[论文解读] The MUSE Hubble Ultra Deep Field Survey: III. Testing photometric redshifts to 30th magnitude

J. Brinchmann, Hanae Inami+15 more|Leiden Repository (Leiden University)|Oct 13, 2017

Galaxies: Formation, Evolution, Phenomena参考文献 67被引用 16

一句话总结

本研究利用MUSE积分场光谱作为真实值，测试了哈勃极深空场中星系在星等30下的测光红移（photo-z）性能。结果表明，尽管EAZY、BPZ和BEAGLE等测光红移代码在所有星等下均实现了偏差<0.05，但在0.4<z<1.5和z>3区间仍存在高达±0.04的系统性偏移，且当|(z_MUSE - pz)/(1+z_MUSE)| > 0.15时，异常值比例达到8–10%，空间混合在暗弱星系巡天中构成关键的污染风险。

ABSTRACT

We tested the performance of photometric redshifts for galaxies in the Hubble Ultra Deep field down to 30th magnitude. We compared photometric redshift estimates from three spectral fitting codes from the literature (EAZY, BPZ and BEAGLE) to high quality redshifts for 1227 galaxies from the MUSE integral field spectrograph. All these codes can return photometric redshifts with bias |Dzn|=|z-z_phot|/(1+z)&lt;0.05 down to F775W=30 and spectroscopic incompleteness is unlikely to strongly modify this statement. We have, however, identified clear systematic biases in the determination of photometric redshifts: in the 0.43 they are systematically biased high by up to Dzn = 0.05, an offset that can in part be explained by adjusting the amount of intergalactic absorption applied. In agreement with previous studies we find little difference in the performance of the different codes, but in contrast to those we find that adding extensive ground-based and IRAC photometry actually can worsen photo-z performance for faint galaxies. We find an outlier fraction, defined through |Dzn|&gt;0.15, of 8% for BPZ and 10% for EAZY and BEAGLE, and show explicitly that this is a strong function of magnitude. While this outlier fraction is high relative to numbers presented in the literature for brighter galaxies, they are very comparable to literature results when the depth of the data is taken into account. Finally, we demonstrate that while a redshift might be of high confidence, the association of a spectrum to the photometric object can be very uncertain and lead to a contamination of a few percent in spectroscopic training samples that do not show up as catastrophic outliers, a problem that must be tackled in order to have sufficiently accurate photometric redshifts for future cosmological surveys.

研究动机与目标

• 评估哈勃极深空场中极端暗弱星系（星等达30等）测光红移的准确性。
• 评估三种广泛使用的photo-z代码（EAZY、BPZ、BEAGLE）与高质量MUSE光谱红移的性能表现。
• 识别在极端深度下测光红移估计中的系统性偏差和异常值比例。
• 研究空间混合对光谱训练样本和测光红移校准的影响。

提出的方法

• 利用MUSE积分场光谱获取1,227个星系在m_F775W = 30星等下的高精度红移。
• 通过归一化红移差值|(z_MUSE - pz)/(1 + z_MUSE)|，将EAZY、BPZ和BEAGLE的测光红移与MUSE红移进行比较。
• 分析测光红移性能在星等、红移和星系颜色方面的依赖关系。
• 评估在暗弱星系中增加地面和IRAC测光数据对测光红移精度的影响。
• 量化具有更强发射线但空间重合的更暗星系的比例，这些星系可能污染红移赋值。
• 探讨星际介质（IGM）吸收建模对测光红移估计系统性偏差的影响。

实验结果

研究问题

• RQ1 在m_F775W = 30时，测光红移的准确性如何？在0.4 < z < 5的红移范围内，其偏差是否保持在<0.05？
• RQ2 在暗弱星等下，EAZY、BPZ和BEAGLE的测光红移估计中是否存在系统性偏差？其成因是什么？
• RQ3 在暗弱星系中，增加广泛的地面和IRAC测光数据如何影响测光红移性能？
• RQ4 有多少比例的星系受空间混合影响，导致训练样本中错误的光谱红移赋值？
• RQ5 灾难性异常值（|Δz/(1+z)| > 0.5）和混合源污染在多大程度上损害未来宇宙学巡天中的测光红移校准？

主要发现

• 所有三种测光红移代码——EAZY、BPZ和BEAGLE——在m_F775W = 30时均实现了|(z_MUSE - pz)/(1 + z_MUSE)| < 0.05的偏差，表明在极端深度下表现稳健。
• 在0.4 < z < 1.5区间检测到最高达-0.04（低估）的系统性偏差，而在z > 3时检测到+0.05（高估）的系统性偏差，表明存在红移依赖的校准问题。
• 异常值比例（定义为|(z_MUSE - pz)/(1 + z_MUSE)| > 0.15）在BPZ中达到8%，在EAZY和BEAGLE中达到10%，且该比例随星等增加而显著上升。
• 增加广泛的地面和IRAC测光数据反而恶化了暗弱星系的测光红移性能，与明亮样本研究的预期相反。
• 在m_F775W = 25时，1–2%的星系存在更暗但空间重合的星系，且其发射线更强，存在错误红移赋值和训练样本污染的风险。
• 灾难性异常值（|Δz/(1+z)| > 0.5）在EAZY中影响的星系数量是BEAGLE或BPZ的2–3倍，但三者同时出现灾难性异常值的星系比例低于0.6%，表明跨代码验证可有效识别异常情况。