‘Infinite Neural Network Quantum States: Entanglement and Training Dynamics’

“We study infinite limits of neural network quantum states (\infty -NNQS), which exhibit representation power through ensemble statistics, and also tractable gradient descent dynamics. Ensemble averages of entanglement entropies are expressed in terms of neural network correlators, and architectures that exhibit volume-law entanglement are presented. The analytic calculations of entanglement entropy bound are tractable because the ensemble statistics are simplified in the Gaussian process limit.”

Find the paper and full list of authors in Machine Learning: Science and Technology.

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