论文标题

用于弱透明跨相关性的流体动力学晕模型

A hydrodynamical halo model for weak-lensing cross correlations

论文作者

Mead, A. J., Tröster, T., Heymans, C., Van Waerbeke, L., McCarthy, I. G.

论文摘要

在银河光环的规模上,宇宙中物质的分布受到能量,非重力过程的影响。所谓的重型反馈。缺乏有关反馈过程如何重新分配物质的细节的知识,这是弱透明调查的不确定性来源,这些调查可以准确探测宇宙中物质在各种规模上的聚类。我们为物质分布开发了一个依赖宇宙学模型,该模型同时解释了暗物质,气体和恒星的聚类。我们通过将模型与从流体动力学模拟的巴哈马套件进行比较来告知我们的模型。除了考虑物质功率光谱外,我们还考虑了涉及电子压力场的光谱,该光谱与Thermal Sunyaev-Zel'Dovich(TSZ)效应直接相关。我们在模型中拟合参数,以便它可以同时对物质和压力数据进行建模,从而使TSZ推断的气体分布对我们模型预测的物质频谱的影响。我们提出两个变体。一个与在每百分比的物质 - 物质功率谱中看到的反馈诱导的抑制作用,而与物质 - 象征数据相匹配的第二个则略有匹配(约2%),但这可以同时在每百分比的〜15级上对物质电子压力谱进行建模。我们设想使用TSZ和镜头自动和互相关数据的组合,用于同时了解宇宙学参数和重型反馈的强度。

On the scale of galactic haloes, the distribution of matter in the cosmos is affected by energetic, non-gravitational processes; so-called baryonic feedback. A lack of knowledge about the details of how feedback processes redistribute matter is a source of uncertainty for weak-lensing surveys, which accurately probe the clustering of matter in the Universe over a wide range of scales. We develop a cosmology-dependent model for the matter distribution that simultaneously accounts for the clustering of dark matter, gas and stars. We inform our model by comparing it to power spectra measured from the BAHAMAS suite of hydrodynamical simulations. As well as considering matter power spectra, we also consider spectra involving the electron-pressure field, which directly relates to the thermal Sunyaev-Zel'dovich (tSZ) effect. We fit parameters in our model so that it can simultaneously model both matter and pressure data and such that the distribution of gas as inferred from tSZ has influence on the matter spectrum predicted by our model. We present two variants; one that matches the feedback-induced suppression seen in the matter-matter power spectrum at the per-cent level and a second that matches the matter-matter data slightly less well (~2 per cent), but that is able to simultaneously model the matter-electron pressure spectrum at the ~15 per-cent level. We envisage our models being used to simultaneously learn about cosmological parameters and the strength of baryonic feedback using a combination of tSZ and lensing auto- and cross-correlation data.

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