Skip to main content
Log in

Fraction-free matrix factors: new forms for LU and QR factors

  • Research Article
  • Published:
Frontiers of Computer Science in China Aims and scope Submit manuscript

Abstract

Gaussian elimination and LU factoring have been greatly studied from the algorithmic point of view, but much less from the point view of the best output format. In this paper, we give new output formats for fraction free LU factoring and for QR factoring. The formats and the algorithms used to obtain them are valid for any matrix system in which the entries are taken from an integral domain, not just for integer matrix systems. After discussing the new output format of LU factoring, the complexity analysis for the fraction free algorithm and fraction free output is given. Our new output format contains smaller entries than previously suggested forms, and it avoids the gcd computations required by some other partially fraction free computations. As applications of our fraction free algorithm and format, we demonstrate how to construct a fraction free QR factorization and how to solve linear systems within a given domain.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Nakos G C, Turner P R, Williams R M. Fraction-free algorithms for linear and polynomial equations. SIGSAM Bull, ACM Press, 1997, 31(3): 11–19

    Google Scholar 

  2. Zhou W, Carette J, Jeffrey D J, et al. Hierarchical representations with signatures for large expression management. AISC, Springer-Verlag, LNAI 4120, 2006, 254–268

  3. Sasaki T, Nurao H. Efficient Gaussian elimination method for symbolic determinants and linear systems. ACM Transactions on Mathematical Software, 1982, 8(3): 277–289

    Article  MATH  Google Scholar 

  4. Kirsch B J, Turner P R. Modified Gaussian elimination for adaptive beamforming using complex RNS arithmetic. NAWC-AD Tech Rep, NAWCADWAR, 1994, 941112-50

  5. Kirsch B J, Turner P R. Adaptive beamforming using RNS arithmetic. In: Proceedings of ARTH. Washington DC: IEEE Computer Society, 1993, 36–43

    Google Scholar 

  6. Turner P R. Gauss elimination: workhorse of linear algebra. NAWC-AD Tech Rep, NAWCAD-PAX 96-194-TR, 1996

  7. Bareiss EH. Sylvester’s identity and multistep integer-preserving Gaussian elimination. Mathematics of Computation, 1968, 22(103): 565–578

    Article  MATH  MathSciNet  Google Scholar 

  8. Bareiss E H. Computational solutions of matrix problems over an integral domain. J. Inst. Maths Applics, 1972, 10: 68–104

    Article  MATH  MathSciNet  Google Scholar 

  9. Gentleman WM, Johnson S C. Analysis of algorithms, a case study: determinants of polynomials. In: Proceedings of 5th Annual ACM Symp on Theory of Computing. Austin: ACM Press, 1973, 135–142

    Chapter  Google Scholar 

  10. Griss M L. An efficient sparse minor expansion algorithm. Houston: ACM, 1976, 429–434

    Google Scholar 

  11. McClellan M T. The exact solution of systems of linear equations with polynomial coefficients. J ACM, 1973, 20(4): 563–588

    Article  MATH  MathSciNet  Google Scholar 

  12. Smit J. The efficient calculation of symbolic determinants. In: Proceedings of SYMSAC. New York: ACM, 1976, 105–113

    Google Scholar 

  13. Smit J. A cancellation free algorithm, with factoring capabilities, for the efficient solution of large sparse sets of equations. In: Proceedings of ISSAC. New York: ACM, 1981, 146–154

    Google Scholar 

  14. Turing A M. Rounding-off errors in matrix processes. Quart. J. Mech. Appl. Math, 1948, 1: 287–308

    Article  MATH  MathSciNet  Google Scholar 

  15. Corless R M, Jeffrey D J. The Turing factorization of a rectangular matrix. SIGSAM Bull, ACM Press, 1997, 31(3): 20–30

    Google Scholar 

  16. Dixon J D. Exact solution of linear equations using p-adic expansion. Numer. Math, 1982, 137–141

  17. Moenck R T, Carter J H. Approximate algorithms to derive exact solutions to systems of linear equations. In: Proceedings of the International Symposium on Symbolic and Algebraic Computation. Berlin: Springer-Verlag, 1979, 65–73

    Google Scholar 

  18. Storjohann A. High-order lifting and integrality certification. Journal of Symbolic Computation, 2003, 36(3–4): 613–648

    Article  MATH  MathSciNet  Google Scholar 

  19. Storjohann A. The shifted number system for fast linear algebra on integer matrices. Journal of Complexity, 2005, 21(4): 609–650

    Article  MATH  MathSciNet  Google Scholar 

  20. von zur Gathen J, Gerhard J. Modern computer algebra. London: Cambridge University Press, 1999

    MATH  Google Scholar 

  21. Krick T, Pardo L M, Sombra, M. Sharp estimates for the arithmetic Nullstellensatz. Duke Mathematical Journal, 2001, 109(3): 521–598

    Article  MATH  MathSciNet  Google Scholar 

  22. Pursell L, Trimble S Y. Gram-Schmidt orthogonalization by Gaussian elimination. American Math. Monthly, 1991, 98(6): 544–549

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wenqin Zhou.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhou, W., Jeffrey, D.J. Fraction-free matrix factors: new forms for LU and QR factors. Front. Comput. Sci. China 2, 67–80 (2008). https://doi.org/10.1007/s11704-008-0005-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11704-008-0005-z

Keywords

Navigation