论文标题

探索音乐簇中的静水质量偏见:应用于NIKA2模拟样本

Exploring the hydrostatic mass bias in MUSIC clusters: application to the NIKA2 mock sample

论文作者

Gianfagna, Giulia, De Petris, Marco, Yepes, Gustavo, De Luca, Federico, Sembolini, Federico, Cui, Weiguang, Biffi, Veronica, Kéruzoré, Florian, Macías-Pérez, Juan, Mayet, Frédéric, Perotto, Laurence, Rasia, Elena, Ruppin, Florian

论文摘要

星系簇是限制宇宙参数的有用工具,只有从观察值中正确推断出它们的质量。特别是,可以使用X射线和Sunyaev-Zeldovich(SZ)效应观测值在静水平衡的框架内得出质量。因此,至关重要的是,在该假设无效时,可以很好地控制可能引入的质量偏见。在这项工作中,我们分析了音乐模拟项目中的一组260个合成簇,RedShifts $ 0 \ leq Z \ leq 0.82 $。我们从仅X射线(温度和密度)以及X射线和SZ(密度和压力)估计音乐簇的静水质量。然后,我们将它们与真实的3D动态质量进行比较。偏见为20%。我们发现,使用温度而不是压力会导致较小的偏差,尽管两个值在1 $σ$之内兼容。还计算出对气体的批量运动和湍流引起的总压力支持的非热贡献,并表明它们足以说明这一偏见。我们还介绍了质量偏差与集群动力状态之间的相关性的研究。在簇的松弛状态与偏置因子之间显示了明显的相关性。我们在32个对象的子样本上应用了相同的分析,该对象已选择用于支持Nika2 SZ大程序。

Clusters of galaxies are useful tools to constrain cosmological parameters, only if their masses can be correctly inferred from observations. In particular, X-ray and Sunyaev-Zeldovich (SZ) effect observations can be used to derive masses within the framework of the hydrostatic equilibrium. Therefore, it is crucial to have a good control of the possible mass biases that can be introduced when this hypothesis is not valid. In this work, we analyzed a set of 260 synthetic clusters from the MUSIC simulation project, at redshifts $0 \leq z \leq 0.82$. We estimate the hydrostatic mass of the MUSIC clusters from X-ray only (temperature and density) and from X-ray and SZ (density and pressure). Then, we compare them with the true 3D dynamical mass. The biases are of the order of 20%. We find that using the temperature instead of the pressure leads to a smaller bias, although the two values are compatible within 1$σ$. Non-thermal contributions to the total pressure support, arising from bulk motion and turbulence of the gas, are also computed and show that they are sufficient to account for this bias. We also present a study of the correlation between the mass bias and the dynamical state of the clusters. A clear correlation is shown between the relaxation state of the clusters and the bias factor. We applied the same analysis on a subsample of 32 objects, already selected for supporting the NIKA2 SZ Large Program.

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