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Calabi-Yau Four/Five/Six-folds as $\mathbb{P}^n_\textbf{w}$ Hypersurfaces: Machine Learning, Approximation, and Generation
May 8, 2024, 4:45 a.m. | Edward Hirst, Tancredi Schettini Gherardini
stat.ML updates on arXiv.org arxiv.org
Abstract: Calabi-Yau four-folds may be constructed as hypersurfaces in weighted projective spaces of complex dimension 5 defined via weight systems of 6 weights. In this work, neural networks were implemented to learn the Calabi-Yau Hodge numbers from the weight systems, where gradient saliency and symbolic regression then inspired a truncation of the Landau-Ginzburg model formula for the Hodge numbers of any dimensional Calabi-Yau constructed in this way. The approximation always provides a tight lower bound, is …
abstract approximation arxiv five gradient hep-th learn machine machine learning math.ag networks neural networks numbers regression six spaces stat.ml systems type via work
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