2022/04/17 by Andrei Constantin, Constantin, Andrei
Computer Science · Decision Sciences · Physics and Astronomy · #Artificial Intelligence (cs.AI) #Computational Physics and Python Applications #FOS: Computer and information sciences #FOS: Physical sciences #High Energy Physics - Theory (hep-th) #Particle physics theoretical and experimental studies #Scientific Computing and Data Management
paper · pdf · doi:10.48550/arxiv.2204.08073
openalex publication_date 2022/04/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The goal of identifying the Standard Model of particle physics and its extensions within string theory has been one of the principal driving forces in string phenomenology. Recently, the incorporation of artificial intelligence in string theory and certain theoretical advancements have brought to light unexpected solutions to mathematical hurdles that have so far hindered progress in this direction. In this review we focus on model building efforts in the context of the E8× E8 heterotic string compactified on smooth Calabi-Yau threefolds and discuss several areas in which machine learning is expected to make a difference.