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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

Neural-network quantum states (NNQSs) can represent many-electron wave functions without explicitly enumerating the determinant space, but their accuracy depends jointly on model size and variational-optimization effort. Here we characterize this dependence for a physics-conditioned autoregressive NNQS trained separate...

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