Author

Wu, Zeming

INSPIRE profile1828440 ORCID0000-0002-3184-8122

4 papers·70 citations in this corpus

	Paper	Category
Jul 7, 2023#22307.02995	Collective flow and the fluid behavior in p/d/ $^{3}$ He+Au collisions at $s_{N N} = 200$ GeV Zeming Wu🇨🇳 · Baochi Fu🇨🇳 · Shujun Zhao🇨🇳 · Runsheng Liu🇨🇳 · Huichao Song🇨🇳	nucl-th	CPC	6
Nov 26, 2018#151811.09466	Universal scaling of the sigma field and net-protons from Langevin dynamics of model A Shanjin Wu🇨🇳 · Zeming Wu🇨🇳 · Huichao Song🇨🇳	nucl-th	PRC	27
Jul 17, 2018#161807.05728	Applications of deep learning to relativistic hydrodynamics Hengfeng Huang🇨🇳 · Bowen Xiao🇨🇳 · Huixin Xiong🇨🇳 · Zeming Wu🇨🇳 · Yadong Mu🇨🇳 · Huichao Song (Peking U)🇨🇳	nucl-th	NPA	5
Jan 11, 2018#11801.03334	Applications of deep learning to relativistic hydrodynamics Hengfeng Huang🇨🇳 · Bowen Xiao🇨🇳 · Ziming Liu🇨🇳 · Zeming Wu🇨🇳 · Yadong Mu🇨🇳 · Huichao Song🇨🇳	nucl-th	PRResearch	32

Collective flow and the fluid behavior in p/d/ $^{3}$ He+Au collisions at $s_{N N} = 200$ GeV
Zeming Wu🇨🇳 · Baochi Fu🇨🇳 · Shujun Zhao🇨🇳 · Runsheng Liu🇨🇳 · Huichao Song🇨🇳
Jul 7, 2023#2nucl-thCPC6 citations
Universal scaling of the sigma field and net-protons from Langevin dynamics of model A
Shanjin Wu🇨🇳 · Zeming Wu🇨🇳 · Huichao Song🇨🇳
Nov 26, 2018#15nucl-thPRC27 citations
Applications of deep learning to relativistic hydrodynamics
Hengfeng Huang🇨🇳 · Bowen Xiao🇨🇳 · Huixin Xiong🇨🇳 · Zeming Wu🇨🇳 · Yadong Mu🇨🇳 · Huichao Song (Peking U)🇨🇳
Jul 17, 2018#16nucl-thNPA5 citations
Applications of deep learning to relativistic hydrodynamics
Hengfeng Huang🇨🇳 · Bowen Xiao🇨🇳 · Ziming Liu🇨🇳 · Zeming Wu🇨🇳 · Yadong Mu🇨🇳 · Huichao Song🇨🇳
Jan 11, 2018#1nucl-thPRResearch32 citations

Showing 1–4 of 4·25 / 50 / 100per page

Page 1 of 1

Shows only papers in the locally ingested corpus, matched through the INSPIRE author identity. This may not match the author's full publication record.

Wu, Zeming

Collective flow and the fluid behavior in p/d/3He+Au collisions at sNN​​=200 GeV

Universal scaling of the sigma field and net-protons from Langevin dynamics of model A

Applications of deep learning to relativistic hydrodynamics

Applications of deep learning to relativistic hydrodynamics

Collective flow and the fluid behavior in p/d/ $^{3}$ He+Au collisions at $s_{N N} = 200$ GeV