Machine learning has been widely applied in physics research. Although unsupervised learning can extract the critical points of phase transitions, the percolation model remains a challenge. Unsupervised learning using the raw configurations of the percolation model fails to capture the critical points. To capture the configuration characteristics of the percolation model, this paper proposes...
The QCD critical point is suggested to be in the same universality class as the 3D Ising model, which implies that the behavior of thermodynamic observables near the QCD critical point can be described by the critical exponents and scaling laws of the Ising model. The percolation study offers valuable insights into the characteristics of phase transition, revealing the underlying mechanisms...
