Study of jet-induced hydro response in high-energy heavy-ion collisions with a flow-matching generative model

Abstract

In high-energy heavy-ion collisions, propagation of the energy deposited into the medium by energetic partons that traverse the quark-gluon plasma (QGP) leads to Mach-cone-like jet-induced medium response. Event-by-event simulations of jet-induced medium responses within a complete model such as the coupled Linear Boltzmann Transport and hydrodynamic (CoLBT-hydro) model are very resource-intensive. In this study, we develop a flow matching generative model trained by CoLBT-hydro events for the study of the medium response induced by $γ$-jets in high-energy heavy-ion collisions. With only the initial spatial and momentum information of the $γ$ and jets, the generative model is shown to conditionally reproduce the marginal final-state hadron spectra from the jet-induced hydro response in $0-10\%$ Pb+Pb collisions at $\sqrt{s_{\rm{NN}}}$ = 5.02~TeV. The generative model achieves a computational acceleration of approximately six orders of magnitude compared to the full CoLBT-hydro simulations, while faithfully preserving the statistical properties of the front and the diffusion wake of the Mach-cone-like hydro response and their contributions to the hadron spectra. Hadron spectra from the medium response, correlations between the front and diffusion wake and rapidity asymmetry due to the diffusion wake in $γ$-hadron correlation are further studied within the generative model.