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Computing Transformation Semigroups

Computing transformation semigroups
Authors: Steve Linton; Götz Pfeiffer; Edmund F. Robertson; Nikola Ruskuc;

Computing Transformation Semigroups

Abstract

The paper describes data structures and algorithms for performing computations in a finite semigroup \(S\) with identity, generated by a set of transformations. A basic idea behind the algorithms is the partition of \(S\) with the aid of an equivalence relation \(\mathcal R\), one of Green's relations. The paper presents algorithms for performing global computations in \(S\) (like its size and structure), as well as local computations within an \(\mathcal R\)-class, without touching the rest of \(S\), thereby improving existing results by \textit{G. Lallement} and \textit{R. McFadden} [J. Symb. Comput. 10, No. 5, 481-498 (1990; Zbl 0792.20061)]. This approach is bound to result in more efficient computations. The algorithms have been implemented in the GAP computer algebra system, and are available as the share package MONOID. Examples of computations using MONOID are given in the paper.

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Ireland
Related Organizations
Keywords

computation, Externally hosted open access publications with University of Galway authors, Algebra and Number Theory, Green relations, Representation of semigroups; actions of semigroups on sets, Symbolic computation and algebraic computation, algorithms, generalized Schützenberger groups, Semigroups of transformations, relations, partitions, etc., Computational Mathematics, finite transformation semigroups, General structure theory for semigroups

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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!
9
Average
Top 10%
Average
hybrid
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