Header menu link for other important links
X
Characterization and lower bounds for branching program size using projective dimension
Krishnamoorthy Dinesh,
Published in Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
2016
Volume: 65
   
Pages: 37.1 - 37.14
Abstract
We study projective dimension, a graph parameter (denoted by pd(G) for a graph G), introduced by Pudlák and Rödl (1992). For a Boolean function f(on n bits), Pudlák and Rödl associated a bipartite graph Gf and showed that size of the optimal branching program computing f (denoted by bpsize(f)) is at least pd(Gf) (also denoted by pd(f)). Hence, proving lower bounds for pd(f) imply lower bounds for bpsize(f). Despite several attempts (Pudlák and Rödl (1992), Rónyai et.al, (2000)), proving super-linear lower bounds for projective dimension of explicit families of graphs has remained elusive. We observe that there exist a Boolean function f for which the gap between the pd(f) and bpsize(f)) is 2Ω(n). Motivated by the argument in Pudlák and Rödl (1992), we define two variants of projective dimension - projective dimension with intersection dimension 1 (denoted by upd(f)) and bitwise decomposable projective dimension (denoted by bpdim(f)). We show the following results: (a) We observe that there exist a Boolean function f for which the gap between upd(f) and bpsize(f) is 2Ω(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 large constant c > 0 and for any function f, bpdim(f)/6 ≤ bpsize(f) ≤ (bpdim(f))c. (b) We introduce a new candidate function family f for showing super-polynomial lower bounds for bpdim(f). As our main result, we demonstrate gaps between pd(f) and the above two new measures for f: pd(f) = O(√n) upd(f) = Ω(n) bpdim(f) = Ω(n1.5/log n). (c) Although not related to branching program lower bounds, we derive exponential lower bounds for two restricted variants of pd(f) and upd(f) respectively by observing that they are exactly equal to well-studied graph parameters - bipartite clique cover number and bipartite partition number respectively. © Krishnamoorthy Dinesh, Sajin Koroth, and Jayalal Sarma.
About the journal
JournalLeibniz International Proceedings in Informatics, LIPIcs
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISSN18688969
Open AccessNo
Concepts (12)
  •  related image
    Boolean functions
  •  related image
    Graph theory
  •  related image
    Software engineering
  •  related image
    Bipartite graphs
  •  related image
    BIPARTITE PARTITION
  •  related image
    Branching programs
  •  related image
    GRAPH PARAMETERS
  •  related image
    Lower bounds
  •  related image
    Polynomial factor
  •  related image
    PROJECTIVE DIMENSION
  •  related image
    SUPER-POLYNOMIALS
  •  related image
    C (programming language)