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arXiv · 1907.10072

Searching the Landscape of Flux Vacua with Genetic Algorithms

Alex Cole·Andreas Schachner·Gary Shiu
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Abstract

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.

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Alex Cole, Andreas Schachner, Gary Shiu. 2019-07-23. Searching the Landscape of Flux Vacua with Genetic Algorithms. https://doi.org/10.1007/jhep11(2019)045

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