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Part of book or chapter of book . 2025
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Part of book or chapter of book . 2025
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Part of book or chapter of book . 2025
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Part of book or chapter of book . 2025
License: CC BY
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Part of book or chapter of book . 2025
License: CC BY
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Part of book or chapter of book . 2025
License: CC BY
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Application of Semigroups

Authors: Dattatray N. Shinde;

Application of Semigroups

Abstract

This chapter provides a comprehensive survey of the applications of semigroup theory across a diverse range of scientific and technical fields. Beginning with a historical and foundational overview, it establishes the semigroup as a powerful generalization of the group, uniquely suited to modelling systems where operations are associative but not necessarily invertible. The discussion is structured to demonstrate the unifying principles of semigroup applications, from their central role in the algebraic theory of automata and formal languages to their utility in modelling complex physical and biological systems. Specific areas of focus include the use of semigroups to represent state transitions in theoretical computer science, their function as a framework for solving partial differential equations, their critical role in describing the non-unitary dynamics of open quantum systems, and their utility in analyzing the evolution of Markov processes. The chapter concludes by highlighting the unifying theme of semigroups as a tool for analyzing systems with "non-invertible functions" and discusses emerging applications in bioinformatics and other fields.

Keywords

Semigroup; Automata Theory; Partial Differential Equations; Markov Processes; Bioinformatics

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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!
0
Average
Average
Average
Green