• DocumentCode
    3018765
  • Title

    On Medium-Uniformity and Circuit Lower Bounds

  • Author

    Santhanam, Rajesh ; Williams, Ross

  • Author_Institution
    Sch. of Inf., Univ. of Edinburgh, Edinburgh, UK
  • fYear
    2013
  • fDate
    5-7 June 2013
  • Firstpage
    15
  • Lastpage
    23
  • Abstract
    We explore relationships between circuit complexity, the complexity of generating circuits, and algorithms for analyzing circuits. Our results can be divided into two parts: 1. Lower Bounds Against Medium-Uniform Circuits. Informally, a circuit class is “medium uniform” if it can be generated by an algorithmic process that is somewhat complex (stronger than LOGTIME) but not infeasible. Using a new kind of indirect diagonalization argument, we prove several new unconditional lower bounds against medium uniform circuit classes, including: ; For all k, P is not contained in P-uniform SIZE(nk). That is, for all k there is a language Lk ∈ P that does not have O(nk)-size circuits constructible in polynomial time. This improves Kannan´s lower bound from 1982 that NP is not in P-uniform SIZE(nk) for any fixed k. ; For all k, NP is not in P||NP-uniform SIZE(nk). This also improves Kannan´s theorem, but in a different way: the uniformity condition on the circuits is stronger than that on the language itself. ; For all k, LOGSPACE does not have LOGSPACE-uniform branching programs of size nk. 2. Eliminating Non-Uniformity and (Non-Uniform) Circuit Lower Bounds. We complement these results by showing how to convert any potential simulation of LOGTIME-uniform NC1 in ACC0/poly or TC0/poly into a medium-uniform simulation using small advice. This lemma can be used to simplify the proof that faster SAT algorithms imply NEXP circuit lower bounds, and leads to the following new connection: . Consider the following task: given a TC0 circuit C of nO(1) size, output yes when C is unsatisfiable, and output no when C has at least 2n-2 satisfying assignments. (Behavior on other inputs can be arbitrary.) Clearly, this problem can be solved efficiently using randomness. If this problem can be solved deterministical- y in 2n-ω(log n) time, then NEXP ⊄ TC0/poly. The lemma can also be used to derandomize randomized TC0 simulations of NC1 on almost all inputs: ; Suppose NC1 ⊆ BPTC0. Then for every ε > 0 and every language L in NC1, there is a (uniform) TC0 circuit family of polynomial size recognizing a language L´ such that L and L´ differ on at most 2 inputs of length n, for all n.
  • Keywords
    circuit complexity; computability; Kannan lower bound; LOGSPACE-uniform branching program; LOGTIME-uniform NC; NEXP circuit lower bound; P-uniform SIZE; SAT algorithm; circuit complexity; circuit lower bounds; indirect diagonalization argument; medium-uniformity; polynomial time; Complexity theory; Encoding; Indexes; Integrated circuit modeling; Logic gates; Polynomials; Standards; circuit complexity; derandomization; lower bounds; medium uniformity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Complexity (CCC), 2013 IEEE Conference on
  • Conference_Location
    Stanford, CA
  • Type

    conf

  • DOI
    10.1109/CCC.2013.40
  • Filename
    6597745