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A Contour-Integral Based Method for Counting the Eigenvalues Inside a Region

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Abstract

In many applications, the information about the number of eigenvalues inside a given region is required. In this work, we develop a contour-integral based method for this purpose. Our method is motivated by two findings. There exist methods for estimating the number of eigenvalues inside a region in the complex plane, but our method is able to compute the number exactly. Our method has a good potential to be implemented on a high-performance parallel architecture. Numerical experiments are reported to show the viability of our method.

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References

  1. Ahlfors, L.: Complex Analysis, 3rd edn. McGraw-Hill, Inc., New York City (1979)

    MATH  Google Scholar 

  2. Bai, Z., Demmel, J., Dongarra, J., Ruhe, A., Van der Vorst, H.: Templates for the Solution of Algebraic Eigenvalue Problems: A Practical Guide. SIAM, Philadelphia (2000)

    Book  MATH  Google Scholar 

  3. Bai, Z., Demmel, J., Gu, G.: An inverse free parallel spectral divide and conquer algorithm for nonsymmetric eigenproblem. Numer. Math. 76, 279–308 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  4. Boisvert, R.F., Pozo, R., Remington, K., Barrett, R., Dongarra, J.: The matrix market: a web resource for test matrix collections. In: Boisvert, R.F. (ed.) Quality of Numerical Software: Assessment and Enhancement, IFIP Advances in Information and Communication Technology, pp. 125–137. Chapman & Hall, London (1997)

    Chapter  Google Scholar 

  5. Cerdá, J., Soria, F.: Accurate and transferable extended Hückel-type tight-binding parameters. Phys. Rev. B 61, 7965 (2000)

    Article  Google Scholar 

  6. Chan, T.T.: Rank revealing QR factorizations. Linear Algebra Appl. 88–89, 67–82 (1987)

    MathSciNet  MATH  Google Scholar 

  7. Davis, P.J., Rabinowitz, P.: Methods of Numerical Integration, 2nd edn. Academic Press, Orlando (1984)

    MATH  Google Scholar 

  8. Demmel, J.: Applied Numerical Linear Algebra. SIAM, Philadelphia (1997)

    Book  MATH  Google Scholar 

  9. Di Napoli, E., Polizzi, E., Saad, Y.: Efficient estimation of eigenvalue counts in an interval. arXiv:1308.4275

  10. Futamura, Y., Tadano, H., Sakurai, T.: Parallel stochastic estimation method of eigenvalue distribution. JSIAM Lett. 2, 127–130 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  11. Gantmacher, F.R.: The Theory of Matrices. Chelsea, New York (1959)

    MATH  Google Scholar 

  12. Golub, G.H., Van Loan, C.F.: Matrix Computations, 3rd edn. Johns Hopkins University Press, Baltimore (1996)

    MATH  Google Scholar 

  13. Grimes, R.G., Lewis, J.D., Simon, H.D.: A shifted block Lanczos algorithm for solving sparse symmetric generalized eigenproblems. SIAM J. Matrix Anal. Appl. 15, 228–272 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  14. Hinrichsen, D., Pritchard, A.J.: Mathematical Systems Theory I: Modelling, State Space Analysis and Robustness. Springer, Berlin (2005)

    Book  MATH  Google Scholar 

  15. Hoshi, T., Yamamoto, S., Fujiwara, T., Sogabe, T., Zhang, S.L.: An order-\(N\) electronic structure theory with generalized eigenvalue equations and its application to a ten-million-atom system. J. Phys. Condens. Matter 24, 165502 (2012)

    Article  Google Scholar 

  16. Kamgnia, E.R., Philippe, B.: Counting eigenvalues in domains of the complex field. arXiv:1110.4797

  17. Lin, L., Saad, Y., Yang, C.: Approximating spectral densities of large matrices. arXiv:1308.5467

  18. Moler, C.B., Stewart, G.W.: An algorithm for generalized matrix eigenvalue problems. SIAM J. Numer. Anal. 10, 241–256 (1973)

    Article  MathSciNet  MATH  Google Scholar 

  19. Polizzi, E.: Density-matrix-based algorithm for solving eigenvalue problems. Phys. Rev. B 79, 115112 (2009)

    Article  Google Scholar 

  20. Ruhe, A.: Rational Krylov: a practical algorithm for large sparse nonsymmetric matrix pencils. SIAM J. Sci. Comput. 19, 1535–1551 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  21. Saad, Y.: Numerical Methods for Large Eigenvalue Problems. SIAM, Philadelphia (2011)

    Book  MATH  Google Scholar 

  22. Sakurai, T., Futamura, Y., Tadano, H.: Efficient parameter estimation and implementation of a contour integral-based eigensolver. J. Algorithms Comput. Technol. 7, 249–269 (2013)

    Article  MathSciNet  Google Scholar 

  23. Sakurai, T., Sugiura, H.: A projection method for generalized eigenvalue problems using numerical integration. J. Comput. Appl. Math. 159, 119–128 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  24. Sakurai, T., Tadano, H.: CIRR: a Rayleigh–Ritz type method with contour integral for generalized eigenvalue problems. Hokkaido Math. J. 36, 745–757 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  25. Sontag, E.D.: Mathematical Control Theory: Deterministic Finite Dimensional Systems, 2nd edn. Springer, New York (1998)

    Book  MATH  Google Scholar 

  26. Stewart, G.W.: Matrix Algorithms, Vol. II, Eigensystems. SIAM, Philadelphia (2001)

    Book  MATH  Google Scholar 

  27. Tang, P., Polizzi, E.: FEAST as a subspace iteration eigensolver accelerated by approximate spectral projection. SIAM J. Matrix Anal. Appl. 35, 354–390 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  28. von Luxburg, U.: A tutorial on spectral clustering. Stat. Comput. 17, 395–416 (2007)

    Article  MathSciNet  Google Scholar 

  29. Yin, G., Chan, R., Yueng, M.-C.: A FEAST algorithm with oblique projection for generalized eigenvalue problems. Numer. Linear Algebra Appl. 24, e2092 (2017)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

I would like to thank Professor Raymond H. Chan, my thesis advisor, for his help in preparing this paper. I also would like to thank the anonymous reviewers for their useful suggestions which have greatly improved this paper. This work was supported by the National Natural Science Foundation of China (NSFC) under Grant 11701593.

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Correspondence to Guojian Yin.

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Yin, G. A Contour-Integral Based Method for Counting the Eigenvalues Inside a Region. J Sci Comput 78, 1942–1961 (2019). https://doi.org/10.1007/s10915-018-0838-z

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  • DOI: https://doi.org/10.1007/s10915-018-0838-z

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