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.
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Abel, S., Rizos, J. Genetic algorithms and the search for viable string vacua. J. High Energ. Phys. 2014, 10 (2014). https://doi.org/10.1007/JHEP08(2014)010
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DOI: https://doi.org/10.1007/JHEP08(2014)010