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Li-Zhong Fu

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#machine learning Preprint Sep 2026

Foundation Neural-Network Quantum States for Molecular Potential Energy Surfaces in Second Quantization

Second-quantized neural-network quantum states have achieved accurate molecular energies, but extending them across molecular geometries requires a shared representation of the geometry-dependent wavefunction coefficients. We introduce geometry-conditioned foundation neural-network quantum states for molecular electron...

Li-Zhong Fu, Jia-Nan Wei, Wen-Guan Wang et al. · 0 citations

Preprint Aug 2026

Scaling Neural Network Quantum States for Ab Initio Quantum Chemistry

Together, these results place autoregressive neural quantum states within the broader landscape of empirical neural scaling and open a quantitative route toward the systematic scaling of neural quantum solvers for ab initio quantum chemistry.

Chen Yu, Han-Lin Kong, Jia-Nan Wei et al. · 0 citations

Aug 2026

Symmetry-Blocked Matrix Product States as a Neural-Network Quantum-State Ansatz for Quantum Chemistry.

This work introduces symmetry-blocked matrix product states (MPS) as neural-network quantum-state ansatzes, denoted QiankunNet-MPS, for ab initio quantum chemistry, explicitly enforcing the U(1) ⊗ U(1) particle-number symmetry of electronic Hamiltonians to eliminate unphysical configurations and reduce the number of va...

Li-Zhong Fu, Bo-Wen Kan, Chu Guo et al. · Journal of Chemical Theory a... · 0 citations