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H. Liao

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Preprint Jul 2026

Exact Neural-Network Representations of the Motzkin States

The results demonstrate that neural architectures can accurately capture highly non-trivial entanglement features inaccessible to conventional tensor networks, providing prototypic examples for benchmarking and a constructive design framework for future neural-network quantum state developments targeting strongly entan...

Runde Zha, Yun-Tian Gu, Chaohui Fan et al. · 0 citations
Preprint Aug 2026

Optimized Tensor-Network Renormalization for Quantum Dynamics: Resolving the Spectral Function of $\mathrm{K_2Co(SeO_3)_2}$

Tensor-network methods have opened a powerful route for the study of dynamical spectral functions in two-dimensional quantum systems. However, existing approaches within the framework of infinite projected entangled-pair states construct the required renormalization tensors solely from the ground-state environment and...

Jiahang Hu, Runze Chi, B. Normand et al. · 1 citation

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