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A Newton method for best uniform rational approximation

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Abstract

We present a novel algorithm, inspired by the recent BRASIL algorithm, for best uniform rational approximation of real continuous functions on real intervals based on a formulation of the problem as a nonlinear system of equations and barycentric interpolation. We derive a closed form for the Jacobian of the system of equations and formulate a Newton’s method for its solution. The resulting method for best uniform rational approximation can handle singularities and arbitrary degrees for numerator and denominator. We give some numerical experiments which indicate that it typically converges globally and exhibits superlinear convergence in a neighborhood of the solution. A software implementation of the algorithm is provided. Interesting auxiliary results include formulae for the derivatives of barycentric rational interpolants with respect to the interpolation nodes, and for the derivative of the nullspace of a full-rank matrix.

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Algorithm 1
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Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

Notes

  1. https://github.com/c-f-h/baryrat

  2. https://pypi.org/project/gmpy2/

References

  1. Absil, P.-A., Mahony, R., Sepulchre, R.: Riemannian geometry of Grassmann manifolds with a view on algorithmic computation. Acta Appl. Math. 80(2), 199–220 (2004). https://doi.org/10.1023/b:acap.0000013855.14971.91https://doi.org/10.1023/b:acap.0000013855.14971.91

    Article  MathSciNet  MATH  Google Scholar 

  2. Achieser, N.I.: Theory of approximation. dover books on advanced mathematics. Dover Publications. ISBN 9780486671291 (1992)

  3. Berrut, J.-P., Mittelmann, H.D.: Matrices for the direct determination of the barycentric weights of rational interpolation. J Comput. Appl. Math 78 (2), 355–370 (1997). https://doi.org/10.1016/s0377-0427(96)00163-x

    Article  MathSciNet  MATH  Google Scholar 

  4. Berrut, J.-P., Trefethen, L.N.: Barycentric Lagrange interpolation. SIAM Rev. 46 (3), 501–517 (2004). https://doi.org/10.1137/s0036144502417715

    Article  MathSciNet  MATH  Google Scholar 

  5. Berrut, J.-P., Baltensperger, R., Mittelmann, H.D.: Recent developments in barycentric rational interpolation. In: Trends and applications in constructive approximation, pp. 27–51. Birkhäuser Basel. https://doi.org/10.1007/3-7643-7356-3_3 (2005)

  6. Braess, D.: Nonlinear approximation theory. Springer Berlin Heidelberg. ISBN 978-3-642-64883-0. https://doi.org/10.1007/978-3-642-61609-9 (1986)

  7. Carpenter, A.J., Ruttan, A., Varga, R.S: Extended numerical computations on the 1/9 conjecture in rational approximation theory. In: Rational approximation and interpolation, pp. 383–411. Springer Berlin Heidelberg. https://doi.org/10.1007/bfb0072427 (1984)

  8. Danczul, T., Hofreither, C.: On rational Krylov and reduced basis methods for fractional diffusion. Journal of Numerical Mathematics. https://doi.org/10.1515/jnma-2021-0032 (2021)

  9. Danczul, T., Hofreither, C., Schöberl, J.: A unified rational Krylov method for elliptic and parabolic fractional diffusion problems. Technical Report arXiv:2103.13068. https://arxiv.org/abs/2103.13068 (2021)

  10. Demmel, J., Gu, M., Eisenstat, S., Slapničar, I., Veselić, K., Drmač, Z.: Computing the singular value decomposition with high relative accuracy. Linear Algebra. Appl 299(1–3), 21–80 (1999). https://doi.org/10.1016/s0024-3795(99)00134-2

    Article  MathSciNet  MATH  Google Scholar 

  11. Driscoll, T.A., Hale, N., Trefethen, L.N.: Chebfun Guide. Pafnuty Publications. http://www.chebfun.org/docs/guide/ (2014)

  12. Edelman, A., Arias, T.A., Smith, S.T.: The geometry of algorithms with orthogonality constraints. SIAM J. Matrix Anal. Appl. 20(2), 303–353 (1998). https://doi.org/10.1137/s0895479895290954

    Article  MathSciNet  MATH  Google Scholar 

  13. Filip, S.-I., Nakatsukasa, Y., Trefethen, L.N., Beckermann, B.: Rational minimax approximation via adaptive barycentric representations. SIAM J. Sci. Comput 40(4), A2427–A2455 (2018). https://doi.org/10.1137/17m1132409

    Article  MathSciNet  MATH  Google Scholar 

  14. Georgieva, I., Hofreither, C.: A newton’s method for best uniform polynomial approximation. Technical Report 2021-46, RICAM. https://www.ricam.oeaw.ac.at/files/reports/21/rep21-46.pdf (2021)

