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cond-mat.mtrl-sci2026
Train for Accuracy, Execute at Scale: Architecture-Preserving Inference for Equivariant Atomistic Foundation Models
Lei Fu, Zihui Feng, Yongheng Li +8
Equivariant atomistic foundation models provide broadly transferable interatomic potentials trained against quantum-mechanical reference data, but their repeated execution at simul…
cond-mat.mes-hall2026
Symmetry-enabled tunable square-lattice Hubbard models in -valley moiré bilayers
Rui Shi, Kejie Bao, Huan Wang +1
Square-lattice moiré systems provide a promising route for quantum simulation of Hubbard physics, yet electrically tunable realizations of the hopping ratio have so far been…
cond-mat.mes-hall2026
Moiré Ferroelectricity-Driven Band Engineering in Twisted Square Bilayers
Kejie Bao, Rui Shi, Huan Wang +2
We develop the moiré band theory for M-valley twisted square homobilayers with layer groups - and -, and propose candidate material realizations. We show that moiré…