Generative AI for brane configurations and gauge theory phases in string theory
Rak-Kyeong Seong (Ulsan National Institute of Science and Technology (UNIST))
Abstract: This talk concerns a family of 4d N=1 supersymmetric gauge theories associated with Calabi-Yau geometries, whose Type IIB brane realizations are encoded in the shape of the mirror curve of the Calabi-Yau. We show how a generative AI model can be trained to learn this correspondence between geometry and gauge theory: taking the complex-structure moduli of the mirror curve as input, the AI model generates its shape, from which the corresponding gauge theory Lagrangian and phase can be read off. The model also tracks how the brane configurations vary across gauge theory phases related by Seiberg duality.
general relativity and quantum cosmologyHEP - experimentHEP - latticeHEP - phenomenologyHEP - theory
Audience: researchers in the topic
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| Organizer: | Ioannis Papadimitriou* |
| *contact for this listing |