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arXiv 0812.3831astro-ph
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六种测光红移方法对150万亮红星系的比较

A Comparison of Six Photometric Redshift Methods Applied to 1.5 Million Luminous Red Galaxies

Filipe B. Abdalla, Manda Banerji, Ofer Lahav, Valery Rashkov

摘要:

我们提出了MegaZ-LRG的更新版本(Collister等人,(2007)),其中光度红移是用神经网络方法、ANNz以及其他五个公开可用的photo-z代码(HyperZ、SDSS、Le PHARE、BPZ和ZEBRA)导出的,用于SDSS DR 6中的约150万个发光红镓(LRG)。这使我们能够确定如果按照其公开版本中的描述使用,代码之间的相对可靠性。我们比较和对比的相对优点,每个代码使用~13000光谱红移从2SLAQ样品。我们发现,每个代码的性能取决于用于评估它的品质因数。正如预期的那样,一个完整的训练集的可用性意味着训练方法在有大量训练对象的中间红移箱中表现最好。像Le PHARE这样使用新观测到的模板的代码在较低的红移区间中表现最好。所有的代码产生合理的光度红移,1-西格玛散射范围从0.057到0.097,如果在整个红移范围内平均。我们还进行测试,以检查来自天空小区域的训练集(如2SLAQ)是否会产生偏差,如果用于在更大的天空区域进行训练。我们的结论是,这不太可能是一个问题,为未来的广泛领域的调查。完整的测光红移目录,包括所有六种方法的红移估计和误差,可以在www.star.ucl.ac.uk/~mbanerji/MegaZLRGDR6/megaz.html上找到。

英文摘要:

We present an updated version of MegaZ-LRG (Collister et al.,(2007)) with photometric redshifts derived with the neural network method, ANNz as well as five other publicly available photo-z codes (HyperZ, SDSS, Le PHARE, BPZ and ZEBRA) for ~1.5 million Luminous Red Galaxies (LRGs) in SDSS DR6. This allows us to identify how reliable codes are relative to each other if used as described in their public release. We compare and contrast the relative merits of each code using ~13000 spectroscopic redshifts from the 2SLAQ sample. We find that the performance of each code depends on the figure of merit used to assess it. As expected, the availability of a complete training set means that the training method performs best in the intermediate redshift bins where there are plenty of training objects. Codes such as Le PHARE, which use new observed templates perform best in the lower redshift bins. All codes produce reasonable photometric redshifts, the 1-sigma scatters ranging from 0.057 to 0.097 if averaged over the entire redshift range. We also perform tests to check whether a training set from a small region of the sky such as 2SLAQ produces biases if used to train over a larger area of the sky. We conclude that this is not likely to be a problem for future wide-field surveys. The complete photometric redshift catalogue including redshift estimates and errors on these from all six methods can be found at www.star.ucl.ac.uk/~mbanerji/MegaZLRGDR6/megaz.html

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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