14 papers
Superconductivity in the - Hubbard Model from Symmetry-Preserving Neural-Network Quantum States
Riccardo Rende, Luciano Loris Viteritti, Antoine Georges
Despite its fundamental importance in the theory of strongly correlated electrons, the nature of the ground state of the two-dimensional doped Hubbard model remains intensely debat…
A quantitative analysis of semantic information in deep representations of text and images
Santiago Acevedo, Andrea Mascaretti, Riccardo Rende +3
It was recently observed that the representations of different models that process identical or semantically related inputs tend to align. We analyze this phenomenon using the Info…
Fermi surface change and -wave superconductivity in the square lattice Kondo-Heisenberg model
Alexander Nikolaenko, Riccardo Rende, Luciano Loris Viteritti +2
We study the two-dimensional Kondo-Heisenberg model on a square lattice, with the conduction electrons away from half-filling, using neural network quantum states. Mapping the grou…
Thermalization Dynamics in the Two-Dimensional Hubbard Model with Neural-Network Quantum States
Alessandro Sinibaldi, Luciano Loris Viteritti, Riccardo Rende +2
Thermalization in strongly correlated fermionic systems remains a central open problem in quantum many-body physics. In this work, we investigate the real-time dynamics and the app…
Scaling Laws for Neural-Network Quantum States
Riccardo Rende, Alessandro Sinibaldi, Luciano Loris Viteritti +3
Scaling laws, the power-law relations between loss, architecture size, and compute observed in modern neural networks, offer a quantitative way to characterize the complexity of a…
Beyond Variational Bias: Resolving Intertwined Orders in the Hubbard Model
Luciano Loris Viteritti, Riccardo Rende, Christopher Roth +3
The two-dimensional Hubbard model at finite doping hosts competing or intertwined orders, resulting in conflicting conclusions from different computational approaches regarding its…