Inception Neural Network for Complete Intersection Calabi-Yau 3-folds

07/27/2020

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by   Harold Erbin, et al.

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We introduce a neural network inspired by Google's Inception model to compute the Hodge number h^1,1 of complete intersection Calabi-Yau (CICY) 3-folds. This architecture improves largely the accuracy of the predictions over existing results, giving already 97 training. Moreover, accuracy climbs to 99 training. This proves that neural networks are a valuable resource to study geometric aspects in both pure mathematics and string theory.