Generating Triangulations and Fibrations with Reinforcement Learning
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866913391106326528 |
|---|---|
| author | Berglund, Per Butbaia, Giorgi He, Yang-Hui Heyes, Elli Hirst, Edward Jejjala, Vishnu |
| author_facet | Berglund, Per Butbaia, Giorgi He, Yang-Hui Heyes, Elli Hirst, Edward Jejjala, Vishnu |
| contents | We apply reinforcement learning (RL) to generate fine regular star triangulations of reflexive polytopes, that give rise to smooth Calabi-Yau (CY) hypersurfaces. We demonstrate that, by simple modifications to the data encoding and reward function, one can search for CYs that satisfy a set of desirable string compactification conditions. For instance, we show that our RL algorithm can generate triangulations together with holomorphic vector bundles that satisfy anomaly cancellation and poly-stability conditions in heterotic compactification. Furthermore, we show that our algorithm can be used to search for reflexive subpolytopes together with compatible triangulations that define fibration structures of the CYs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_21017 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Generating Triangulations and Fibrations with Reinforcement Learning Berglund, Per Butbaia, Giorgi He, Yang-Hui Heyes, Elli Hirst, Edward Jejjala, Vishnu High Energy Physics - Theory Mathematical Physics Algebraic Geometry We apply reinforcement learning (RL) to generate fine regular star triangulations of reflexive polytopes, that give rise to smooth Calabi-Yau (CY) hypersurfaces. We demonstrate that, by simple modifications to the data encoding and reward function, one can search for CYs that satisfy a set of desirable string compactification conditions. For instance, we show that our RL algorithm can generate triangulations together with holomorphic vector bundles that satisfy anomaly cancellation and poly-stability conditions in heterotic compactification. Furthermore, we show that our algorithm can be used to search for reflexive subpolytopes together with compatible triangulations that define fibration structures of the CYs. |
| title | Generating Triangulations and Fibrations with Reinforcement Learning |
| topic | High Energy Physics - Theory Mathematical Physics Algebraic Geometry |
| url | https://arxiv.org/abs/2405.21017 |