We employ a deep learning approach to infer the holographic model of a strange metal. As input data representing the boundary quantum system, we use observables such as conductivity and/or entanglement entropy. As a toy model, we consider the Einstein-Maxwell-Dilaton theory and apply deep learning to reconstruct the spacetime metric and the potential functions in the action. We would like to emphasize that our approach is not limited to holography; it can be applied to a broad range of physics problems involving differential equations and integrals. In this sense, it has the potential to serve as a general problem-solving technique for physics. (References: 2502.10245 [hep-th], 2406.07395 [hep-th] 2401.00939 [hep-th,] 2011.13726 [physics.class-ph])

Biography

2013~       Professor, Gwangju Institute of Science and Technology, Korea

2011~2013  Postdoc,  Amsterdam U. the Netherlands

2009~2011  Postdoc,  Southampton U. UK

2002~2009  Ph.D,    Stony Brook U. New York, USA

Inviter: Li Li