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Durham University

Department of Mathematical Sciences

Academic Staff

Publication details for Professor Steven Abel

Abel, S.A. & Rizos, J. (2014). Genetic Algorithms and the Search for Viable String Vacua. Journal of High Energy Physics 2014(8): 10.

Author(s) from Durham


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.