Characterization and Lower Bounds for Branching Program Size using Projective Dimension

preprint2017arXivOpen access

Abstract

We study projective dimension, a graph parameter (denoted by pd(G)(G) for a graph GG), introduced by (Pudlák, Rödl 1992), who showed that proving lower bounds for pd(Gf)(G_f) for bipartite graphs GfG_f associated with a Boolean function ff imply size lower bounds for branching programs computing ff. Despite several attempts (Pudlák, Rödl 1992 ; Babai, Rónyai, Ganapathy 2000), proving super-linear lower bounds for projective dimension of explicit families of graphs has remained elusive. We show that there exist a Boolean function ff (on nn bits) for which the gap between the projective dimension and size of the optimal branching program computing ff (denoted by bpsize(f)(f)), is 2Ω(n)2^{Ω(n)}. Motivated by the argument in (Pudlák, Rödl 1992), we define two variants of projective dimension - projective dimension with intersection dimension 1 (denoted by upd(G)(G)) and bitwise decomposable projective dimension (denoted by bitpdim(G)(G)). As our main result, we show that there is an explicit family of graphs on N=2nN = 2^n vertices such that the projective dimension is O(n)O(\sqrt{n}), the projective dimension with intersection dimension 11 is Ω(n)Ω(n) and the bitwise decomposable projective dimension is Ω(n1.5log⁡n)Ω(\frac{n^{1.5}}{\log n}). We also show that there exist a Boolean function ff (on nn bits) for which the gap between upd(Gf)(G_f) and bpsize(f)(f) is 2Ω(n)2^{Ω(n)}. In contrast, we also show that the bitwise decomposable projective dimension characterizes size of the branching program up to a polynomial factor. That is, there exists a constant c>0c>0 and for any function ff, bitpdim(Gf)/6≤bpsize(f)≤(bitpdim(Gf))c\textrm{bitpdim}(G_f)/6 \le \textrm{bpsize}(f) \le (\textrm{bitpdim}(G_f))^c. We also study two other variants of projective dimension and show that they are exactly equal to well-studied graph parameters - bipartite clique cover number and bipartite partition number respectively.

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