A Stronger LP Bound for Formula Size Lower Bounds via Clique Constraints

We introduce a new technique proving formula size lower bounds based on the linear programming bound originally introduced by Karchmer, Kushilevitz and Nisan [11] and the theory of stable set polytope. We apply it to majority functions and prove their formula size lower bounds improved from the classical result of Khrapchenko [13]. Moreover, we introduce a notion of unbalanced recursive ternary majority functions motivated by a decomposition theory of monotone self-dual functions and give integrally matching upper and lower bounds of their formula size. We also show monotone formula size lower bounds of balanced recursive ternary majority functions improved from the quantum adversary bound of Laplante, Lee and Szegedy [15].

• Type: Conference
• Year: 2009
• Where: STACS
• Authors: Kenya Ueno
• Keywords: Formula Size, Majority Functions, Size Lower Bounds, STACS 2009, Theoretical Computer Science