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NNQS-Transformer: an Efficient and Scalable Neural Network Quantum States Approach for Ab initio Quantum Chemistry
Neural network quantum state (NNQS) has emerged as a promising candidate for quantum many-body problems, but its practical applications are often hindered by the high cost of sampling and local energy calculation.
Anharmonic Raman spectra simulation of crystals from deep neural networks
Raman spectroscopy is an effective tool to analyze the structures of various materials as it provides chemical and compositional information.
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