A neural network learns holographic bulk functions from lattice QCD data at zero chemical potential and embeds them into an EMD model to describe finite-density QCD and locate the critical end point.
Data- driven einstein-dilaton model for pure yang-mills ther- modynamics and glueball spectrum
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HoloNet: Toward a Unified Einstein-Maxwell-Dilaton Framework of QCD
A neural network learns holographic bulk functions from lattice QCD data at zero chemical potential and embeds them into an EMD model to describe finite-density QCD and locate the critical end point.