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Searching the landscape of flux vacua with genetic algorithms. (English) Zbl 1429.83085
Summary: In this paper, we employ genetic algorithms to explore the landscape of type IIB flux vacua. We show that genetic algorithms can efficiently scan the landscape for viable solutions satisfying various criteria. More specifically, we consider a symmetric \(T^6\) as well as the conifold region of a Calabi-Yau hypersurface. We argue that in both cases genetic algorithms are powerful tools for finding flux vacua with interesting phenomenological properties. We also compare genetic algorithms to algorithms based on different breeding mechanisms as well as random walk approaches.

MSC:
83E30 String and superstring theories in gravitational theory
14J32 Calabi-Yau manifolds (algebro-geometric aspects)
68W50 Evolutionary algorithms, genetic algorithms (computational aspects)
81T30 String and superstring theories; other extended objects (e.g., branes) in quantum field theory
Software:
PIKAIA; SDaA
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