The lens parallax method: determining the redshifts of the faint blue galaxies through gravitational lensing

The lens parallax method: determining the redshifts of the faint blue galaxies through gravitational lensing
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透镜视差法:通过引力透镜确定微弱蓝色星系的红移

DOI:
10.1086/176200
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发表时间:
1994
期刊:
arXiv: Astrophysics
影响因子:
--
通讯作者:
R. Narayan
R. Narayan
中科院分区:
--
文献类型:
--
作者:
M. Bartelmann;R. Narayan

文献摘要

被引文献

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我们提出了一种新的技术,我们称之为透镜视差法,同时确定暗蓝色星系的红移分布和前景星系团的质量分布。该方法基于引力透镜,并利用了暗蓝色星系的平均角尺寸是表面亮度的一个确定函数这一事实。该方法首先需要校准无透镜空白场中角尺寸与表面亮度的关系,并确定暗蓝色星系中最亮星系的平均红移。通过将这些信息与前景星系团中背景星系的扭曲图像的观测相结合,我们表明有可能获得星系的平均红移作为其表面亮度的函数。使用大约10个中等红移丰富簇的样本,并使用10个表面亮度的bin,可以实现bin到bin的信噪比为$\sim3.5$。该方法同时可以确定透镜团的会聚和剪切作为位置的函数,从而可以得到透镜的质量分布。透镜视差方法可以与其他先前提出的映射簇的技术结合使用,并将提高精度。
We propose a new technique, which we call the lens parallax method, to determine simultaneously the redshift distribution of the faint blue galaxies and the mass distribution of foreground clusters of galaxies. The method is based on gravitational lensing and uses the fact that the mean angular size of the faint blue galaxies is a well-determined function of surface brightness. The method requires first a calibration of the angular-size vs. surface brightness relation in unlensed blank fields and a determination of the mean redshift of the brightest of the faint blue galaxies. By combining this information with observations of the distorted images of background galaxies in the fields of foreground clusters, we show that it is possible to obtain the mean redshift of the galaxies as a function of their surface brightness. With a sample of about ten moderate redshift rich clusters and using ten bins in surface brightness, a bin-to-bin signal-to-noise ratio of $\sim3.5$ can be achieved. The method simultaneously allows a determination of the convergence and shear of the lensing cluster as a function of position, and through this the mass distribution of the lens can be obtained. The lens parallax method can be used in conjunction with, and will improve the accuracy of, other previously proposed techniques for mapping clusters.