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arXiv 1111.1070astro-ph.CO
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华丽的放大:利用透镜信号的另一半

Magnificent Magnification: Exploiting the Other Half of the Lensing Signal

Eric M. Huff, Genevieve J. Graves

摘要:

本文介绍了一种测量星系弱引力透镜放大率的新方法。我们的方法利用了星系性质之间的紧密比例关系,这些性质被引力透镜改变,如表观大小,而其他性质则没有,如表面亮度。特别是,我们使用一个版本的著名的基本平面关系的早期类型的星系。这种修改后的“光度基本平面”取代光度星系的性质的速度分散,从而避免了光谱数据的需要。我们提出了第一次检测放大使用这种方法,将其应用到光度表从斯隆数字巡天。这种分析表明,所得到的放大率信号与使用重力剪切的常规方法可获得的放大率信号相当。我们抑制了系统误差的主要来源,并讨论了适度的改进,可能使这种方法等于甚至超过与剪切实现的信号噪声比。此外,系统误差的一些主要来源与基于剪切的技术的主要来源有很大不同。因此,将这两种技术结合起来解决了每种技术的主要弱点,并提供了对单独使用的任何一种方法的实质性改进。有了这项新技术,放大率成为未来大型地面测量的必要测量工具,这些测量旨在测量引力透镜。

英文摘要:

We describe a new method for measuring galaxy magnification due to weak gravitational lensing. Our method makes use of a tight scaling relation between galaxy properties that are modified by gravitational lensing, such as apparent size, and other properties that are not, such as surface brightness. In particular, we use a version of the well-known fundamental plane relation for early type galaxies. This modified "photometric fundamental plane" replaces velocity dispersions with photometric galaxy properties, thus obviating the need for spectroscopic data. We present the first detection of magnification using this method by applying it to photometric catalogs from the Sloan Digital Sky Survey. This analysis shows that the derived magnification signal is comparable to that available from conventional methods using gravitational shear. We suppress the dominant sources of systematic error and discuss modest improvements that may allow this method to equal or even surpass the signal-to-noise achievable with shear. Moreover, some of the dominant sources of systematic error are substantially different from those of shear-based techniques. Thus, combining the two techniques addresses the major weaknesses of each and provides a substantial improvement over either method used in isolation. With this new technique, magnification becomes a necessary measurement tool for the coming era of large ground-based surveys intending to measure gravitational lensing.

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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