Cosmological Radiative Transfer Comparison Project II: The Radiation-Hydrodynamic Tests

TL;DR

This paper compares nine radiation hydrodynamics codes on three astrophysical problems, demonstrating broad agreement but also highlighting differences and the need for careful, problem-specific testing of numerical methods.

Contribution

It provides a direct comparison of nine coupled radiation-hydrodynamics codes on key astrophysical tests, assessing their robustness and identifying areas for improvement.

Findings

Broad agreement among codes on test problems

No major failures observed in the methods

All codes showed some shortcomings and differences

Abstract

The development of radiation hydrodynamical methods that are able to follow gas dynamics and radiative transfer self-consistently is key to the solution of many problems in numerical astrophysics. Such fluid flows are highly complex, rarely allowing even for approximate analytical solutions against which numerical codes can be tested. An alternative validation procedure is to compare different methods against each other on common problems, in order to assess the robustness of the results and establish a range of validity for the methods. Previously, we presented such a comparison for a set of pure radiative transfer tests (i.e. for fixed, non-evolving density fields). This is the second paper of the Cosmological Radiative Transfer (RT) Comparison Project, in which we compare 9 independent RT codes directly coupled to gasdynamics on 3 relatively simple astrophysical hydrodynamics problems: (5) the expansion of an H II region in a uniform medium; (6) an ionization front (I-front) in a 1/r^2 density profile with a flat core, and (7), the photoevaporation of a uniform dense clump. Results show a broad agreement between the different methods and no big failures, indicating that the participating codes have reached a certain level of maturity and reliability. However, many details still do differ, and virtually every code has showed some shortcomings and has disagreed, in one respect or another, with the majority of the results. This underscores the fact that no method is universal and all require careful testing of the particular features which are most relevant to the specific problem at hand.