[论文解读] The SRG/eROSITA All-Sky Survey

Matthias Kluge, J. Comparat+30 more|arXiv (Cornell University)|Feb 13, 2024

Astronomy and Astrophysical Research被引用 1

一句话总结

本文利用DESI遗产巡天的测光红移和丰度数据，首次对eROSITA全天巡天（eRASS1）在银河南半球的12,000个X射线选源星系团和星系群进行了光学识别与表征。该星表在 z > 0.05 时达到86%的纯度和>95%的完整性，且速度 dispersion-丰度关系校准良好，其关系为 log(λnorm) = 2.401 × log(σ) − 5.074，内在发散为 δin = 0.10 ± 0.01 dex。

ABSTRACT

Aims. Characterising galaxy cluster populations from a catalogue of sources selected in astronomical surveys requires knowledge of sample incompleteness, known as the selection function. The first All-Sky Survey (eRASS1) by eROSITA on board Spectrum Roentgen Gamma (SRG) has enabled the collection of large samples of galaxy clusters detected in the soft X-ray band over the western Galactic hemisphere. The driving goal consists in constraining cosmological parameters, which puts stringent requirements on the accuracy and flexibility of explainable selection function models. Methods. We used a large set of mock observations of the eRASS1 survey and we processed simulated data identically to the real eRASS1 events. We matched detected sources to simulated clusters and we associated detections to intrinsic cluster properties. We trained a series of models to build selection functions depending only on observable surface brightness data. We developed a second series of models relying on global cluster characteristics such as X-ray luminosity, flux, and the expected instrumental count rate as well as on morphological properties. We validated our models using our simulations and we ranked them according to selected performance metrics. We validated the models with datasets of clusters detected in X-rays and via the Sunyaev–Zeldovich effect. We present the complete Bayesian population modelling framework developed for this purpose. Results. Our results reveal the surface brightness characteristics most relevant to cluster selection in the eRASS1 sample, in particular the ambiguous role of central surface brightness at the scale of the instrument resolution. We have produced a series of user-friendly selection function models and demonstrated their validity and their limitations. Our selection function for bright sources reproduces the catalogue matches with external datasets well. We discuss potential inconsistencies in the selection models at a low signal-to-noise revealed by comparison with a deep X-ray sample acquired by eROSITA during its performance verification phase. Conclusions. Detailed modelling of the eRASS1 galaxy cluster selection function is made possible by reformulating selection into a classification problem. Our models are used in the first eRASS1 cosmological analysis and in sample studies of eRASS1 cluster and groups. These models are crucial for science with eROSITA cluster samples and our new methods pave the way for further investigation of faint cluster selection effects.

研究动机与目标

• 对eROSITA全天巡天（eRASS1）在银河南半球的X射线选源星系团和星系群进行光学识别与表征。
• 通过结合X射线探测与DESI遗产影像巡天的光学和近红外数据，提高星系团样本的纯度。
• 对12,000个星系团高精度测量测光红移、丰度、光学中心和最亮团星系（BCG）位置。
• 通过光谱红移和文献匹配星系团验证星表，确保其在宇宙学应用中的稳健性。
• 校准速度 dispersion-丰度关系，以用于宇宙学参数估计。

提出的方法

• 应用eROMaPPer星系团探测算法，利用DESI遗产巡天数据中的红序列测光法检测星系团。
• 对 0.05 < z < 0.9 的星系团，测得测光红移精度为 δz/(1 + z) ≲ 0.005。
• 利用大规模光谱红移数据集，分别测量了3,210个和1,499个星系团的 zspec 和速度 dispersion σ。
• 通过与文献星系团星表交叉匹配，并对整个遗产巡天区域进行盲应用，评估样本的纯度与完整性。
• 利用光谱子样本拟合速度 dispersion-丰度关系，同时考虑内在发散。
• 在多个文献星系团星表上验证识别方法，确保一致性与可靠性。

实验结果

研究问题

• RQ1 当使用多波段数据进行光学识别时，eROSITA全天巡天星系团样本的纯度与完整性如何？
• RQ2 利用红序列法对X射线选源星系团的测光红移测量精度如何？
• RQ3 eRASS1星系团样本中速度 dispersion 与丰度之间的标定关系是什么？其内在发散是多少？
• RQ4 当将光学识别方法盲应用于整个遗产巡天区域时，其性能如何？
• RQ5 考虑到其X射线选源与光学验证，该星表在宇宙学分析中的可靠性如何？

主要发现

• eRASS1星系团样本在 z > 0.05 时纯度为86%，光学完整性 >95%。
• 测光红移精度在 0.05 < z < 0.9 范围内达到 δz/(1 + z) ≲ 0.005。
• 速度 dispersion-丰度关系校准为 log(λnorm) = 2.401 × log(σ) − 5.074，内在发散为 δin = 0.10 ± 0.01 dex。
• 星表包含12,000个星系团与星系群，中值红移 z = 0.31，其中10%位于 z > 0.72。
• 识别方法在文献星表上成功验证，并盲应用于遗产巡天的24,069 deg²区域，证实其稳健性。
• 该星表是精密宇宙学的主要资源，可实现质量-可观测量关系校准与百分之一精度的宇宙学参数约束。