2014

Genetic Algorithms and the Search for Viable String Vacua

Abel, Steven, Rizos, John

Understand

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.

Reading the bibliography…