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https://dx.doi.org/10.48550/ar...
Article . 2021
License: arXiv Non-Exclusive Distribution
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Classification of OBDD size for monotone 2-CNFs

Authors: Razgon, Igor;

Classification of OBDD size for monotone 2-CNFs

Abstract

We introduce a new graph parameter called linear upper maximum induced matching width \textsc{lu-mim width}, denoted for a graph $G$ by $lu(G)$. We prove that the smallest size of the \textsc{obdd} for $��$, the monotone 2-\textsc{cnf} corresponding to $G$, is sandwiched between $2^{lu(G)}$ and $n^{O(lu(G))}$. The upper bound is based on a combinatorial statement that might be of an independent interest. We show that the bounds in terms of this parameter are best possible.

The presentation has been significantly improved. New material has been added: full proofs instead of sketches, examples with illustrations

Keywords

FOS: Computer and information sciences, Ordered Binary Decision Diagrams, upper and lower bounds, Computational Complexity (cs.CC), Monotone 2-CNFs, 004, Computer Science - Computational Complexity, Width parameters of graphs, FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), ddc: ddc:004

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
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Average
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