arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2001.11508astro-ph.CO
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利用Mock-X表征静水质量偏差

Characterizing hydrostatic mass bias with Mock-X

David J. Barnes, Mark Vogelsberger, Francesca A. Pearce, Ana-Roxana Pop, Rahul Kannan, Kaili Cao, Scott T. Kay, Lars Hernquist

AI总结:

利用Mock-X框架研究星系团静水质量偏差,发现其质量依赖性,偏差随团簇质量增加而增大。

摘要:

未来十年的调查将提供大量星系团样本,从而改变我们对它们形成过程的理解。星系团天文学和宇宙学研究将受到大规模样本的限制。已知的性质下,流体动力学模拟为研究潜在系统误差提供了重要资源。然而,只有在正确的方式下将模拟与观测进行比较,才能实现这一点。在这里,我们介绍了Mock-X分析框架,这是一种多波长工具,能够从宇宙学模拟中生成合成图像,并通过观测方法推导暗物质晕属性。我们详细说明了生成光学、Compton-y和X射线图像的方法。概述了我们的合成X射线图像分析方法,通过探索IllustrisTNG、BAHAMAS和MACSIS模拟的静水质量偏差来展示该框架的能力。使用模拟导出的剖面,我们发现质量偏差约为0.13,与团簇质量无关,也不受流体动力学方法或子格物理的影响。然而,从合成观测中得出的静水偏差是质量依赖性的,对于最重的团簇,偏差增加到0.3。这一结果是由对由气体在准压力平衡下产生宽温度分布的光谱进行单温度拟合驱动的。由于较冷的气体主导发射,光谱学温度和质量估计被低估,这归因于其二次密度依赖性。偏差和质量估计的散射与数值方法和子格物理无关。我们的结果与当前观测一致,未来调查将包含足够数量的重团簇样本,以确认静水偏差的质量依赖性。

英文摘要:

Surveys in the next decade will deliver large samples of galaxy clusters that transform our understanding of their formation. Cluster astrophysics and cosmology studies will become systematics limited with samples of this magnitude. With known properties, hydrodynamical simulations of clusters provide a vital resource for investigating potential systematics. However, this is only realized if we compare simulations to observations in the correct way. Here we introduce the \textsc{Mock-X} analysis framework, a multiwavelength tool that generates synthetic images from cosmological simulations and derives halo properties via observational methods. We detail our methods for generating optical, Compton-$y$ and X-ray images. Outlining our synthetic X-ray image analysis method, we demonstrate the capabilities of the framework by exploring hydrostatic mass bias for the IllustrisTNG, BAHAMAS and MACSIS simulations. Using simulation derived profiles we find an approximately constant bias $b\approx0.13$ with cluster mass, independent of hydrodynamical method or subgrid physics. However, the hydrostatic bias derived from synthetic observations is mass-dependent, increasing to $b=0.3$ for the most massive clusters. This result is driven by a single temperature fit to a spectrum produced by gas with a wide temperature distribution in quasi-pressure equilibrium. The spectroscopic temperature and mass estimate are biased low by cooler gas dominating the emission, due to its quadratic density dependence. The bias and the scatter in estimated mass remain independent of the numerical method and subgrid physics. Our results are consistent with current observations and future surveys will contain sufficient samples of massive clusters to confirm the mass dependence of the hydrostatic bias.

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