The effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations
The effects of subgrid models on the properties of giant molecular clouds in galaxy formation simulations
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DOI：
10.1093/mnras/staa3122
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发表时间：
2020-01
影响因子：
4.8
通讯作者：
Hui Li;M. Vogelsberger;F. Marinacci;L. Sales;P. Torrey
中科院分区：
文献类型：
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作者：
Hui Li;M. Vogelsberger;F. Marinacci;L. Sales;P. Torrey
最近的宇宙流体动力学模拟能够再现星系的许多统计性质，这些性质与观测数据一致。然而，所采用的子网格模型对模拟结果影响很大，限制了这些模拟的预测能力。在这项工作中，我们在走私框架下进行了一套孤立的银河盘模拟，并研究了不同的亚格子模型如何影响巨型分子云(GMC)的性质。我们使用AsterDendro，一种层次化的簇发现算法来识别模拟中的GMC。我们发现，不同的亚格子恒星形成效率、ϵff和恒星反馈通道的选择，会产生非常不同的GMC群体的质量和空间分布。在没有反馈的情况下，GMC的质量函数具有较浅的幂函数斜率，并且与有反馈的运行相比扩展到更高的质量范围。此外，ϵff越高，分子气体消耗越快，质量函数斜率越大。反馈还抑制了GMC空间分布的两点相关函数(TPCF)中的功率。具体来说，辐射反馈强烈地降低了0.2kpc以下尺度上的TPCF，而超新星反馈则降低了0.2kpc以上尺度上的功率。最后，与低ϵff的运行相比，高ϵff的运行表现出更高的TPCF，这是因为稠密气体被更有效地耗尽，从而促进了结构良好的超新星气泡的形成。我们认为，比较模拟和观测到的GMC种群可以帮助在下一代星系形成模拟中更好地约束亚格子模型。
Recent cosmological hydrodynamical simulations are able to reproduce numerous statistical properties of galaxies that are consistent with observational data. Yet, the adopted subgrid models strongly affect the simulation outcomes, limiting the predictive power of these simulations. In this work, we perform a suite of isolated galactic disc simulations under the SMUGGLE framework and investigate how different subgrid models affect the properties of giant molecular clouds (GMCs). We employ astrodendro, a hierarchical clump-finding algorithm, to identify GMCs in the simulations. We find that different choices of subgrid star formation efficiency, ϵff, and stellar feedback channels, yield dramatically different mass and spatial distributions for the GMC populations. Without feedback, the mass function of GMCs has a shallower power-law slope and extends to higher mass ranges compared to runs with feedback. Moreover, higher ϵff results in faster molecular gas consumption and steeper mass function slopes. Feedback also suppresses power in the two-point correlation function (TPCF) of the spatial distribution of GMCs. Specifically, radiative feedback strongly reduces the TPCF on scales below 0.2 kpc, while supernova feedback reduces power on scales above 0.2 kpc. Finally, runs with higher ϵff exhibit a higher TPCF than runs with lower ϵff, because the dense gas is depleted more efficiently, thereby facilitating the formation of well-structured supernova bubbles. We argue that comparing simulated and observed GMC populations can help better constrain subgrid models in the next generation of galaxy formation simulations.