Revealing Physical Redundancy in the Two-dimensional Fermi-Hubbard Model via Transferable Observable Reconstruction
The Fermi-Hubbard model provides a paradigmatic setting for studying strongly correlated quantum matter, where different observables are commonly used to probe charge, interaction, and spin correlations. In this work, we investigate whether these observables contain mutually transferable physical information beyond their apparent distinction. We quantify such physical redundancy through transferability tests among three representative observables of the two-dimensional Fermi-Hubbard model: total density (N), double occupancy (D), and spin-spin correlation (S). Using a neural-network reconstruction framework, we find that the phase diagram of one observable can be reconstructed from another with accuracy close to self-reconstruction benchmarks, especially in trivial phase regimes. This transferability relies on correct physical labeling, persists across finite-temperature regimes, and remains robust under noisy inputs. Our results suggest that separate observables can carry a substantial fraction of one another's physical information, providing numerical evidence for observable-level redundancy in the two-dimensional Fermi-Hubbard system.