Fermionic neural Gibbs states

Jannes Nys; Juan Carrasquilla

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arXiv · 2512.04663

Fermionic neural Gibbs states

Jannes Nys·Juan Carrasquilla

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Abstract

We introduce fermionic neural Gibbs states (fNGS), a variational framework for modeling finite-temperature properties of strongly interacting fermions. fNGS starts from a reference mean-field thermofield-double state and uses neural-network transformations together with imaginary-time evolution to systematically build strong correlations. Applied to the doped Fermi-Hubbard model, a minimal lattice model capturing essential features of strong electronic correlations, fNGS accurately reproduces thermal energies over a broad range of temperatures, interaction strengths, even at large dopings, for system sizes beyond the reach of exact methods. These results demonstrate a scalable route to studying finite-temperature properties of strongly correlated fermionic systems beyond one dimension with neural-network representations of quantum states.

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quant-ph cond-mat.str-el cs.LG physics.comp-ph

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Jannes Nys, Juan Carrasquilla. 2025-12-04. Fermionic neural Gibbs states. https://arxiv.org/abs/2512.04663

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