Nature Physics, Published online: 09 July 2024; doi:10.1038/s41567-024-02567-0
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.
