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arXiv · 1404.7359

Genetic Algorithms and the Search for Viable String Vacua

Steven Abel·John Rizos
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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 10^{10} models, and yet a Genetic Algorithm can find them after constructing only 10^5 examples. Such non-deterministic search methods may be the only means to search for Standard Model string vacua with detailed phenomenological requirements.

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Steven Abel, John Rizos. 2014-06-16. Genetic Algorithms and the Search for Viable String Vacua. https://doi.org/10.1007/jhep08(2014)010

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