An improved optimization algorithm enables the training of large-scale neural quantum states in which the enormous number of neuron connections capture the intricate complexity of quantum many-body wavefunctions. This advance leads to unprecedented accuracy in paradigmatic quantum models, opening up new avenues for simulating and understanding complex quantum phenomena.
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This is a summary of: Chen, A. & Heyl, M. Empowering deep neural quantum states through efficient optimization. Nat. Phys. https://doi.org/10.1038/s41567-024-02566-1 (2024).
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Efficient optimization of deep neural quantum states. Nat. Phys. 20, 1381–1382 (2024). https://doi.org/10.1038/s41567-024-02567-0
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DOI: https://doi.org/10.1038/s41567-024-02567-0
