利用多区域重模拟评估千禧年TNG星系形成模型的灵活性
Evaluating the flexibility of the MillenniumTNG galaxy formation model with multi-zoom re-simulations
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中文总结 AI 辅助
研究通过多区域重模拟评估千禧年TNG星系形成模型灵活性，用新方法降低计算成本，测量晕的GSMF和气体分数并训练模拟器，找到一组能较好拟合观测值的参数组合，显示该模型可与强反馈情景一致。
中文摘要 AI 辅助
在本研究中，我们开展了一项新的模拟活动，旨在了解控制宇宙流体动力学模拟中恒星形成和AGN反馈过程的参数如何影响诸如星系恒星质量函数（GSMF）和大型暗物质晕中气体分数等可观测量。这些模拟是对从千禧年TNG（MTNG）模拟中选取的晕进行放大，并采用一种新颖的多区域方法运行，该方法以高于背景的分辨率同时重新模拟给定大体积的几个子区域，从而降低计算成本和并行化中的不平衡。我们测量了每次重模拟中晕的GSMF和气体分数，并在这些量上训练高斯过程模拟器。所得模拟器预测晕中GSMF和气体分数分别具有约0.1 dex和约10%的精度。利用模拟器，我们可以同时拟合这两个量的最新测量值，特别是现在即使对于相对大质量的星系团也观察到的较低气体分数。有趣的是，我们找到了MTNG星系形成模型的一组参数组合，它对测量的GSMF和气体分数都提供了定性的良好拟合。这组参数与基准参数的不同主要在于要求恒星反馈的能量显著降低以及动力学AGN反馈事件的能量显著增加且更罕见。这一发现意味着MTNG模型可以与从星系群和星系团中去除大量气体的强反馈情景一致，尽管我们提醒，我们尚未广泛研究这些新参数对MTNG成功预测的许多量的影响。
英文摘要
In this study we introduce a new simulation campaign designed to understand how parameters that control star-formation and AGN feedback processes in cosmological hydrodynamical simulations impact observables such as the galaxy stellar-mass function (GSMF) and the gas fractions in large dark matter halos. These simulations are zoom-ins to halos selected from the MillenniumTNG (MTNG) simulation, and are run employing a novel multi-zoom approach which simultaneously re-simulates several sub-regions of a given large volume at a higher resolution than the background, thus reducing computational cost and imbalances in parallelization. We measure the GSMF and gas-fractions in halos for each of the re-simulations, and train Gaussian-process emulators on these quantities. The resulting emulators predict the GSMF and gas-fractions in halos with $\sim0.1\,\mathrm{dex}$ and $\sim 10\%$ precision respectively. Using the emulators we can simultaneously fit recent measurements of both quantities, in particular the lower gas fractions now observed even for comparatively massive clusters. Interestingly, we find a combination of parameters of the MTNG galaxy formation model that provides a qualitatively good fit to both the measured GSMF and gas fractions. This combination of parameters differs from the fiducial one mainly by requiring that stellar-feedback is significantly less energetic, and that kinetic AGN feedback events are significantly more energetic and rare. This finding implies that the MTNG model can be consistent with scenarios of strong feedback that remove large amounts of gas from groups and clusters, albeit we caution that we have not extensively examined the effect of these new parameters on many quantities for which MTNG made successful predictions.
