Sampling string vacua using generative models
Abstract
Abstract We apply generative models to a key problem in the string compactification program, namely construction of type IIB string vacua. To this end, we make use of a Bayesian flow network, a generative model capable of handling discrete data, to generate flux vectors that give rise to type IIB vacua. Furthermore, we sample flux vacua that have certain desirable properties by employing a Transformer as a conditional generative model. Both models demonstrate good performance in finding flux vacua and thus prove to be powerful tools in the exploration of the string landscape.
Fields of Study & Subjects
Algorithms and Data Compression
Publication details
- Journal / source
- Machine Learning Science and Technology
- Publisher
- IOP Publishing
- Volume
- 7
- Issue
- 1
- Pages
- 015018–015018
- Publication date
- 2 January 2026
- Language
- EN