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Holography, Pade Approximants and Deconstruction
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Holography, Pade Approximants and Deconstruction
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We investigate the relation between holographic calculations in 5D and the Migdal approach to correlation functions in large N theories. The latter employs Pade approximation to extrapolate short distance correlation functions to large distances. We make the Migdal/5D relation more precise by quantifying the correspondence between Pade approximation and the background and boundary conditions in 5D. We also establish a connection between the Migdal approach and the models of deconstructed dimensions.
Forward citations
Cited by 2 Pith papers
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Neural network learns confining potentials and dilaton profile in holographic QCD from meson spectra, predicting steeper IR dilaton and pion masses with good accuracy.
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Learning holographic QCD with unflavored meson spectra
Neural networks trained on rho, a1, a2 and f0 mass spectra reconstruct a holographic QCD background with scalar potential k1 X^3 + k2 X^4 (k1 ~ -8, k2 ~17) and claim a pion-mass prediction that is partly circular.
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