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Learning the Emergent Bulk Geometry of the Three Dimensional Ising Model
computational-physicsdisordered-systems-and-neural-networkshigh-energy-physics-theoryquantum-physicsstatistical-mechanics
We use Monte Carlo data for the three-dimensional Ising model at the critical temperature to predict an emergent radial geometry of the bulk using machine learning. Specifically, we employ a differentiable solver for a probe field on an asymptotically $\mathrm{AdS}_4$ background, trained to reproduc
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