Agradecimentos: WF is thankful for useful discussions with Dr. Markus Holzmann and Dr. Matthew Foulkes. Simulations were performed in part at the Centro Nacional de Processamento de Alto Desempenho em São Paulo (CENAPAD-SP). The authors acknowledge financial support from the Brazilian agency, Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), projects Proc. No. 2016/17612-7 and Proc. No. 2020/10505-6 Ver menos

Abstract: We introduce a neural network-based approach for modeling wave functions that satisfy Bose-Einstein statistics. Applying this ing from 2 to 14 atoms), we accurately predict ground state energies, pair density functions, and two-body contact parameters C(N) 2 related to weak unitarity. The results obtained via the variational Monte Carlo method exhibit remarkable agreement with previous studies using the diffusion Monte Carlo method, which is considered exact within its statistical uncertainties. This indicates the effectiveness of our neural network approach for investigating many-body systems governed by Bose-Einstein statistics Ver menos