Characterization and Lower Bounds for Branching Program Size using Projective Dimension
Krishnamoorthy Dinesh, Sajin Koroth, Jayalal Sarma

TL;DR
This paper investigates the projective dimension of graphs related to Boolean functions, establishing exponential gaps with branching program size and introducing variants that provide new lower bounds and characterizations for computational complexity.
Contribution
The paper introduces two variants of projective dimension, proves exponential gaps with branching program size, and shows that one variant characterizes size up to a polynomial factor.
Findings
Existence of Boolean functions with exponential gap between projective dimension and branching program size.
Explicit graph families with specific bounds on projective dimension variants.
Bitwise decomposable projective dimension characterizes branching program size up to polynomial factors.
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…
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