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Author

Luciano Loris Viteritti

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Preprint Sep 2026

Designing Strongly Correlated Quantum Phases of Matter with Foundation Neural-Network Quantum States

Designing a material with a desired property amounts to solving an inverse problem: finding the couplings of a microscopic Hamiltonian whose ground state exhibits that property. For strongly correlated quantum systems, solving this problem efficiently remains largely out of reach. To address this challenge, we present...

A. Sinibaldi, Luciano Loris Viteritti, Riccardo Rende et al. · 0 citations
Preprint Aug 2026

Superconductivity in the $t$-$t'$ Hubbard Model from Symmetry-Preserving Neural-Network Quantum States

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 debated. Variational approaches provide a powerful route to this problem, but their conclusions can depend sensitively on the chosen wave-functio...

Riccardo Rende, Luciano Loris Viteritti, Antoine Georges · 2 citations · ⚡1
Preprint Sep 2026

Kibble-Zurek Dynamics in Two-dimensional Frustrated Systems with a Neural Foundation-state Subspace Method

Universal scaling generated when a strongly interacting quantum many-body system is driven across a continuous phase transition provides a dynamical probe of equilibrium criticality. Accessing this regime numerically in two dimensions is challenging because it requires accurate real-time evolution of correlated many-bo...

Linda Mauron, Luciano Loris Viteritti, Z. Denis et al. · 0 citations

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