Characterization and Lower Bounds for Branching Program Size using Projective Dimension
Abstract
We study projective dimension, a graph parameter (denoted by pd for a graph ), introduced by (Pudl\'ak, R\"odl 1992), who showed that proving lower bounds for pd for bipartite graphs associated with a Boolean function imply size lower bounds for branching programs computing . Despite several attempts (Pudl\'ak, R\"odl 1992 ; Babai, R\'{o}nyai, 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 (on bits) for which the gap between the projective dimension and size of the optimal branching program computing (denoted by bpsize), is . Motivated by the argument in (Pudl\'ak, R\"odl 1992), we define two variants of projective dimension - projective dimension with intersection dimension 1 (denoted by upd) and bitwise decomposable projective dimension (denoted by bitpdim). As our main result, we show that there is an explicit family of graphs on vertices such that the projective dimension is , the projective dimension with intersection dimension is and the bitwise decomposable projective dimension is . We also show that there exist a Boolean function (on bits) for which the gap between upd and bpsize is . 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 and for any function , . 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.
Cite
@article{arxiv.1604.07200,
title = {Characterization and Lower Bounds for Branching Program Size using Projective Dimension},
author = {Krishnamoorthy Dinesh and Sajin Koroth and Jayalal Sarma},
journal= {arXiv preprint arXiv:1604.07200},
year = {2020}
}
Comments
24 pages, 3 figures