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We design a neural network Ansatz for variationally finding the ground-state wave function of the Homogeneous Electron Gas, a fundamental model in the physics of extended systems of interacting fermions.
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2012
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V. Olevano, A. Titov, M. Ladisa, K. Hämäläinen, S. Huotari, and M. Holzmann, Momentum distribution and compton profile by the ab initio gw approximation, Phys. Rev. B 86
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2014
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M. Taddei, M. Ruggeri, S. Moroni, and M. Holzmann, Iterative backflow renormalization procedure for many-body ground-state wave functions of strongly interacting normal fermi liquids, Physical Review B 91
2015
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2016
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2020
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2021
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2021
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2021
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2022
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K. Haule and K. Chen, Single-particle excitations in the uniform electron gas by diagrammatic monte carlo, Scientific Reports 12
2022
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2022
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L. Wang, H. Xie, and L. Zhang, m* of electron gases: a neural canonical transformation study, Bulletin of the American Physical Society (2022)
2022
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G. Pescia, J. Han, A. Lovato, J. Lu, and G. Carleo, Neural-network quantum states for periodic systems in continuous space, Phys. Rev. Res. 4
2022
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2023
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