Year: 2023
Type: book-chapter
Abstract: 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 networks 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.
Source: WORLD SCIENTIFIC (EUROPE) eBooks
Authors: Harold Erbin, Riccardo Finotello
Institutions: Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Université Paris-Saclay, Laboratoire d'Intégration des Systèmes et des Technologies, The NSF AI Institute for Artificial Intelligence and Fundamental Interactions, Massachusetts Institute of Technology, CEA Paris-Saclay - Etablissement de Saclay, CEA Paris-Saclay
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4382284155