Deep Learning Complete Intersection Calabi–Yau Manifolds
Published in Machine Learning in Pure Mathematics and Theoretical Physics, 2023
Cite as: H. Erbin, R. Finotello, Deep Learning Complete Intersection Calabi–Yau Manifolds. In Machine Learning in Pure Mathematics and Theoretical Physics, World Scientific, pp. 151-181 (2023), edited by Y.-H. He https://doi.org/10.1142/9781800613706_0005
We review advancements in deep learning techniques for complete intersection Calabi–Yau (CICY) 3- and 4-folds, with the aim of understanding better how to handle algebraic topological data with machine learning. We first discuss methodological aspects and data analysis, before describing neural network architectures. Then, we describe the state-of-the-art accuracy in predicting Hodge numbers. We include new results on extrapolating predictions from low to high Hodge numbers, and conversely.