Quark Matter 2025

Nuclear equation of state at finite μB using deep learning assisted quasi parton model

Not scheduled

20m

Goethe University Frankfurt, Campus Westend, Theodor-W.-Adorno-Platz 1, 60629 Frankfurt am Main, Germany

Poster QCD phase diagram & critical point Poster session 1

Speaker

Dr Fu-Peng Li (Central China Normal University)

Description

The equation of state (EoS) at finite baryon chemical potential remains an elusive target for direct lattice QCD calculations, constituting a highly challenging topic. To address this issue, we have developed a novel Deep-learning quasi-parton model, which is constructed using three deep neural networks, to capture the fundamental properties of hot and dense QCD matter. Each neural network represents three distinct quasi-particle masses that are contingent upon the temperature (T) and baryon chemical potential (${\mu }_B$). The resulting EoS derived from the quasi-particle model demonstrates strong agreement with lattice QCD results using Taylor expansion techniques. This provides a robust framework for approximating the EoS of QCD matter at finite baryon chemical potentials, thereby enhancing our theoretical understanding of QCD matter under extreme conditions.

Presentation materials

QM_poster.pdf