Genetic algorithms and the search for viable string vacua

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Article

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.

Keywords

Superstring Vacua Superstrings and Heterotic Strings 

Notes

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Copyright information

© The Author(s) 2014

Authors and Affiliations

  1. 1.IPPP, Durham UniversityDurhamU.K.
  2. 2.Physics DepartmentUniversity of IoanninaIoanninaGreece

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