A flow-matching generative model trained on CoLBT-hydro data conditionally generates marginal final-state hadron spectra from jet-induced hydro responses in 0-10% Pb+Pb collisions at 5.02 TeV, matching training data statistics with approximately six orders of magnitude computational speedup.
Energy and momentum deposited into a QCD medium by a jet shower
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
Hard partons moving through a dense QCD medium lose energy by radiative emissions and elastic scatterings. Deposition of the radiative contribution into the medium requires rescattering of the radiated gluons. We compute the total energy loss and its deposition into the medium self-consistently within the same formalism, assuming perturbative interaction between probe and medium. The same transport coefficients that control energy loss of the hard parton determine how the energy is deposited into the medium; this allows a parameter free calculation of the latter once the former have been computed or extracted from experimental energy loss data. We compute them for a perturbative medium in hard thermal loop (HTL) approximation. Assuming that the deposited energy-momentum is equilibrated after a short relaxation time, we compute the medium's hydrodynamical response and obtain a conical pattern that is strongly enhanced by showering.
fields
nucl-th 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
A flow-matching generative model for event-by-event jet-induced hydro response in high-energy heavy-ion collisions
A flow-matching generative model trained on CoLBT-hydro data conditionally generates marginal final-state hadron spectra from jet-induced hydro responses in 0-10% Pb+Pb collisions at 5.02 TeV, matching training data statistics with approximately six orders of magnitude computational speedup.