Joint reconstruction of the mass distributions of galaxyclusters from gravitational lensing and thermal gas
Joint reconstruction of the mass distributions of galaxyclusters from gravitational lensing and thermal gas
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DOI：
10.11588/heidok.00017156
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发表时间：
2014
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影响因子：
--
通讯作者：
Charles L. Majer
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文献类型：
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作者：
Charles L. Majer
我们专注于重建大质量星系团的质量分布，这是宇宙中最大的引力约束对象。一种确定星系团质量的方法是基于引力透镜效应。估计由这种方法引起的误差是至关重要的，但计算昂贵。我们提出了一种新的方法来估计分析重建使用弱透镜信息的错误。由于星系团拥有大量的团内介质，它们提供了大量的观测数据。我们提出了一种新的方法来推断从其中两个：热Sunyaev-Zel'dovich效应的信号和由于热韧致辐射的X射线的发射的透镜潜力。通过假设气体处于流体静力平衡并遵循多方状态方程，我们将这些观测量与引力势联系起来，然后将引力势沿着视线投影，以推断透镜势。为此，我们通过Richardson-Lucy算法对可观测量进行去投影。我们测试我们的方法与分析配置文件，数值模拟和星系团RXJ 1347上的集群。我们的努力是第一步走向联合集群重建的非参数算法。通过考虑所有可能的星系团观测量，可以更精确地确定星系团的质量分布。
We focus on the reconstruction of mass distributions of the massive galaxy clusters, which are the largest gravitationally bound objects in the Universe. An approach to determine the masses of clusters is based on the effects of gravitational lensing. Estimating errors induced by this method is crucial but computationally expensive. We present a novel approach to estimate analytically the errors made by reconstructions which use weak-lensing information. As galaxy clusters host a large amount of intracluster medium they provide a multitude of observables. We present a new method to infer the lensing potential from two of these: signals of the thermal Sunyaev-Zel’dovich effect and the emission of X-rays due to thermal bremsstrahlung. By assuming that the gas is in hydrostatic equilibrium and follows a polytropic equation of state, we link these observables to the gravitational potential, which is then projected along the line-of-sight to infer the lensing potential. For this we deproject the observables by means of the Richardson-Lucy algorithm. We test our method on clusters with analytic profiles, a numerical simulation and on the galaxy cluster RXJ1347. Our efforts are the first steps towards a non-parametric algorithm for a joint cluster reconstruction. By taking all possible cluster observables into account, mass distributions of clusters will be determined more accurately.