Poster
in
Workshop: Machine Learning and the Physical Sciences
Machine learning for complete intersection Calabi-Yau manifolds
Harold Erbin · Mohamed Tamaazousti · Riccardo Finotello
Abstract:
We describe the recent developments in using machine learning techniques to compute Hodge numbers of complete intersection Calabi-Yau (CICY) 3- and 4-folds. The main motivation is to understand how to study data from algebraic geometry and solve problems relevant for string theory with machine learning. We describe the state-of-the art methods which reach near-perfect accuracy for several Hodge numbers, and discuss extrapolating from low to high Hodge numbers, and conversely.
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