• DocumentCode
    2376774
  • Title

    Tensor Rank: Some Lower and Upper Bounds

  • Author

    Alexeev, Boris ; Forbes, Michael A. ; Tsimerman, Jacob

  • Author_Institution
    Dept. of Math., Princeton Univ., Princeton, NJ, USA
  • fYear
    2011
  • fDate
    8-11 June 2011
  • Firstpage
    283
  • Lastpage
    291
  • Abstract
    The results of Strassen and Raz show that good enough tensor rank lower bounds have implications for algebraic circuit/formula lower bounds. We explore tensor rank lower and upper bounds, focusing on explicit tensors. For odd d, we construct field-independent explicit 0/1 tensors T : [n]d → F with rank at least 2n⌊d/2⌋ + n - Θ(d lg n). This improves the lower-order terms in known lower bounds for any odd d ≥ 3. We also explore a generalization of permutation matrices, which we denote permutation tensors. We show, by apply ing known counting lower bounds, that there exist order-3 permutation tensors with super-linear rank as well as order d permutation tensors with high rank. We also explore a natural class of permutation tensors, which we call group tensors. For any group G, we define the group tensor TGd : Gd → F, by TGd(g1, ,gd) = 1 iff g1 ⋯ gd = 1G. We give two upper bounds for the rank of these tensors. The first uses representation theory and works over "large" fields F, showing (among other things) that rankF(TGd) ≤ |G|d/2. In the case that d = 3, we are able to show that rankF(TG3) ≤ O(|G|ω/2) ≤ O(|G|1.19), where ω is the exponent of matrix multiplication. The next upper bound uses interpolation and only works for abelian G, showing that over any field F that rankF(TGd) ≤ O(|G|1+1g d lgd-1 |G|). In either case, this shows that many permutation tensors have far from maximal rank, which is very different from the matrix case and thus eliminates many natural candidates for high tensor rank. We also explore monotone tensor rank. We give explicit 0/1 tensors T - - : [n]d → F that have tensor rank at most dn but have monotone tensor rank exactly nd-1. This is a nearly optimal separation.
  • Keywords
    circuit complexity; interpolation; matrix multiplication; tensors; algebraic circuit lower bound; algebraic formula lower bound; group tensor; interpolation; matrix multiplication; permutation matrices; permutation tensor; representation theory; tensor rank lower bounds; tensor rank upper bound; Complexity theory; Computational modeling; Integrated circuit modeling; Polynomials; Tensile stress; USA Councils; Upper bound; algebraic complexity; tensor rank;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Complexity (CCC), 2011 IEEE 26th Annual Conference on
  • Conference_Location
    San Jose, CA
  • ISSN
    1093-0159
  • Print_ISBN
    978-1-4577-0179-5
  • Electronic_ISBN
    1093-0159
  • Type

    conf

  • DOI
    10.1109/CCC.2011.28
  • Filename
    5959837