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arXiv 0709.1692astro-ph
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星系-星系弱透镜效应的精密测光红移定标

Precision photometric redshift calibration for galaxy-galaxy weak lensing

R. Mandelbaum, U. Seljak, C. M. Hirata, S. Bardelli, M. Bolzonella, A. Bongiorno, M. Carollo, T. Contini, C. E. Cunha, B. Garilli, A. Iovino, P. Kampczyk, J. -P… 展开作者

R. Mandelbaum, U. Seljak, C. M. Hirata, S. Bardelli, M. Bolzonella, A. Bongiorno, M. Carollo, T. Contini, C. E. Cunha, B. Garilli, A. Iovino, P. Kampczyk, J. -P. Kneib, C. Knobel, D. C. Koo, F. Lamareille, O. Le Fevre, J. -F. Leborgne, S. J. Lilly, C. Maier, V. Mainieri, M. Mignoli, J. A. Newman, P. A. Oesch, E. Perez-Montero, E. Ricciardelli, M. Scodeggio, J. Silverman, L. Tasca

摘要:

精确的光度红移是精密弱透镜测量的关键要求之一。斯隆数字巡天(SDSS)的大尺寸和存在的大光谱红移样本是通量限制超过其深度,使其成为开发方法的最佳数据源,以正确校准光度红移透镜。在这里,我们专注于星系-星系透镜的光谱透镜红移调查,在SDSS。我们开发的统计数据,量化的透镜校准和加权方案的源红移误差的影响,并显示如何可以使用它们在存在的红移故障和采样方差。然后,我们用来自DEEP 2和zCOSMOS的光谱证明了它们与2838个源星系的使用,评估了几种公共光度红移算法,在两种情况下,包括每个对象的完整p(z),发现透镜校准偏差低至1%(由于两种类型的偏差的偶然消除)或对于有效使用的方法高达20%(尽管这些算法的小的平均photoz偏差)。我们的工作表明,透镜特定的统计必须使用可靠的校准透镜信号,由于(经常非高斯)photoz错误的不对称效应。我们还表明,大尺度结构(LSS)可以强烈影响的photoz校准和其误差估计,由于LSS和photoz误差之间的相关性,并认为,至少需要两个独立的度尺度光谱样本,以抑制其影响。考虑到我们光谱样本的大小,我们可以将星系-星系透镜校准误差降低到远低于当前SDSS统计误差的水平。

英文摘要:

Accurate photometric redshifts are among the key requirements for precision weak lensing measurements. Both the large size of the Sloan Digital Sky Survey (SDSS) and the existence of large spectroscopic redshift samples that are flux-limited beyond its depth have made it the optimal data source for developing methods to properly calibrate photometric redshifts for lensing. Here, we focus on galaxy-galaxy lensing in a survey with spectroscopic lens redshifts, as in the SDSS. We develop statistics that quantify the effect of source redshift errors on the lensing calibration and on the weighting scheme, and show how they can be used in the presence of redshift failure and sampling variance. We then demonstrate their use with 2838 source galaxies with spectroscopy from DEEP2 and zCOSMOS, evaluating several public photometric redshift algorithms, in two cases including a full p(z) for each object, and find lensing calibration biases as low as 1% (due to fortuitous cancellation of two types of bias) or as high as 20% for methods in active use (despite the small mean photoz bias of these algorithms). Our work demonstrates that lensing-specific statistics must be used to reliably calibrate the lensing signal, due to asymmetric effects of (frequently non-Gaussian) photoz errors. We also demonstrate that large-scale structure (LSS) can strongly impact the photoz calibration and its error estimation, due to a correlation between the LSS and the photoz errors, and argue that at least two independent degree-scale spectroscopic samples are needed to suppress its effects. Given the size of our spectroscopic sample, we can reduce the galaxy-galaxy lensing calibration error well below current SDSS statistical errors.

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