A deep neural network approach to solve the Dirac equation

• Published in: The European physical journal. A, Hadrons and nuclei Vol. 61; no. 7
• Main Authors: Wang, Chuanxin, Naito, Tomoya, Li, Jian, Liang, Haozhao
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 15.07.2025; Springer Nature B.V
• Subjects: Artificial neural networks; Dirac equation; Excitation; Hadrons; Heavy Ions; Machine learning; Nuclear Fusion; Nuclear Physics; Particle and Nuclear Physics; Physics; Physics and Astronomy; Regular Article - Theoretical Physics; Unsupervised learning

We extend the method from [Naito, Naito, and Hashimoto, Phys. Rev. Research 5 , 033189 (2023)] to solve the Dirac equation not only for the ground state but also for low-lying excited states using a deep neural network and the unsupervised machine learning technique. The variational method fails bec...