Ab initio calculation of real solids via neural network ansatz

HIGHLIGHTS

• who: Xiang Li from the (UNIVERSITY) have published the Article: Ab initio calculation of real solids via neural network ansatz, in the Journal: (JOURNAL) of 24/05/2022
• what: The authors propose an architecture that extends molecular neural_networks with the inclusion of periodic boundary conditions to enable ab initio calculation of real solids. The authors propose a powerful periodic neural_network ansatz for solids, which combines periodic distance features20 with existing molecule neural_networks10. Based on that, the authors develop a highly efficient QMC method for ab initio calculation of real solid and general periodic systems with . . .
  

   

  

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