Novel approach generates data for heavy-ion collisions, suggesting potential in theoretical studies and applications.
A novel point-cloud diffusion model for relativistic heavy-ion collisions, capable of ultrafast generation of complete, event-by-event collision output, is introduced. When trained on ultrarelativistic quantum molecular dynamics cascade simulations, the model generates realistic collision event output containing 26 distinct hadron species, as a list of particle momentum vectors along with their particle ID. From solving inverse problems to accelerating model calculations or detector simulations, the model can be a promising general-purpose tool for heavy-ion collisions beneficial to both theoretical studies and experimental applications.
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Kuttan et al. (2025) studied this question.
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