Particle production in relativistic heavy-ion collisions: A consistent hydrodynamic approach
Rajeev S. Bhalerao, Amaresh Jaiswal, Subrata Pal, and V. Sreekanth

TL;DR
This paper develops a consistent relativistic viscous hydrodynamic framework for heavy-ion collisions, highlighting the importance of using the same non-equilibrium distribution in both evolution equations and particle production calculations.
Contribution
It derives viscous hydrodynamic equations from thermodynamics and demonstrates the impact of distribution function choices on particle production rates in heavy-ion collisions.
Findings
Relaxation times are identical for shear viscosity but differ for bulk viscosity.
Different non-equilibrium distribution functions lead to significant variations in particle production.
Inconsistent treatment of non-equilibrium effects can bias the extraction of quark-gluon plasma properties.
Abstract
We derive relativistic viscous hydrodynamic equations invoking the generalized second law of thermodynamics for two different forms of the non-equilibrium single-particle distribution function. We find that the relaxation times in these two derivations are identical for shear viscosity but different for bulk viscosity. These equations are used to study thermal dilepton and hadron spectra within longitudinal scaling expansion of the matter formed in relativistic heavy-ion collisions. For consistency, the same non-equilibrium distribution function is used in the particle production prescription as in the derivation of the viscous evolution equations. Appreciable differences are found in the particle production rates corresponding to the two non-equilibrium distribution functions. We emphasize that an inconsistent treatment of the non-equilibrium effects influences the particle production…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
