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nucl-th2026
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…
nucl-th2025
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…