The entropy per rapidity dS/dy produced in central Pb-Pb ultra-relativistic nuclear collisions at LHC energies is calculated using experimentally identified particle spectra and source radii estimated from Hanbury Bro...The entropy per rapidity dS/dy produced in central Pb-Pb ultra-relativistic nuclear collisions at LHC energies is calculated using experimentally identified particle spectra and source radii estimated from Hanbury Brown-Twiss (HBT) correlations for particles π, k, p, Λ, Ω, and ∑ and π, k, p, Λ, and K^(0)_(s) at √s =2.76 and 5.02 TeV, respectively. An artificial neural network (ANN) simulation model is used to estimate the entropy per rapidity dS/dy at the considered energies. The simulation results are compared with equivalent experimental data, and a good agreement is achieved. A mathematical equation describing the experimental data is obtained. Extrapolation of the transverse momentum spectra at pT =0 is required to calculate dS/dy;thus, we use two different fitting functions, the Tsallis distribution and hadron resonance gas (HRG) model. The success of the ANN model in describing the experimental measurements leads to the prediction of several spectra values for the mentioned particles, which may lead to further predictions in the absence of experiments.展开更多
文摘The entropy per rapidity dS/dy produced in central Pb-Pb ultra-relativistic nuclear collisions at LHC energies is calculated using experimentally identified particle spectra and source radii estimated from Hanbury Brown-Twiss (HBT) correlations for particles π, k, p, Λ, Ω, and ∑ and π, k, p, Λ, and K^(0)_(s) at √s =2.76 and 5.02 TeV, respectively. An artificial neural network (ANN) simulation model is used to estimate the entropy per rapidity dS/dy at the considered energies. The simulation results are compared with equivalent experimental data, and a good agreement is achieved. A mathematical equation describing the experimental data is obtained. Extrapolation of the transverse momentum spectra at pT =0 is required to calculate dS/dy;thus, we use two different fitting functions, the Tsallis distribution and hadron resonance gas (HRG) model. The success of the ANN model in describing the experimental measurements leads to the prediction of several spectra values for the mentioned particles, which may lead to further predictions in the absence of experiments.
