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arXiv 0802.0004astro-ph
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基于粒子透镜的团簇质量重构I:弱透镜的应用

Reconstruction of Cluster Masses using Particle Based Lensing I: Application to Weak Lensing

Sanghamitra Deb, David M. Goldberg, Vede J. Ramdass

摘要:

提出了一种新的引力透镜技术-粒子透镜(PBL)技术,用于星系团的质量重建。传统上,大多数方法都采用有限反演或网格化,将观测到的透镜星系椭圆率转化为对星系团表面质量密度的估计。我们从不同的角度来处理这个问题,在光滑粒子流体动力学的多尺度分析的成功的动机。在PBL中,我们把每个透镜星系作为一个粒子,然后重建的潜力,通过平滑的本地内核与可变的平滑尺度。通过这种方式,我们可以调整重建以在整个过程中产生恒定的信噪比,并最大限度地利用高信息密度的区域。PBL被设计成包括所有透镜观测量,包括来自强透镜的多个图像位置和通量,以及包括剪切和弯曲的弱透镜信号。然而,在本文中,我们描述了一个剪切重建,并将该方法应用于几个测试用例,包括模拟透镜集群,以及研究良好的“子弹头”(1 E0657 -56)。在前一种情况下,我们表明,PBL能够更好地识别尖点和子结构比基于网格的重建,在后一种情况下,我们表明,PBL是能够识别子结构的子弹集群,甚至没有利用强大的透镜测量。我们还公开了我们的代码。

英文摘要:

We present Particle-Based Lensing (PBL), a new technique for gravitational lensing mass reconstructions of galaxy clusters. Traditionally, most methods have employed either a finite inversion or gridding to turn observational lensed galaxy ellipticities into an estimate of the surface mass density of a galaxy cluster. We approach the problem from a different perspective, motivated by the success of multi-scale analysis in smoothed particle hydrodynamics. In PBL, we treat each of the lensed galaxies as a particle and then reconstruct the potential by smoothing over a local kernel with variable smoothing scale. In this way, we can tune a reconstruction to produce constant signal-noise throughout, and maximally exploit regions of high information density. PBL is designed to include all lensing observables, including multiple image positions and fluxes from strong lensing, as well as weak lensing signals including shear and flexion. In this paper, however, we describe a shear-only reconstruction, and apply the method to several test cases, including simulated lensing clusters, as well as the well-studied ``Bullet Cluster'' (1E0657-56). In the former cases, we show that PBL is better able to identify cusps and substructures than are grid-based reconstructions, and in the latter case, we show that PBL is able to identify substructure in the Bullet Cluster without even exploiting strong lensing measurements. We also make our codes publicly available.

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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