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The critical complexity of all (monotone) boolean functions and monotone graph properties

The critical complexity of all (monotone) Boolean functions and monotone graph properties
Authors: Ingo Wegener;

The critical complexity of all (monotone) boolean functions and monotone graph properties

Abstract

CREW-PRAM's are a powerful model of parallel computers. Lower bounds for this model are rather general. \textit{S. A. Cook}, \textit{C. Dwork} and \textit{R. Reischuk} [SIAM J. Comput. 15, 87-97 (1986)] proved that the CREW-PRAM complexity of Boolean functions is bounded by \(\log_ b(f)\), where \(b\approx 4.79\) and c(f) is the critical complexity of f. This lower bound is often even tight. For a class of functions F the critical complexity c(F), the minimum of all c(f) where \(f\in F\), is the best general lower bound on the critical complexity of all \(f\in F\). We determine the critical complexity of the set of all nondegenerate Boolean functions and all monotone nondegenerate Boolean functions up to a small additive term. And we compute exactly the critical complexity of the class of all monotone graph properties, proving partially a conjecture of \textit{G. Turán} [Inf. Process. Lett. 18, 151-153 (1984; Zbl 0542.68026)].

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Keywords

Analysis of algorithms and problem complexity, parallel random access machines, Models of computation (Turing machines, etc.), CREW- PRAM complexity, Graph theory (including graph drawing) in computer science, Switching theory, application of Boolean algebra; Boolean functions, concurrency, critical complexity, parallel computation, Engineering(all)

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selected citations
These citations are derived from selected sources.
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!
16
Average
Top 10%
Average
hybrid