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arXiv 2409.14799astro-ph.GAastro-ph.CO
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通过颜色空间分析增强测光红移星表:在 KiDS-Bright 星系中的应用

Enhancing Photometric Redshift Catalogs Through Color-Space Analysis: Application to KiDS-Bright Galaxies

Priyanka Jalan, Maciej Bilicki, Wojciech A. Hellwing, Angus H. Wright, Andrej Dvornik, Catherine Heymans, Hendrik Hildebrandt, Shahab Joudaki, Konrad Kuijken, C… 展开作者

Priyanka Jalan, Maciej Bilicki, Wojciech A. Hellwing, Angus H. Wright, Andrej Dvornik, Catherine Heymans, Hendrik Hildebrandt, Shahab Joudaki, Konrad Kuijken, Constance Mahony, Szymon Jan Nakoneczny, Mario Radovich, Jan Luca van den Busch, Mijin Yoon

AI总结:

提出基于自组织映射(SOM)的颜色空间分析方法,通过对比分光校准数据识别代表性差的星系,优化KiDS-Bright测光红移星表,发现GAMA样本代表性充足,改进潜力有限。

摘要:

我们提出了一种通过比较测光红移星系星表的颜色空间匹配与重叠的分光光度学校准数据来优化其的方法。我们关注测光红移(photo-$z$)通过经验估计的情况。识别在分光数据中代表性不足的星系至关重要,因为由于超出了训练样本的外推,它们的 photo-$z$ 可能不可靠。我们的方法使用自组织映射(SOM)将星等和颜色的多维参数空间投影到二维流形上,使我们能够作为各种星系性质的函数来分析生成的模式。使用 SOM,我们将限于 $r<20$ mag 的 Kilo-Degree Survey 亮星系样本(KiDS-Bright)与各种分光样本(包括 Galaxy And Mass Assembly (GAMA))进行比较。我们的分析表明,GAMA 在 KiDS-Bright 最暗($r\gtrsim19.5$)和最高红移($z\gtrsim0.4$)的范围内代表性不足,但在颜色或恒星质量方面没有强烈的趋势。通过结合来自 SDSS、2dF 和早期 DESI 的额外分光数据,我们识别出 photo-$z$ 估计欠佳的 SOM 单元。我们推导出一组基于 SOM 的标准来优化测光样本并改善 photo-$z$ 统计数据。对于 KiDS-Bright 样本,这种改进是适度的:排除代表性最差的 20% 样本使 photo-$z$ 离散度降低了不到 10%。我们得出结论,用于 KiDS-Bright photo-$z$ 训练的 GAMA 在大部分颜色空间中具有足够的代表性,能够进行可靠的红移估计。来自 DESI 等巡天的未来分光数据应能更好地发挥我们方法的全部改进潜力。

英文摘要:

We present a method to refine photometric redshift galaxy catalogs by comparing their color-space matching with overlapping spectroscopic calibration data. We focus on cases where photometric redshifts (photo-$z$) are estimated empirically. Identifying galaxies that are poorly represented in spectroscopic data is crucial, as their photo-$z$ may be unreliable due to extrapolation beyond the training sample. Our approach uses a self-organizing map (SOM) to project a multi-dimensional parameter space of magnitudes and colors onto a 2-D manifold, allowing us to analyze the resulting patterns as a function of various galaxy properties. Using SOM, we compare the Kilo-Degree Survey bright galaxy sample (KiDS-Bright), limited to $r<20$ mag, with various spectroscopic samples, including the Galaxy And Mass Assembly (GAMA). Our analysis reveals that GAMA under-represents KiDS-Bright at its faintest ($r\gtrsim19.5$) and highest-redshift ($z\gtrsim0.4$) ranges, however no strong trends in color or stellar mass. By incorporating additional spectroscopic data from the SDSS, 2dF, and early DESI, we identify SOM cells where photo-$z$ are estimated suboptimally. We derive a set of SOM-based criteria to refine the photometric sample and improve photo-$z$ statistics. For the KiDS-Bright sample, this improvement is modest: exclusion of the least represented 20% of the sample reduces photo-$z$ scatter by less than 10%. We conclude that GAMA, used for KiDS-Bright photo-$z$ training, is sufficiently representative for reliable redshift estimation across most of the color space. Future spectroscopic data from surveys such as DESI should be better suited for exploiting the full improvement potential of our method.

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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