  15. Giles, M.: An extended collection of matrix derivative results for forward and reverse mode automatic differentiation. Technical report, University of Oxford. https://ora.ox.ac.uk/objects/uuid:8d0c0a29-c92b-4153-a1d2-38b276e93124 (2008)

  16. Güttel, S.: Rational Krylov approximation of matrix functions: Numerical methods and optimal pole selection. GAMM-Mitteilungen 36(1), 8–31 (2013). https://doi.org/10.1002/gamm.201310002

    Article  MathSciNet  MATH  Google Scholar 

  17. Harizanov, S., Lazarov, R., Margenov, S., Marinov, P., Vutov, Y.: Optimal solvers for linear systems with fractional powers of sparse SPD matrices. Numerical Linear Algebra with Applications 25 (5), e2167 (2018). https://doi.org/10.1002/nla.2167

    Article  MathSciNet  MATH  Google Scholar 

  18. Harizanov, S., Lazarov, R., Margenov, S., Marinov, P.: The best uniform rational approximation: applications to solving equations involving fractional powers of elliptic operators. Number 9 in Lectures Notes in Computer Science and Technologies of the IICT-BAS. Institute of Information and Communication Technologies at the Bulgarian Academy of Sciences. https://pa.iict.bas.bg/lcst/2019/09-2019-HLMM.pdf(2019)

  19. Harizanov, S., Lazarov, R., Margenov, S., Marinov, P., Pasciak, J.: Analysis of numerical methods for spectral fractional elliptic equations based on the best uniform rational approximation. Chin J. Comput. Phys 408, 109285 (2020). https://doi.org/10.1016/j.jcp.2020.109285

    Article  MathSciNet  MATH  Google Scholar 

  20. Higham, N.J.: QR factorization with complete pivoting and accurate computation of the SVD. Linear Algebra. Appl. 309 (1–3), 153–174 (2000). https://doi.org/10.1016/s0024-3795(99)00230-x

    Article  MathSciNet  MATH  Google Scholar 

  21. Higham, N.J.: The numerical stability of barycentric Lagrange interpolation. IMA J. Numer. Anal 24(4), 547–556 (2004). https://doi.org/10.1093/imanum/24.4.547

    Article  MathSciNet  MATH  Google Scholar 

  22. Hofreither, C.: A unified view of some numerical methods for fractional diffusion. Comput. Math. Appl 80(2), 332–350 (2020). https://doi.org/10.1016/j.camwa.2019.07.025

    Article  MathSciNet  MATH  Google Scholar 

  23. Hofreither, C.: An algorithm for best rational approximation based on barycentric rational interpolation. Numerical Algorithms. https://doi.org/10.1007/s11075-020-01042-0 (2021)

  24. Ionită, A.C.: Lagrange Rational Interpolation and its Applications to Approximation of Large-Scale Dynamical Systems. PhD Thesis, Rice University, Houston (2013)

    Google Scholar 

  25. Knockaert, L.: A simple and accurate algorithm for barycentric rational interpolation. IEEE Signal Process. Lett. 15, 154–157 (2008). https://doi.org/10.1109/lsp.2007.913583

    Article  Google Scholar 

  26. Nakatsukasa, Y., Sète, O., Trefethen, L.N.: The AAA algorithm for rational approximation. SIAM J. Sci. Comput 40(3), A1494–A1522 (2018). https://doi.org/10.1137/16m1106122

    Article  MathSciNet  MATH  Google Scholar 

  27. Schneider, C., Werner, W.: Some new aspects of rational interpolation. Math. Comput. 47(175), 285–285 (1986). https://doi.org/10.1090/s0025-5718-1986-0842136-8

    Article  MathSciNet  MATH  Google Scholar 

  28. Trefethen, L.N.: Approximation Theory and Approximation Practice. Other Titles in Applied Mathematics. SIAM. ISBN 9781611972405 (2013)

  29. Varga, R.S., Carpenter A.J.: Some numerical results on best uniform rational approximation of xα on [0, 1]. Numerical Algorithms 2(2), 171–185 (1992). https://doi.org/10.1007/bf02145384

    Article  MathSciNet  Google Scholar 

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Funding

This work was supported by the bilateral project KP-06-Austria/8/2019 (WTZ BG 03/2019), funded by Bulgarian National Science Fund and OeAD (Austria). The second author received support from the Austrian Science Fund (FWF) grant P 33956-NBL.

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Correspondence to Clemens Hofreither.

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Georgieva, I., Hofreither, C. A Newton method for best uniform rational approximation. Numer Algor 93, 1741–1758 (2023). https://doi.org/10.1007/s11075-022-01487-5

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