Entanglement features of random neural network quantum states

نویسندگان

چکیده

Restricted Boltzmann machines (RBMs) are a class of neural networks that have been successfully employed as variational ansatz for quantum many-body wave functions. Here, we develop an analytic method to study spin states encoded by random RBMs with independent and identically distributed complex Gaussian weights. By mapping the computation ensemble-averaged quantities statistical mechanics models, able investigate parameter space RBM ensemble in thermodynamic limit. We discover qualitatively distinct functions varying parameters, which correspond phases equivalent model. Notably, there is regime typical near-maximal entanglement entropy limit, similar Haar-random states. However, these generically exhibit nonergodic behavior Ising basis, do not form state designs, making them distinguishable from

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ژورنال

عنوان ژورنال: Physical review

سال: 2022

ISSN: ['0556-2813', '1538-4497', '1089-490X']

DOI: https://doi.org/10.1103/physrevb.106.115138