Machine learning of Calabi-Yau volumes
@article{Krefl2017MachineLO, title={Machine learning of Calabi-Yau volumes}, author={Daniel Krefl and Rak-Kyeong Seong}, journal={Physical Review D}, year={2017}, volume={96}, pages={066014} }
We employ machine learning techniques to investigate the volume minimum of Sasaki-Einstein base manifolds of noncompact toric Calabi-Yau three-folds. We find that the minimum volume can be approxim ...
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- 2018
- 31
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References
SHOWING 1-10 OF 20 REFERENCES
The Geometric Dual of a–Maximisation for Toric Sasaki–Einstein Manifolds
- Mathematics, Physics
- 2006
- 315
- PDF
From toric geometry to quiver gauge theory: The equivalence of a‐maximization and Z‐minimization
- Mathematics, Physics
- 2005
- 47
- PDF
Counting BPS operators in gauge theories: quivers, syzygies and plethystics
- Physics, Mathematics
- 2007
- 301
- PDF