Genetic Algorithms and the Search for Viable String Vacua

Abel, S.A.; Rizos, J.

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.

Citation

Abel, S., & Rizos, J. (2014). Genetic Algorithms and the Search for Viable String Vacua. Journal of High Energy Physics, 2014(8), Article 10. https://doi.org/10.1007/jhep08%282014%29010

• Journal Article Type: Article
• Publication Date: Aug 1, 2014
• Deposit Date: Oct 22, 2014
• Publicly Available Date: Dec 17, 2014
• Journal: Journal of High Energy Physics
• Print ISSN: 1126-6708
• Electronic ISSN: 1029-8479
• Publisher: Scuola Internazionale Superiore di Studi Avanzati (SISSA)
• Peer Reviewed: Peer Reviewed
• Volume: 2014
• Issue: 8
• Article Number: 10
• DOI: https://doi.org/10.1007/jhep08%282014%29010
• Public URL: https://durham-repository.worktribe.com/output/1418754
• Related Public URLs: http://arxiv.org/abs/arXiv:1404.7359