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Multiple orthogonal polynomials applied to matrix function evaluation

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Abstract

Multiple orthogonal polynomials generalize standard orthogonal polynomials by requiring orthogonality with respect to several inner products. This paper discusses an application to the approximation of matrix functions and presents quadrature rules that generalize the anti-Gauss rules proposed by Laurie.

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References

  1. Aliaga, J.I., Boley, D.L., Freund, R.W., Hernández, V.: A Lanczos-type method for multiple starting vectors. Math. Comput. 69, 1577–1601 (1999)

    Article  MathSciNet  Google Scholar 

  2. Bai, Z., Day, D., Ye, Q.: ABLE: an adaptive block Lanczos method for non-Hermitian eigenvalue problems. SIAM J. Matrix Anal. Appl. 20, 1060–1082 (1999)

    Article  MathSciNet  Google Scholar 

  3. Borges, C.F.: On a class of Gauss-like quadrature rules. Numer. Math. 67, 271–288 (1994)

    Article  MathSciNet  Google Scholar 

  4. Calvetti, D., Reichel, L., Sgallari, F.: Application of anti-Gauss quadrature rules in linear algebra. In: Gautschi, W., Golub, G.H., Opfer, G. (eds.) Applications and Computation of Orthogonal Polynomials, pp. 41–56. Birkhäuser, Basel (1999)

    Chapter  Google Scholar 

  5. Coussement, J., Van Assche, W.: Gaussian quadrature for multiple orthogonal polynomials. J. Comput. Appl. Math. 178, 131–145 (2005)

    Article  MathSciNet  Google Scholar 

  6. Daems, E., Kuijlaars, A.B.J.: Multiple orthogonal polynomials of mixed type and non-intersecting Brownian motions. J. Approx Theory 146, 91–114 (2007)

    Article  MathSciNet  Google Scholar 

  7. Fenu, C., Martin, D., Reichel, L., Rodriguez, G.: Block Gauss and anti-Gauss quadrature with application to networks. SIAM J. Matrix Anal. Appl. 34, 1655–1684 (2013)

    Article  MathSciNet  Google Scholar 

  8. Fidalgo Prieto, U., Illán, J., López Lagomasino, G.: Hermite-Padé approximation and simultaneous quadrature formulas. J. Approx. Theory 126, 171–197 (2004)

    Article  MathSciNet  Google Scholar 

  9. Fidalgo Prieto, U., López Lagomasino, G.: Rate of convergence of generalized Hermite–Padé approximants of Nikishin systems. Constr. Approx. 23, 165–196 (2006)

    Article  MathSciNet  Google Scholar 

  10. Fidalgo Prieto, U., López Lagomasino, G.: Nikishin systems are perfect. Constr. Approx. 34, 297–356 (2011)

    Article  MathSciNet  Google Scholar 

  11. Fidalgo, U., Medina Peralta, S., Minguez Ceniceros, J.: Mixed type multiple orthogonal polynomials: perfectness and interlacing properties of zeros. Linear Algebra Appl. 438, 1229–1239 (2013)

    Article  MathSciNet  Google Scholar 

  12. Freund, R.W.: Band Lanczos methods. In: Bai, Z., Demmel, J., Dongarra, J., Ruhe, A., van der Vorst, H. (eds.) Templets for the Solution of Algebraic Eigenvalue Problems. SIAM, Philadelphia (2000). (Sections 3.6 and 5.7)

    Google Scholar 

  13. Freund, R.W.: Model reduction methods based on Krylov subspaces. Acta Numer. 12, 267–319 (2003)

    Article  MathSciNet  Google Scholar 

  14. Gautschi, W.: Orthogonal Polynomials: Computation and Approximation. Oxford University Press, Oxford (2004)

    MATH  Google Scholar 

  15. Golub, G.H., Meurant, G.: Matrices, Moments and Quadrature with Applications. Princeton University Press, Princeton (2010)

    MATH  Google Scholar 

  16. Higham, N.J.: Stability analysis of algorithms for solving confluent Vandermonde-like systems. SIAM J. Matrix Anal. Appl. 11, 23–41 (1990)

    Article  MathSciNet  Google Scholar 

  17. Higham, N.J.: Functions of Matrices: Theory and Computation. SIAM, Philadelphia (2008)

    Book  Google Scholar 

  18. Ismail, M.E.H.: Classical and Quantum Orthogonal Polynomials in One Variable. Cambridge University Press, Cambridge (2005)

    Book  Google Scholar 

  19. Laurie, D.P.: Anti-Gauss quadrature formulas. Math. Comput. 65, 739–747 (1996)

    Article  Google Scholar 

  20. Milovanović, G.V., Stanić, M.: Construction of multiple orthogonal polynomials by discretized Stieltjes–Gautschi procedure and corresponding Gaussian quadratures. Facta Univ. Ser. Math. Inform. 18, 9–29 (2003)

    MathSciNet  MATH  Google Scholar 

  21. Milovanović, G.V., Stanić, M.: Multiple orthogonality and quadratures of Gaussian type. Rend. Circ. Mat. Palermo Serie II Suppl. 76, 75–90 (2005)

    MathSciNet  MATH  Google Scholar 

  22. Notaris, S.E.: Gauss–Kronrod quadrature formulae: a survey of fifty years of research. Electron. Trans. Numer. Anal. 45, 371–404 (2016)

    MathSciNet  MATH  Google Scholar 

  23. Saad, Y.: Iterative Methods for Sparse Linear Systems, 2nd edn. SIAM, Philadelphia (2003)

    Book  Google Scholar 

  24. Van Assche, W.: Padé and Hermite–Padé approximation and orthogonality. Surv. Approx. Theory 2, 61–91 (2006)

    MathSciNet  MATH  Google Scholar 

  25. Ye, Q.: A breakdown-free variation of the nonsymmetric Lanczos algorithm. Math. Comput. 62, 179–207 (1994)

    Article  MathSciNet  Google Scholar 

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Acknowledgements

The authors would like to thank Ulises Fidalgo and Qiang Ye for valuable discussions, and the referees for comments. The research was supported in part by NSF grants DMS-1720259 and DMS-1729509.

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Correspondence to Lothar Reichel.

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Communicated by Marko Huhtanen.

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Alqahtani, H., Reichel, L. Multiple orthogonal polynomials applied to matrix function evaluation. Bit Numer Math 58, 835–849 (2018). https://doi.org/10.1007/s10543-018-0709-x

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  • DOI: https://doi.org/10.1007/s10543-018-0709-x

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