[Paper Review] 3D radiative hydrodynamic simulations of protostellar collapse with H-C-O dynamical chemistry

Natalia Dzyurkevich, B. Commerçon+2 more|arXiv (Cornell University)|May 25, 2016

Astrophysics and Star Formation Studies3 citations

TL;DR

This study presents the first 3D radiative hydrodynamic simulations of protostellar collapse with full dynamical H-C-O chemistry, coupling radiative transfer, gas-grain chemistry, and hydrodynamics. It demonstrates that dynamical chemistry is essential for accurate CO gas-phase abundance and ice formation, especially for dust grains larger than 1 µm, and shows that dust size and distribution strongly affect ionization and magnetic dissipation.

ABSTRACT

Combining the co-evolving chemistry, hydrodynamics and radiative transfer is an important step for star formation studies. It allows both a better link to observations and a self-consistent monitoring of the magnetic dissipation in the collapsing core. Our aim is to follow a chemo-dynamical evolution of collapsing dense cores with a reduced gas-grain chemical network. We present the results of radiative hydrodynamic (RHD) simulations of 1 M$_\odot$ isolated dense core collapse. The physical setup includes RHD and dynamical evolution of a chemical network. To perform those simulations, we merged the multi-dimensional adaptive-mesh-refinement code RAMSES and the thermo-chemistry Paris-Durham shock code. We simulate the formation of the first hydro-static core (FHSC) and the co-evolution of 56 species describing mainly H-C-O chemistry. Accurate benchmarking is performed, testing the reduced chemical network against a well-establiched complex network. We show that by using a compact set of reactions, one can match closely the CO abundances with results of a much more complex network. Our main results are: (a) We find that gas-grain chemistry post-processing can lead to one order of magnitude lower CO gas-phase abundances compared to the dynamical chemistry, with strongest effect during the isothermal phase of collapse. (b) The free-fall time has little effect on the chemical abundances for our choice of the parameters. (c) Dynamical chemical evolution is required to describe the CO gas phase abundance as well as the CO ice formation for the mean grain size larger then 1$μ$m. (d) Furthermore, dust mean size and size distribution have a strong effect on chemical abundances and hence on the ionization degree and magnetic dissipation. We conclude that dust grain growth in the collapse simulations can be as important as coupling the collapse with chemistry.

Motivation & Objective

• To model the chemo-dynamical evolution of protostellar collapse with self-consistent radiative hydrodynamics and gas-grain chemistry.
• To assess the impact of free-fall time and dust properties on chemical abundances during core collapse.
• To evaluate the necessity of dynamical chemistry versus post-processing static chemistry for accurate CO and ice abundances.
• To quantify how dust grain size and size distribution affect ionization degree and magnetic dissipation in collapsing cores.
• To establish a computationally feasible reduced H-C-O chemical network that matches complex networks while enabling 3D simulations.

Proposed method

• Coupled the RAMSES adaptive-mesh-refinement hydrodynamics code with the PDS thermo-chemistry code for 3D radiative hydrodynamics and dynamical chemistry.
• Simulated 1 M⊙ isolated dense core collapse with 56 species, focusing on H-C-O chemistry to reduce computational cost.
• Used a reduced chemical network validated against a full gas-grain network to ensure accuracy while enabling 3D simulations.
• Tracked the formation of the first hydrostatic core up to central densities of ~10^13 cm⁻³ and temperatures of ~800 K.
• Performed post-processing with an extended static chemistry network on the final dynamical structure to assess differences in CO abundances.
• Varied free-fall time and dust grain size (0.02–0.1 µm) to study their effects on molecular depletion and ionization.

Experimental results

Research questions

• RQ1 How does the duration of the free-fall phase (i.e. free-fall time) affect the chemical abundances in collapsing cores?
• RQ2 To what extent does dynamical chemistry differ from post-processing static chemistry in predicting CO gas-phase abundances?
• RQ3 How do dust grain size and size distribution influence molecular depletion and ionization in protostellar cores?
• RQ4 What is the impact of dust grain growth on the accuracy of magnetic diffusivity estimates in collapsing cores?
• RQ5 Can a reduced H-C-O chemical network accurately reproduce the results of a full gas-grain network in 3D chemo-dynamical simulations?

Key findings

• The reduced H-C-O chemical network provides a good match to a full network, enabling computationally feasible 3D chemo-dynamical simulations.
• Post-processing with static chemistry leads to CO gas-phase abundances that are up to an order of magnitude lower than those from dynamical chemistry, especially during the isothermal collapse phase.
• Free-fall time has little effect on chemical abundances for the chosen parameters, indicating that dynamical timescales dominate over chemical evolution timescales.
• For dust grains larger than 1 µm, gas-dust interaction timescales exceed dynamical timescales, making dynamical chemistry essential for accurate molecular depletion.
• Varying dust grain size from 0.02 to 0.1 µm changes CO and H₂O gas-phase abundances by up to two orders of magnitude, highlighting the critical role of dust size.
• Dust grain size and size distribution strongly influence ionization degree and magnetic dissipation, making them as important as chemistry coupling in collapse simulations.