A conditional variational autoencoder trained on known Type IIB flux vacua can generate new physically valid flux vectors with targeted superpotential values faster than Metropolis sampling.
Enumerating Flux Vacua with Enhanced Symmetries
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abstract
We study properties of flux vacua in type IIB string theory in several simple but illustrative models. We initiate the study of the relative frequencies of vacua with vanishing superpotential W=0 and with certain discrete symmetries. For the models we investigate we also compute the overall rate of growth of the number of vacua as a function of the D3-brane charge associated to the fluxes, and the distribution of vacua on the moduli space. The latter two questions can also be addressed by the statistical theory developed by Ashok, Denef and Douglas, and our results are in good agreement with their predictions. Analysis of the first two questions requires methods which are more number-theoretic in nature. We develop some elementary techniques of this type, which are based on arithmetic properties of the periods of the compactification geometry at the points in moduli space where the flux vacua are located.
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Solving inverse problems of Type IIB flux vacua with conditional generative models
A conditional variational autoencoder trained on known Type IIB flux vacua can generate new physically valid flux vectors with targeted superpotential values faster than Metropolis sampling.