Speaker
Description
At the beginning of the 21st century, a new phase of strongly interacting matter, known as the quark-gluon plasma (QGP), was established [1]. To study QGP formation in heavy-ion collisions, the solution of system of relativistic hydrodynamics equations with a specific equation of state (EoS) is typically employed. In light of difficulties for non-zero baryonic potentials within Lattice QCD, various holographic models based on the AdS/CFT duality have been proposed to obtain the QGP EoS from the thermodynamic properties of a corresponding black brane in AdS$_5$ [2].
In this work, we discuss possible phenomenological approaches for incorporating not only the baryon chemical potential but also the strangeness potential into holographic thermodynamics. The first method uses the established concept of a free quark gas with a specific symmetry generalization [3]. The second method employs a phenomenological hypothesis inspired by the thermodynamic dependencies of the hadron gas model [4]. We apply machine learning methods to address regression and optimization problems during the calibration of the model's free parameters using LQCD results for quark masses that approximate the physical values [5]. For practical applications in heavy-ion collision studies, the holographic EoS with strangeness is incorporated into the hydrodynamical packages MUSIC [6] and vHLLE [7].
To obtain final hadronic spectra, numerical simulations were conducted using the iEBE-MUSIC and SMASH-vHLLE frameworks; these additionally include packages for initial conditions, freeze-out, and a hadronic afterburner. The effect of the strangeness enabled EoS on the results is discussed.
The authors acknowledge Saint-Petersburg State University for a research project 103821868.
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