3 papers
hep-ph2026
Extracting Transport Properties of Quark-Gluon Plasma from the Heavy-Quark Potential With Neural Networks in a Holographic Model
Wen-Chao Dai, Ou-Yang Luo, Bing Chen +3
Using Kolmogorov-Arnold Networks (KANs), we construct a holographic model informed by lattice QCD data. This neural network approach enables the derivation of an analytical solutio…
hep-ph2025
Thermodynamics of Heavy Quarkonium in a Bayesian Holographic QCD model
Liqiang Zhu, Ou-Yang Luo, Xun Chen +3
Leveraging high-precision lattice QCD data on the equation of state and baryon number susceptibility at vanishing chemical potential, we construct a Bayesian holographic QCD model…
hep-ph2024
Neural Network Modeling of Heavy-Quark Potential from Holography
Ou-Yang Luo, Xun Chen, Fu-Peng Li +2
Using Multi-Layer Perceptrons (MLP) and Kolmogorov-Arnold Networks (KAN), we construct a holographic model based on lattice QCD data for the heavy-quark potential in the 2+1 system…