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Synergy between deep neural networks and the variational Monte Carlo method for small 4HeN clusters

Synergy between deep neural networks and the variational Monte Carlo method for small 4HeN clusters

William Freitas, S. A. Vitiello

ARTIGO

Inglês

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,... Ver mais
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... Ver mais

FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP

2016/17612-7; 2020/10505-6

Aberto

Synergy between deep neural networks and the variational Monte Carlo method for small 4HeN clusters

William Freitas, S. A. Vitiello

										

Synergy between deep neural networks and the variational Monte Carlo method for small 4HeN clusters

William Freitas, S. A. Vitiello

    Fontes

    Quantum: the open journal for quantum science (Fonte avulsa)