4 papers
Revisiting identified-particle spectra using the Boltzmann-Gibbs blast-wave model in a Bayesian inference framework
Z. Xie, W. Z. Li, J. Q. Tao +7
We perform a Bayesian analysis of transverse momentum () spectra of identified particles, i.e., pions, kaons, and protons, at midrapidity in Au+Au collisions and Pb…
Initial spin fluctuations as a probe of cluster spin structure in and nuclei
Xiang Fan, Jun-Qi Tao, Ze-Fang Jiang +1
We investigate the imprint of clustering on initial spin fluctuations in relativistic and collisions…
Deep learning approaches to extract nuclear deformation parameters from initial-state information in heavy-ion collisions
Jun-Qi Tao, Yang Liu, Yu Sha +5
The deformation of heavy nuclei leaves characteristic imprints on the initial conditions of relativistic heavy-ion collisions. However, event-by-event fluctuations make the quantit…
A deep learning approach for predicting multiple observables in Au+Au collisions at RHIC
Jun-Qi Tao, Xiang Fan, Yang Liu +4
We develop a neural network model, based on the processes of high-energy heavy-ion collisions, to study and predict several experimental observables in Au+Au collisions. We present…