ordinary differential equations and studies how consistency techniques can help address the accuracy problems typically exhibited by these methods, while trying to preserve their efficiency. It proposes to generalize interval techniques into a two-step process: a forward process that computes an enclosure and a backward process that reduces this enclosure. Consistency techniques apply naturally to the backward (pruning) step but can also be applied to the forward phase. The paper describes the framework, studies the various steps in detail, proposes a number of novel techniques, and gives some preliminary experimental results to indicate the potential of this new research avenue.

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References

  1. Aberth, O. (1988). Precise Numerical Analysis. William Brown, Dubuque, IA.

    Google Scholar 

  2. Berz, M., Bischof, C., Corliss, G., & Griewank, A., eds. (1996). Computational Differentiation: Techniques, Applications, and Tools.Philadelphia, Penn.: SIAM.

    Google Scholar 

  3. Bohlender, G.(1996).Literature on enclosure methods and related topics. Technical Report, www.unikarlsruhe. de/ Gred.Bohlender, Institut für Angewandte Mathematik, Universität Karlsruhe.

  4. Corliss, G. (1995). Theory of Numerics in Ordinary and Partial Differential Equations, Light, W.A., Machetta, M. eds., Vol.IV, Chapt.Guaranteed Error Bounds for Ordinary Differential Equations, pages 1–75.Oxford University Press.

  5. Corliss, G.F.(1988).Applications of differentiation arithmetic.In Moore, R.E., ed., Reliability in Computing. pages 127–148, Academic Press, London.

    Google Scholar 

  6. Cruz, J., & Barahona, P.(1999).An Interval constraint approach to handle parametric ordinary differential equations for decision support. In Jaffar, J., ed., Principles and Practice of Constraint Programming (CP99).pages 478–479.

  7. Davey, D., & Stewart, N.(1976).Guaranteed error bounds for the initial value problem using polytope arithmetic. BIT 16: 257–268.

    Google Scholar 

  8. Deville, Y., Janssen, M., & Van Hentenryck, P. (1998). Consistency techniques in ordinary differential equations. In Maher, M., & Puget, J.-F. eds., Principles and Practice of Constraint Programming (CP98), LNCS 1520, pages 162–176.Springer-Verlag.

  9. Hartman, P. (1964). Ordinary Differential Equations. Wiley, New York.

    Google Scholar 

  10. Henrici, P. (1962). Discrete Variable Methods in Ordinary Differential Equations.John Wiley & Sons, New York.

    Google Scholar 

  11. Hickey, T.(1999).Analytic constraint solving and interval arithmetic.T echnical Report Cs-99-203, Michtom School of Computer Science, Brandeis University.

  12. Janssen, M., Deville, Y., & Van Hentenryck, P. (1999). Multistep filtering operators for ordinary differential equations. In Jaffar, J., ed., Principles and Practice of Constraint Programming (CP99).LNCS 1713, pages 246–260.Springer-Verlag.

  13. Lohner, R.J.(1987).Enclosing the solutions of ordinary initial and boundary value problems.In Kaucher, E.W., Kulisch, U.W., & Ullrich, C.eds., Computer Arithmetic: Scientific Computation and Programming Languages.pages 255–286. Wiley-Teubner Series in Computer Science, Stuttgart.

    Google Scholar 

  14. Moore, R. (1966). Interval Analysis.Prentice-Hall, Englewood Cliffs, NJ.

    Google Scholar 

  15. Moore, R. (1979). Methods and Applications of Interval Analysis.SIAM Publ.

  16. Nedialkov, N.S.(1999).Computing rigorous bounds on the solution of an initial value problem for an ordinary differential equation.Ph. D.thesis, University of Toronto.

  17. Rall, L.B.(1980).Applications of software for automatic differentiation in numerical computation.In Alefeld, G., & Grigorieff, R. D., eds., Fundamentals of Numerical Computation (Computer Oriented Numerical Analysis), Computing Supplement No.2.pages 141–156. Springer-Verlag, Berlin.

    Google Scholar 

  18. Rall, L.B.(1981). Automatic Differentiation: Techniques and Applications, LNCS 120, Springer-Verlag.

  19. Rihm, R.(1999).Implicit methods for enclosing solutions of ODEs. Journal of Universal Computer Science 4(2): 202–209.

    Google Scholar 

  20. Stauning, O.(1996).Enclosing solutions of ordinary differential equations.T echnical Report IMM-REP-1996-18, Technical University of Denmark.

  21. Stewart, N.(1971).A heuristic to reduce the wrapping effect in the numerical solution of ODE. BIT 11: 328–337.

    Google Scholar 

  22. Van Hentenryck, P.(1998a).A constraint satisfaction approach to a circuit design problem. Journal of Global Optimization, 13: 75–93.

    Google Scholar 

  23. Van Hentenryck, P.(1998b).A gentle introduction to numerica. Artificial Intelligence 103(1–2): 209–235.

    Google Scholar 

  24. Van Hentenryck, P., Laurent, M., & Deville, Y. (1997). Numerica, A ModelingLang uage for Global Optimization.MIT Press.

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Deville, Y., Janssen, M. & Van Hentenryck, P. Consistency Techniques in Ordinary Differential Equations. Constraints 7, 289–315 (2002). https://doi.org/10.1023/A:1020573518783

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