Mott Transition and Volume Law Entanglement with Neural Quantum States

Abstract

The interplay between delocalisation and repulsive interactions can cause electronic systems to undergo a Mott transition between a metal and an insulator. Here we use neural network hidden fermion determinantal states (HFDS) to uncover this transition in the disordered, fully-connected Hubbard model. Whilst dynamical mean-field theory (DMFT) provides exact solutions to physical observables of the model in the thermodynamic limit, our method allows us to directly access the wave function for finite system sizes well beyond the reach of exact diagonalisation. We demonstrate how HFDS are able to obtain more accurate results in the metallic regime and in the vicinity of the transition than calculations based on a Matrix Product State (MPS) ansatz, for which the volume law of entanglement exhibited by the system is prohibitive. We use the HFDS method to calculate the energy and double occupancy, the quasi-particle weight and the energy gap and, importantly, the amplitudes of the wave function which provide a novel insight into this model. Our work paves the way for the study of strongly correlated electron systems with neural quantum states.

Main Text: 5 pages, 3 figures

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• Efficiency of the hidden fermion determinant states Ansatz in the light of different complexity measures
• Basis dependence of Neural Quantum States for the Transverse Field Ising Model