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arXiv 1209.0565astro-ph.COastro-ph.HEphysics.data-anstat.AP
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团内介质的富集历史:贝叶斯方法

The enrichment history of the intracluster medium: a Bayesian approach

S. Andreon

摘要:

本文通过对130个星系团在0.1<z<1.3时的数据进行严格分析,测量了星系团中铁含量的演化。由于a)丰度测量的低信噪比和上限,b)可能的选择效应,c)参数空间的边界,d)非高斯误差,e)研究对象的内在多样性,以及f)丰度系统学,使得这项任务变得困难。我们引入贝叶斯模型来同时解决所有这些问题,从而允许串扰(协方差)。在模拟数据上,贝叶斯拟合恢复了输入富集历史,这与标准分析不同。在考虑了可能依赖于X射线温度、金属丰度系统学和研究对象的内在多样性之后,我们发现,无论是在高红移还是低红移,都没有达到现今的金属含量,而是随着时间的推移逐渐增加:在数据采样的7 Gyr中,铁丰度增加了1.5倍。因此,金属丰度的反馈不会在高红移处结束。进化是建立在中等数量的证据,19比1的赔率对更快或更慢的金属富集的历史。我们第一次量化了金属丰度的内在分布,18+/-3%,在校正了演化,X射线温度和金属丰度系统学的影响之后。最后,我们还提出了一个解析近似的X射线温度和金属丰度的似然函数,这是有用的其他回归拟合涉及这些参数。文中提供了130个聚类的数据和随机计算的代码。

英文摘要:

This work measures the evolution of the iron content in galaxy clusters by a rigorous analysis of the data of 130 clusters at 0.1<z<1.3. This task is made difficult by a) the low signal-to-noise ratio of abundance measurements and the upper limits, b) possible selection effects, c) boundaries in the parameter space, d) non-Gaussian errors, e) the intrinsic variety of the objects studied, and f) abundance systematics. We introduce a Bayesian model to address all these issues at the same time, thus allowing cross-talk (covariance). On simulated data, the Bayesian fit recovers the input enrichment history, unlike in standard analysis. After accounting for a possible dependence on X-ray temperature, for metal abundance systematics, and for the intrinsic variety of studied objects, we found that the present-day metal content is not reached either at high or at low redshifts, but gradually over time: iron abundance increases by a factor 1.5 in the 7 Gyr sampled by the data. Therefore, feedback in metal abundance does not end at high redshift. Evolution is established with a moderate amount of evidence, 19 to 1 odds against faster or slower metal enrichment histories. We quantify, for the first time, the intrinsic spread in metal abundance, 18+/-3 %, after correcting for the effect of evolution, X-ray temperature, and metal abundance systematics. Finally, we also present an analytic approximation of the X-ray temperature and metal abundance likelihood functions, which are useful for other regression fitting involving these parameters. The data for the 130 clusters and code used for the stochastic computation are provided with the paper.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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