2021/07/31 by Y. Huang, Yige Huang, Long-Gang Pang +3
Mathematics · Physics and Astronomy · #Cloud computing #Computer science #Critical point (mathematics) #Criticality #Geometry #Heavy ion #High-Energy Particle Collisions Research #Ion #Ising model #Mathematics #Nuclear physics #Particle physics theoretical and experimental studies #Physics #Quantum Chromodynamics and Particle Interactions #Quantum mechanics #Statistical physics #Universality (dynamical systems) #hep-ex #hep-ph #nucl-ex #nucl-th
paper · pdf · doi:10.1016/j.physletb.2022.137001
published as Physics Letters B 827, 137001 (2022) · 10 pages, 5 figures, version accepted by Physics Letters B
arxiv created 2022/03/02 · openalex publication_date 2022/03/02 · arxiv updated 2022/03/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
Systems with different interactions could develop the same critical behaviour due to the underlying symmetry and universality. Using this principle of universality, we can embed critical correlations modeled on the 3D Ising model into the simulated data of heavy-ion collisions, hiding weak signals of a few inter-particle correlations within a large particle cloud. Employing a point cloud network with dynamical edge convolution, we are able to identify events with critical fluctuations through supervised learning, and pick out a large fraction of signal particles used for decision-making in each single event.