Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Xiao-Hua Fan"'
Publikováno v:
Physics Letters B, Vol 848, Iss , Pp 138359- (2024)
A convolutional neural network-based classifier is elaborated to retrace the initial orientation of deformed nucleus-nucleus collisions by integrating multiple typical experimental observables. The isospin-dependent Boltzmann-Uehling-Uhlenbeck transp
Externí odkaz:
https://doaj.org/article/293f9783c81143d19455bfdac41efe1a
Publikováno v:
Physics Letters B, Vol 840, Iss , Pp 137870- (2023)
A Kohn-Sham scheme based multi-task neural network is elaborated for the supervised learning of nuclear shell evolution. The training set is composed of the single-particle wave functions and occupation probabilities of 320 nuclei, calculated by the
Externí odkaz:
https://doaj.org/article/d6b63883a2cf42b7a034cce1355648fd
Autor:
Xiao-Hua Fan, Zu-Xing Yang, Peng Yin, Peng-Hui Chen, Jian-Min Dong, Zhi-Pan Li, Haozhao Liang
Publikováno v:
Physics Letters B, Vol 834, Iss , Pp 137482- (2022)
We adapt the local density approximation to add the high-momentum tails (HMTs) to finite nuclei's Slater-determinant momentum distributions. The HMTs are extracted by the extended Brueckner-Hartree-Fock (EBHF) method or by the lowest order cluster ap
Externí odkaz:
https://doaj.org/article/5503916d73d14faabeab7b165e2f1032
Publikováno v:
Physics Letters B, Vol 823, Iss , Pp 136650- (2021)
With the datasets of the density distributions calculated by Skyrme density functional theories, we elaborated deep neural networks to generate the density profile and provide a table of related hyperparameters set for similar applications of other s
Externí odkaz:
https://doaj.org/article/1cd0c4711f174ceeacd82d62fccdcfbf
Publikováno v:
Physics Letters
A Kohn-Sham scheme based multi-task neural network is elaborated for the supervised learning of nuclear shell evolution. The training set is composed of the single-particle wave functions and occupation probabilities of 320 nuclei, calculated by the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1d395d396ef7abc5af2422b0af51f03
http://arxiv.org/abs/2212.02093
http://arxiv.org/abs/2212.02093
Autor:
Hao Liu, Haijun Deng, Kang-Lian Tan, Xue-Min Liang, Xiao-hua Fan, Guoxin Li, Tingyu Mou, Run-Sheng Xie, Zhi-Qiang Chen
Publikováno v:
Gastroenterology Report
Background:?> Laparoscopic surgery for rectal cancer is commonly performed in China. However, compared with open surgery, the effectiveness of laparoscopic surgery, especially the long-term survival, has not been sufficiently proved. Methods:?> Data
Autor:
Qicheng Chen, Shi-Jun Xia, Lixing Cao, Xiao-Hua Fan, Yang-Xue Huang, Jinxuan Lin, Tao Wang, Huachan Gan, Zhiqiang Chen, Zhi Jiang
Publikováno v:
World Journal of Gastroenterology
BACKGROUND During the perioperative period, the characteristic therapy of traditional Chinese medicine is effective in improving postoperative rehabilitation. In large-scale hospitals practicing traditional Chinese medicine, there is accumulating exp
Publikováno v:
Physics Letters
Physics Letters B, Vol 823, Iss, Pp 136650-(2021)
Physics Letters B, Vol 823, Iss, Pp 136650-(2021)
With the datasets of the density distributions calculated by Skyrme density functional theories, we elaborated deep neural networks to generate the density profile and provide a table of related hyperparameters set for similar applications of other s
Publikováno v:
Chinese Physics C. 46:064103
We extend the deformed relativistic Hartree-Bogoliubov theory in continuum (DRHBc) to go beyond-mean-field framework by performing a two-dimensional collective Hamiltonian. The influences of dynamical correlations on the ground-state properties are e
Initialization effects of nucleon profile on the π yields in heavy-ion collisions at medium energies
Publikováno v:
Journal of Physics G: Nuclear and Particle Physics. 48:105105
We study a problem of $\pi$ production in heavy ion collisions in the context of the Isospin-dependent Boltzmann-Uehling-Uhlenbeck (IBUU) transport model. We generated nucleon densities using two different models, the Skyrme-Hartree-Fock (SHF) model