We study the well-known type IIA intersecting D-brane models on the T6/ℤ2×ℤ2′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {T}^6/\\left({\\mathbb{Z}}_2\ imes {\\mathbb{Z}}_2^{\\prime}\\right) $$\\end{document} orientifold via a machine-learning approach. We apply several autoencoder models with and without positional encoding to D6-brane configurations satisfying certain concrete models described in ref. [1] and attempt to extract some features which the configurations possess. We observe that the configurations cluster in two-dimensional latent layers of the autoencoder models and analyze which physical quantities are relevant to the clustering. As a result, it is found that tadpole charges of hidden D6-branes characterize the clustering. We expect that there is another important factor because a checkerboard pattern in two-dimensional latent layers is observed in the clustering.
Read full abstract