Internet publication
String model building, reinforcement learning and genetic algorithms
- Abstract:
- We investigate reinforcement learning and genetic algorithms in the context of heterotic Calabi-Yau models with monad bundles. Both methods are found to be highly efficient in identifying phenomenologically attractive three-family models, in cases where systematic scans are not feasible. For monads on the bi-cubic Calabi-Yau either method facilitates a complete search of the environment and leads to similar sets of previously unknown three-family models.
- Publication status:
- Published
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(Preview, Pre-print, pdf, 1.5MB, Terms of use)
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- Publication website:
- https://arxiv.org/abs/2111.07333v1
Authors
- Publication date:
- 2021-11-14
- Language:
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English
- Pubs id:
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1211327
- Local pid:
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pubs:1211327
- Deposit date:
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2022-08-01
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- Copyright holder:
- Abel et al.
- Copyright date:
- 2021
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