Neural quantum states are a new family of variational Ansätze for quantum-many body wave
functions with advantageous properties in the notoriously challenging case of two spatial …

Among the variational wave functions for fermionic Hamiltonians, neural network backflow
(NNBF) and hidden fermion determinant states (HFDS) are two prominent classes that …

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 …

We study the preparation of thermal states of the dense and sparse Sachdev-Ye-Kitaev
(SYK) model using a variational quantum algorithm for $6\le N\le 12$ Majorana fermions …

Passetti et al.[Physical Review Letters 131, 036502 (2023)] recently assessed the potential
of neural quantum states (NQS) in learning ground-state wave functions with volume-law …

Despite the huge theoretical potential of neural quantum states, their use in describing
generic, highly-correlated quantum many-body systems still often poses practical difficulties …

Finding reliable approximations to the quantum many-body problem is one of the central
challenges of modern physics. Elemental to this endeavor is the development of advanced …

The Sachdev-Ye-Kitaev (SYK) model, known for its strong quantum correlations and chaotic
behavior, serves as a key platform for quantum gravity studies. However, variationally …

A central problem in quantum mechanics involves solving the Electronic Schrodinger
Equation for a molecule or material. The Variational Monte Carlo approach to this problem …

We investigate the ergodicity-to-localization transition in interacting fermion systems
subjected to a spatially uniform electric field. For that we employ the recently proposed …