Neural network learns confining potentials and dilaton profile in holographic QCD from meson spectra, predicting steeper IR dilaton and pion masses with good accuracy.
Emerging Holography
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abstract
We rederive AdS/CFT predictions for infrared two-point functions by an entirely four dimensional approach, without reference to holography. This approach, originally due to Migdal in the context of QCD, utilizes an extrapolation from the ultraviolet to the infrared using a Pade approximation of the two-point function. We show that the Pade approximation and AdS/CFT give the same leading order predictions, and discuss including power corrections such as those due to condensates of gluons and quarks in QCD. At finite order the Pade approximation provides a gauge invariant regularization of a higher dimensional gauge theory in the spirit of deconstructed extra dimensions. The radial direction of anti-de Sitter space emerges naturally in this approach.
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Learning holographic QCD with unflavoured meson spectra
Neural network learns confining potentials and dilaton profile in holographic QCD from meson spectra, predicting steeper IR dilaton and pion masses with good accuracy.