MAHGIC: a Model Adapter for the Halo-Galaxy Inter-Connection
MAHGIC: a Model Adapter for the Halo-Galaxy Inter-Connection
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MAHGIC：Halo-Galaxy 互连的模型适配器
DOI：
10.1093/mnras/stab2377
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发表时间：
2021
影响因子：
4.8
通讯作者：
Katz Neal
中科院分区：
文献类型：
--
作者：
Chen Yangyao;Mo H. J.;Li Cheng;Wang Kai;Wang Huiyuan;Yang Xiaohu;Zhang Youcai;Katz Neal
我们开发了一个模型来建立星系和它们的暗物质晕之间的相互联系。我们使用主成分分析(PCA)对晕/次晕的质量集合历史和星系的恒星形成历史进行降维，并使用梯度增强决策树(GBDT)将晕/次晕的属性转换为星系的属性。我们使用两组流体动力学模拟来激励我们的模型体系结构并训练转换。然后，我们将这两组训练好的模型应用于纯暗物质(DMO)模拟，以表明变换是可靠的，并且在统计上是准确的。因此，由高分辨率流体动力学模拟训练的模型，或由一组实现相同星系形成物理的此类模拟训练的模型，可以应用于大型DMO模拟，以制作流体动力学模拟的模拟副本。该模型既灵活又可解释，这为未来的应用铺平了道路，在这些应用中，我们将同时使用不同红移的观测来约束该模型，并从经验上探索星系如何在暗物质晕中形成和演化。
We develop a model to establish the interconnection between galaxies and their dark matter haloes. We use Principal Component Analysis (PCA) to reduce the dimensionality of both the mass assembly histories of haloes/subhaloes and the star formation histories of galaxies, and Gradient Boosted Decision Trees (GBDT) to transform halo/subhalo properties into galaxy properties. We use two sets of hydrodynamic simulations to motivate our model architecture and to train the transformation. We then apply the two sets of trained models to dark-matter-only (DMO) simulations to show that the transformation is reliable and statistically accurate. The model trained by a high-resolution hydrodynamic simulation, or by a set of such simulations implementing the same physics of galaxy formation, can thus be applied to large DMO simulations to make ‘mock’ copies of the hydrodynamic simulation. The model is both flexible and interpretable, which paves the way for future applications in which we will constrain the model using observations at different redshifts simultaneously and explore how galaxies form and evolve in dark matter haloes empirically.