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Part of the book series: NATO Science Series ((ASIC,volume 536))

Abstract

The divide-and-conquer paradigm as well as other closely related principles of algorithmic design like recursion or hierarchy have turned out to be advantageous for a wide spectrum of numerical topics, especially in situations where adaptively refined grids have to be taken into account. Starting from a really classic example, Archimedes’ solution to the problem of integrating a parabola segment, we discuss the impact of such design patterns on numerical quadrature, interpolation, and the numerical solution of elliptic PDEs.

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References

  1. K. I. Babenko, Approximation by trigonometric polynomials in a certain class of periodic functions of several variables, Soviet Math. Dokl., 1 (1960), pp. 672–675. Russian original in Dokl. Akad. Nauk SSSR, 132 (1960), pp. 982-985.

    MathSciNet  MATH  Google Scholar 

  2. R. Balder and C. Zenger, The solution of multidimensional real Helmholtz equations on sparse grids, SIAM J. Sci. Comp., 17 (1996), pp. 631–646.

    Article  MathSciNet  MATH  Google Scholar 

  3. R. Becker and R. Rannacher, A feed-back approach to error control in finite element methods: basic analysis and examples, East-West J. Numer. Math., 4 (1996), pp. 237–264.

    MathSciNet  MATH  Google Scholar 

  4. T. Bonk, Ein rekursiver Algorithmus zur adaptiven numerischen Quadratur mehrdimensionaler Funktionen, Dissertation, Institut für Informatik, TU München, 1994.

    MATH  Google Scholar 

  5. —, A new algorithm for multi-dimensional adaptive numerical quadrature, in Adaptive Methods — Algorithms, Theory, and Applications, W. Hackbusch and G. Wittum, eds., vol. 46 of NNFM, Vieweg, Braunschweig/Wiesbaden, 1994, pp. 54–68.

    Google Scholar 

  6. H.-J. Bungartz, Finite Elements of Higher Order on Sparse Grids, Habilitationsschrift, Institut für Informatik, TU München, and Shaker Verlag, Aachen, 1998.

    Google Scholar 

  7. H.-J. Bungartz and T. Dornseifer, Sparse grids: Recent developments for elliptic partial differential equations. To appear in Multigrid Methods V, LNCSE, Springer, Berlin/Heidelberg, 1998. Also available as report TUM-I9702, Institut für Informatik, TU München, 1997.

    Google Scholar 

  8. H.-J. Bungartz and M. Griebel, A note on the complexity of solving Poisson’s equation for spaces of bounded mixed derivatives. To appear in J. Complexity, 1999.

    Google Scholar 

  9. T. Dornseifer, Diskretisierung allgemeiner elliptischer Differentialgleichungen in krummlinigen Koordinatensystemen auf dünnen Gittern, Dissertation, Institut für Informatik, TU München, 1997.

    Google Scholar 

  10. K. Eriksson, D. Estep, P. Hansbo, and C. Johnson, Adaptive Finite Elements, Springer, Berlin/Heidelberg, 1996.

    Google Scholar 

  11. T. Gerstner and M. Griebel, Numerical integration using sparse grids, Numerical Algorithms, 18 (1998), pp. 209–232.

    Article  MathSciNet  MATH  Google Scholar 

  12. A. R. Krommer and C. W. Ueberhuber, Numerical Integration on Advanced Computer Systems, vol. 848 of LNCS, Springer, Berlin/Heidelberg, 1994.

    Book  MATH  Google Scholar 

  13. S. Schneider and C. Zenger, Multigrid methods for hierarchical adaptive finite elements. Subm. to proc. GAMM-workshop on multigtid methods, Bonn, 1998.

    Google Scholar 

  14. S.A. Smolyak, Quadrature and interpolation formulas for tensor products of certain classes of functions, Soviet Math. Dokl., 4 (1963), pp. 240–243. Russian original in Dokl. Akad. Nauk SSSR, 148 (1963), pp. 1042-1045.

    Google Scholar 

  15. V. N. Temlyakov, Approximation of Functions with Bounded Mixed Derivative, vol. 178 of Proc. Steklov Inst. of Math., AMS, Providence, Rode Island, 1989.

    MATH  Google Scholar 

  16. C. Zenger, Sparse grids, in Parallel Algorithms for Partial Differential Equations, W. Hackbusch, ed., vol. 31 of NNFM, Vieweg, Braunschweig/Wiesbaden, 1991.

    Google Scholar 

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© 1999 Springer Science+Business Media Dordrecht

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Bungartz, HJ., Zenger, C. (1999). Error Control for Adaptive Sparse Grids. In: Bulgak, H., Zenger, C. (eds) Error Control and Adaptivity in Scientific Computing. NATO Science Series, vol 536. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-4647-0_7

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  • DOI: https://doi.org/10.1007/978-94-011-4647-0_7

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-0-7923-5809-1

  • Online ISBN: 978-94-011-4647-0

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