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Article type: Research Article
Authors: Koroth, Sajin† | Sarma, Jayalal
Affiliations: Department of Computer Science & Engineering, Indian Institute of Technology Madras, Chennai 36, India. [email protected], [email protected]
Correspondence: [†] Address for correspondence: Department of CSE, Indian Institute of Technology Madras, Chennai 600036, India.
Note: [*] A preliminary version of this work with a subset of results was presented at the 20th International Computing and Combinatorics Conference (COCOON’14) and appears in [1].
Abstract: We study depth lower bounds against non-monotone circuits, parametrized by a new measure of non-monotonicity: the orientation of a function f is the characteristic vector of the minimum sized set of negated variables needed in any DeMorgan circuit (circuits where negations appear only at the leaves) computing f. We prove trade-off results between the depth and the weight/structure of the orientation vectors in any circuit C computing the CLIQUE function on an n vertex graph. We prove that if C is of depth d and each gate computes a Boolean function with orientation of weight at most w (in terms of the inputs to C), then d × w must be Ω(n). In particular, if the weights are o(nlogkn), then C must be of depth ω(logk n). We prove a barrier for our general technique. However, using specific properties of the CLIQUE function (used in Amano Maruoka (2005)) and the Karchmer–Wigderson framework (Karchmer Wigderson (1988)), we go beyond the limitations and obtain lower bounds when the weight restrictions are less stringent. We then study the depth lower bounds when the structure of the orientation vector is restricted. Asymptotic improvements to our results (in the restricted setting) separates NP from NC. As our main tool, we generalize Karchmer–Wigderson games (Karchmer Wigderson (1988)) for monotone functions to work for non-monotone circuits parametrized by the weight/structure of the orientation. We also prove structural results about orientation and prove connections between number of negations and weight of orientations required to compute a function.
DOI: 10.3233/FI-2017-1515
Journal: Fundamenta Informaticae, vol. 152, no. 2, pp. 123-144, 2017
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