Author

Jiang, Weiguang

INSPIRE profile1982598 ORCID0000-0001-8441-972X

3 papers·396 citations in this corpus

	Paper	Category
Dec 5, 2024#12412.02876	Data-driven analysis of dipole strength functions using artificial neural networks Weiguang Jiang · Tim Egert · Sonia Bacca · Francesca Bonaiti · Peter von Neumann Cosel	nucl-th	PRC	4
Jul 25, 2024#62407.17098	Diagrammatic ab initio methods for infinite nuclear matter with modern chiral interactions Francesco Marino · Weiguang Jiang · Samuel J. Novario	nucl-th	PRC	27
Sep 6, 2018#41809.01292	Gogny-force derived effective shell-model Hamiltonian Weiguang Jiang🇨🇳 · Baishan Hu🇨🇳 · Zhonghao Sun🇨🇳 · Furong Xu🇨🇳	nucl-th	PRC	9

Data-driven analysis of dipole strength functions using artificial neural networks
Weiguang Jiang · Tim Egert · Sonia Bacca · Francesca Bonaiti · Peter von Neumann Cosel
Dec 5, 2024#1nucl-thPRC4 citations
Diagrammatic ab initio methods for infinite nuclear matter with modern chiral interactions
Francesco Marino · Weiguang Jiang · Samuel J. Novario
Jul 25, 2024#6nucl-thPRC27 citations
Gogny-force derived effective shell-model Hamiltonian
Weiguang Jiang🇨🇳 · Baishan Hu🇨🇳 · Zhonghao Sun🇨🇳 · Furong Xu🇨🇳
Sep 6, 2018#4nucl-thPRC9 citations

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Jiang, Weiguang

Data-driven analysis of dipole strength functions using artificial neural networks

Diagrammatic ab initio methods for infinite nuclear matter with modern chiral interactions

Gogny-force derived effective shell-model Hamiltonian