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Genetic algorithms and the search for viable string vacua.

Abel, S.A. and Rizos, J. (2014) 'Genetic algorithms and the search for viable string vacua.', Journal of high energy physics., 2014 (8). p. 10.

Abstract

Genetic Algorithms are introduced as a search method for finding string vacua with viable phenomenological properties. It is shown, by testing them against a class of Free Fermionic models, that they are orders of magnitude more efficient than a randomised search. As an example, three generation, exophobic, Pati-Salam models with a top Yukawa occur once in every 1010 models, and yet a Genetic Algorithm can find them after constructing only 105 examples. Such non-deterministic search methods may be the only means to search for Standard Model string vacua with detailed phenomenological requirements.

Item Type:Article
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Available under License - Creative Commons Attribution.
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Status:Peer-reviewed
Publisher Web site:http://dx.doi.org/10.1007/JHEP08(2014)010
Publisher statement:© 2014 The Authors. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits any use, distribution and reproduction in any medium, provided the original author(s) and source are credited.
Date accepted:No date available
Date deposited:17 December 2014
Date of first online publication:August 2014
Date first made open access:No date available

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