[论文解读] 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 Studies被引用 3

一句话总结

本研究首次实现了包含完整动态H-C-O化学过程的原恒星坍缩三维辐射流体动力学模拟，耦合了辐射转移、气-尘化学与流体动力学。结果表明，动态化学对准确预测CO气相丰度和冰形成至关重要，尤其在尘埃颗粒直径大于1 µm时；同时发现尘埃尺寸与分布显著影响电离度与磁能耗散。

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.

研究动机与目标

• 模拟原恒星坍缩的化学-动力学演化过程，采用自洽的辐射流体动力学与气-尘化学模型。
• 评估自由下落时间与尘埃特性对核心坍缩期间化学丰度的影响。
• 评估动态化学相对于后处理静态化学在准确预测CO与冰丰度方面的必要性。
• 量化尘埃颗粒尺寸与粒径分布对坍缩核心中电离度与磁能耗散的影响。
• 建立计算上可行的简化H-C-O化学网络，使其在保持与复杂网络一致的同时，支持三维模拟。

提出的方法

• 将RAMSES自适应网格加密流体动力学代码与PDS热化学代码耦合，实现三维辐射流体动力学与动态化学模拟。
• 对1 M⊙孤立致密核心坍缩进行模拟，包含56种物种，聚焦H-C-O化学以降低计算成本。
• 采用经验证的简化化学网络，确保精度的同时支持三维模拟。
• 追踪首个准静态核心的形成过程，直至中心密度达到约10^13 cm⁻³，温度达约800 K。
• 对最终的动力学结构进行后处理，采用扩展的静态化学网络，评估CO丰度的差异。
• 改变自由下落时间与尘埃颗粒尺寸（0.02–0.1 µm），研究其对分子耗竭与电离的影响。

实验结果

研究问题

• RQ1 自由下落阶段的持续时间（即自由下落时间）如何影响坍缩核心中的化学丰度？
• RQ2 动态化学与后处理静态化学在预测CO气相丰度方面有多大差异？
• RQ3 尘埃颗粒尺寸与粒径分布在原恒星核心中如何影响分子耗竭与电离？
• RQ4 尘埃颗粒生长对坍缩核心中磁扩散系数估算的准确性有何影响？
• RQ5 简化H-C-O化学网络能否在三维化学-动力学模拟中准确再现完整气-尘网络的结果？

主要发现

• 简化H-C-O化学网络与完整网络结果高度一致，使计算上可行的三维化学-动力学模拟成为可能。
• 后处理静态化学导致的CO气相丰度比动态化学低至一个数量级，尤其在等温坍缩阶段更为显著。
• 在所选参数下，自由下落时间对化学丰度影响甚微，表明动力学时序主导于化学演化时序。
• 当尘埃颗粒直径大于1 µm时，气-尘相互作用时间尺度超过动力学时间尺度，因此动态化学对准确预测分子耗竭至关重要。
• 尘埃颗粒尺寸从0.02 µm增至0.1 µm，可使CO与H₂O气相丰度变化达两个数量级，凸显尘埃尺寸的关键作用。
• 尘埃颗粒尺寸与粒径分布显著影响电离度与磁能耗散，其重要性与化学耦合相当，是坍缩模拟中的关键因素。