Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Kai-Jia Sun"'
Publikováno v:
Physical Review C. 103
Based on an improved multiphase transport (AMPT) model, which gives a good description of proton production with a smooth quark matter to hadronic matter transition in relativistic heavy ion collisions, we study deuteron and triton productions from t
Publikováno v:
Physical Review Research. 2
The machine-learning techniques have shown their capability for studying phase transitions in condensed matter physics. Here, we employ the machine-learning techniques to study the nuclear liquid-gas phase transition. We adopt an unsupervised learnin
Publikováno v:
Physical Review C. 101
We study the production of charmed hadrons $D^{0}$ and $\Lambda_c^+$ in relativistic heavy-ion collisions using an improved quark coalescence model. In particular, we extend the usual coalescence model by letting a produced hadron to have the same ve
Publikováno v:
Physical Review C. 98
Using a covariant quark coalescence model combined with a blast-wave-like analytical parametrization for (anti-)strange-quark phase-space freeze-out configuration, we extract information on strange-quark freeze-out dynamics in $\text{Pb}+\text{Pb}$ c
Autor:
Lie-Wen Chen, Kai-Jia Sun
Publikováno v:
Physical Review C. 95
Based on a covariant coalescence model with a blast-wave-like parametrization for the phase-space configuration of constituent particles at freeze-out, we derive an approximate analytical formula for the yields of clusters produced in relativistic he
Autor:
Kai-Jia Sun, Lie-Wen Chen
Publikováno v:
Physical Review C. 93
We show that the measured yield ratio HΛ3/He3(H¯Λ¯3/He¯3) in Au+Au collisions at sNN=200 GeV and in Pb+Pb collisions at sNN=2.76 TeV can be understood within a covariant coalescence model if (anti-)Λ particles freeze out earlier than (anti-)nuc