Application of the holographic equations of state for modeling experiments on heavy ion collisions

In this paper, we propose a method for numerical modeling of the nuclear matter properties within the framework of relativistic heavy-ion collisions using a holographic equation of state (EoS). Machine learning methods were applied to address the regression and optimization issues during the calibration of the relevant parameters using the LQCD results for quark masses that approximate the physical values. Numerical simulations are performed using the iEBE-MUSIC and vHLLE-SMASH frameworks, which incorporate certain relativistic hydrodynamics solvers. We modify the code by implementing a tabulated holographic EoS, enabling simulations of quark-gluon plasma evolution with dynamically generated initial conditions via the 3D Monte Carlo Glauber Model and SMASH. Finally, the spectra of produced hadrons are computed using a hybrid iSS+UrQMD and Hadron Sampler+SMASH approaches at the freeze-out stage.