Diffusion-Based Point-Cloud Generation of Heavy-Ion Events
This paper presents a fast, high-fidelity generative model based on score-driven diffusion and the Point-Edge Transformer architecture that successfully simulates realistic, high-multiplicity heavy-ion collision events through a two-stage training strategy, demonstrating its potential to replace computationally intensive traditional simulations.