Joint Bayesian analysis of soft and high-$p_{\perp }$ probes yields tighter constraints on QGP properties

Abstract

To extract bulk QGP properties, we perform a joint Bayesian calibration of bulk-medium parameters using low-$\text{pt}$ bulk and high-$\text{pt}$ tomography within a common medium evolution. Low-$\text{pt}$ observables are computed with \textsc{TRENTo}+\textsc{VISHNU}; temperature profiles are passed to \textsc{DREENA-A} to predict light/heavy $R_{\mathrm{AA}}(\text{pt})$ and $v_2(\text{pt})$. Gaussian-process emulation enables Hamiltonian Monte Carlo sampling of the low-$\text{pt}$-only and joint posteriors. The low-$\text{pt}$-only case underpredicts high-$\text{pt}$ anisotropy; the joint calibration matches both sectors and markedly tightens bulk-parameter constraints, demonstrating the added power of high-$\text{pt}$ data.

Comments: 5 pages, 5 figures