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Towards Stronger Depth Lower Bounds

Authors Gabriel Bathie , R. Ryan Williams

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Author Details

Gabriel Bathie
  • LaBRI, Université de Bordeaux, France
  • DIENS, PSL Research University, Paris, France
R. Ryan Williams
  • CSAIL, Massachusetts Institute of Technology, Cambridge, MA, USA

Funding

  • Bathie, Gabriel: Portions of this work were completed while the author was visiting MIT.
  • Williams, R. Ryan: Supported by NSF CCF-2127597 and a Frank Quick Faculty Research Innovation Fellowship. Portions of this work was completed while the author was visiting the Simons Institute for the Theory of Computing, at the University of California at Berkeley.

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Gabriel Bathie and R. Ryan Williams. Towards Stronger Depth Lower Bounds. In 15th Innovations in Theoretical Computer Science Conference (ITCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 287, pp. 10:1-10:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/LIPIcs.ITCS.2024.10

Abstract

A fundamental problem in circuit complexity is to find explicit functions that require large depth to compute. When considering the natural DeMorgan basis of {OR,AND}, where negations incur no cost, the best known depth lower bounds for an explicit function in NP have the form (3-o(1))log₂ n, established by Håstad (building on others) in the early 1990s. We make progress on the problem of improving this factor of 3, in two different ways:  
- We consider an "algorithmic method" approach to proving stronger depth lower bounds for non-uniform circuits in the DeMorgan basis. We show that slightly faster algorithms (than what is known) for counting the number of satisfying assignments on subcubic-size DeMorgan formulas would imply supercubic-size DeMorgan formula lower bounds, implying that the depth must be at least (3+ε)log₂ n for some ε > 0. For example, if #SAT on formulas of size n^{2+2ε} can be solved in 2^{n - n^{1-ε}log^k n} time for some ε > 0 and a sufficiently large constant k, then there is a function computable in 2^{O(n)} time with a SAT oracle which does not have n^{3+ε}-size formulas. In fact, the #SAT algorithm only has to work on formulas that are a conjunction of n^{1-ε} subformulas, each of which is n^{1+3ε} size, in order to obtain the supercubic lower bound. As a proof of concept, we show that our new algorithms-to-lower-bounds connection can be applied to prove new lower bounds for "hybrid" DeMorgan formula models which compute interesting functions at their leaves.
- Turning to the {NAND} basis, we establish a greater-than-(3 log₂ n) depth lower bound against uniform circuits solving the SAT problem, using an extension of the "indirect diagonalization" method for NAND formulas. Note that circuits over the NAND basis are a special case of circuits over the DeMorgan basis; however, hard functions such as Andreev’s function (known to require depth (3-o(1))log₂ n in the DeMorgan basis) can still be computed with NAND circuits of depth (3+o(1))log₂ n. Our results imply that SAT requires polylogtime-uniform NAND circuits of depth at least 3.603 log₂ n.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational complexity and cryptography
Keywords
  • DeMorgan formulas
  • depth complexity
  • circuit complexity
  • lower bounds
  • #SAT
  • NAND gates
  • SAT

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