skip to main content
10.1145/3476446.3536180acmconferencesArticle/Chapter ViewAbstractPublication PagesissacConference Proceedingsconference-collections
research-article

A Greedy Approach to the Canny-Emiris Formula

Authors Info & Claims
Published:05 July 2022Publication History

ABSTRACT

The Canny-Emiris formula [3] gives the sparse resultant as a ratio between the determinant of a Sylvester-type matrix and a minor of it, by a subdivision algorithm. The most complete proof of the formula was given by D'Andrea et al. in [9] under general conditions on the underlying mixed subdivision. Before the proof, Canny and Pedersen had proposed [5] a greedy algorithm which provides smaller matrices, in general. The goal of this paper is to give an explicit class of mixed subdivisions for the greedy approach such that the formula holds, and the dimensions of the matrices are reduced compared to the subdivision algorithm. We measure this reduction for the case when the Newton polytopes are zonotopes generated by n line segments (where n is the rank of the underlying lattice), and for the case of multihomogeneous systems. This article comes with a JULIA implementation of the treated cases.

References

  1. M. R. Bender, J.C. Faugere, A. Mantzaflaris, and E. Tsigaridas. 2021. Koszul-type determinantal formulas for families of mixed multilinear systems. SIAM Jrnl. on App. AG, 5, 4, 589--619. doi: 10.1137/20M1332190.Google ScholarGoogle Scholar
  2. M.R. Bender, J.-C. Faugère, and E. Tsigaridas. 2018. Towards mixed gröbner basis algorithms: the multihomogeneous and sparse case. ISSAC - 43rd Intern. Symp. on Symbolic & Algebraic Computation. doi: 10.1145/3208976.3209018. https: //hal.inria.fr/hal-01787423.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. J.F. Canny and I.Z. Emiris. 1993. An efficient algorithm for the sparse mixed resultant. Appl. algebra, algebraic algor. & error-correcting codes, 673, 89--104.Google ScholarGoogle Scholar
  4. J.F. Canny and I.Z. Emiris. 1995. Efficient incremental algorithms for the sparse resultant and the mixed volume. Jour. Symb. Comput., 20, 117--149. doi: 10.1006/jsco.1995.1041.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. J.F. Canny and P. Pedersen. 1993. An Algorithm for the Newton Resultant. Technical report. Cornell University, NY, USA.Google ScholarGoogle Scholar
  6. D. Cox, J. Little, and D. O'Shea. 2015. Using Algebraic Geometry. Volume 185. isbn: 0--387--20706--6. doi: 10.1007/b138611.Google ScholarGoogle Scholar
  7. C. D'Andrea. 2001. Macaulay style formulas for sparse resultants. Trans. AMS, 354, (August 2001). doi: 10.2307/3073009.Google ScholarGoogle Scholar
  8. C. D'Andrea and I.Z. Emiris. 2001. Computing sparse projection operators. Contemporary Mathematics, 286, 121--140.Google ScholarGoogle ScholarCross RefCross Ref
  9. C. D'Andrea, G. Jeronimo, and M. Sombra. 2020. The cannyemiris conjecture for the sparse resultant. CoRR, abs/2004.14622. arXiv: 2004.14622. https://arxiv.org/abs/2004.14622.Google ScholarGoogle Scholar
  10. C. D'Andrea and M. Sombra. 2015. A poisson formula for the sparse resultant. Proc. London Math. Society, 110, 4, 932--964. issn: 0024--6115. doi: 10.1112/plms/pdu069. http://dx.doi.org/10.1112/plms/pdu069.Google ScholarGoogle ScholarCross RefCross Ref
  11. A. Dickenstein and I.Z. Emiris. 2003. Multihomogeneous resultant formulae by means of complexes. Journal of Symbolic Computation, 36, 317--342. doi: 10.1016/S0747--7171(03)00086--5.Google ScholarGoogle ScholarCross RefCross Ref
  12. I. Emiris and A. Mantzaflaris. 2012. Multihomogeneous resultant formulae for systems with scaled support. J. Symbolic Computation, 820--842. doi: 10.1016/j.jsc.2011.12.010. https://hal.inria.fr/inria-00355881.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. I.Z. Emiris and A. Rege. 1994. Monomial bases and polynomial system solving. Proc. Intern. Symp. Symbolic & Algebraic Computation, 114--122. M.A.H. MacCallum, editor. doi: 10. 1145/190347.190374. https://doi.org/10.1145/190347.190374.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. M. Gelfand, M. Kapranov, and A. Zelevinsky. 1994. Discriminants, resultants, and multidimensional determinants. Birkhauser.Google ScholarGoogle Scholar
  15. F.S. Macaulay. 1903. Some formulae in elimination. Proc. Lond. Math. Soc. 35, 3--27.Google ScholarGoogle Scholar
  16. T. Michiels and R. Cools. 2000. Decomposing the secondary cayley polytope. Discrete and Computational Geometry, 23, 3, 367--380. issn: 1432-0444. doi: https://doi.org/10.1007/PL00009506.Google ScholarGoogle ScholarCross RefCross Ref
  17. R. P. Stanley. 2016. Smith normal form in combinatorics. Journal of Combinatorial Theory, Series A, 144, 476--495. Fifty Years of the Journal of Combinatorial Theory. issn: 0097--3165. doi: https://doi.org/10.1016/j.jcta.2016.06.013.Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. B. Sturmfels. 1994. On the Newton polytope of the resultant. J. Algebraic Combin., 3, 207--236.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. B. Sturmfels and A. Zelevinsky. 1994. Multigraded resultants of sylvester type. Journal of Algebra, 163, 115--127.Google ScholarGoogle ScholarCross RefCross Ref
  20. G.M. Ziegler. 1995. Lectures on Polytopes. (1st edition). Number 152 in Grad Texts in Math. Springer, New York.Google ScholarGoogle Scholar

Index Terms

  1. A Greedy Approach to the Canny-Emiris Formula

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        ISSAC '22: Proceedings of the 2022 International Symposium on Symbolic and Algebraic Computation
        July 2022
        547 pages
        ISBN:9781450386883
        DOI:10.1145/3476446

        Copyright © 2022 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 5 July 2022

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        Overall Acceptance Rate395of838submissions,47%

        Upcoming Conference

        ISSAC '24
      • Article Metrics

        • Downloads (Last 12 months)12
        • Downloads (Last 6 weeks)0

        Other Metrics

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader