Modelling of ionising feedback with Smoothed Particle Hydrodynamics and Monte Carlo Radiative Transfer on a Voronoi grid

TL;DR

This paper introduces a novel radiation-hydrodynamics scheme combining SPH and Monte Carlo radiative transfer on a Voronoi grid, enabling realistic simulations of ionising feedback in star-forming regions.

Contribution

The authors develop and validate a new RHD method integrating SPH with Monte Carlo radiative transfer on a Voronoi grid, suitable for complex star formation simulations.

Findings

Successfully reproduces D-type H II region expansion.

Shows robustness of the scheme with different grid and resolution choices.

Estimates ionised material in a star-forming cloud similar to the Galactic Center.

Abstract

The ionising feedback of young massive stars is well known to influence the dynamics of the birth environment and hence plays an important role in regulating the star formation process in molecular clouds. For this reason, modern hydrodynamics codes adopt a variety of techniques accounting for these radiative effects. A key problem hampering these efforts is that the hydrodynamics are often solved using smoothed particle hydrodynamics (SPH), whereas radiative transfer is typically solved on a grid. Here we present a radiation-hydrodynamics (RHD) scheme combining the SPH code Phantom and the Monte Carlo Radiative Transfer (MCRT) code CMacIonize, using the particle distribution to construct a Voronoi grid on which the MCRT is performed. We demonstrate that the scheme successfully reproduces the well-studied problem of D-type H II region expansion in a uniform density medium. Furthermore, we use this simulation setup to study the robustness of the RHD code with varying choice of grid structure, density mapping method, and mass and temporal resolution. To test the scheme under more realistic conditions, we apply it to a simulated star-forming cloud reminiscing those in the Central Molecular Zone of our galaxy, in order to estimate the amount of ionised material that a single source could create. We find that a stellar population of several $10^3~\rm{M_{\odot}}$ is needed to noticeably ionise the cloud. Based on our results, we formulate a set of recommendations to guide the numerical setup of future and more complex simulations of star forming clouds.