Maximum entropy kinetic matching conditions for heavy-ion collisions

TL;DR

This paper introduces a new particlization method for heavy-ion collision modeling that relies solely on macroscopic hydrodynamic data, avoiding assumptions about microscopic degrees of freedom.

Contribution

It proposes an entropy-based kinetic matching approach that directly links fluid dynamics output to particle distributions without additional microscopic assumptions.

Findings

Provides a consistent way to couple hydrodynamics to kinetic models

Reduces reliance on microscopic assumptions in particlization

Enhances the theoretical foundation of heavy-ion collision simulations

Abstract

Coupling hadronic kinetic theory models to fluid dynamics in phenomenological studies of heavy ion collisions requires a prescription for ``particlization''. Existing particlization models are based on implicit or explicit assumptions about the microscopic degrees of freedom that go beyond the information provided by the preceding fluid dynamical history. We propose an alternative prescription which uses only macroscopic information provided by the hydrodynamic output. This method follows directly from the connections between information theory and statistical mechanics.