检验星系等级结构形成的理论需要估计星系形态的分布及其随红移的变化。这项研究的一个方面涉及识别具有扰动形态的星系（例如，合并星系）。这通常是通过总结星系图像来完成的，例如，Conselice（2003）和Lotz等人（2004）的CAS和Gini-M20统计数据，并将特定统计值与干扰相关联。我们介绍了三种增强高红移（z ~ 2）处扰动形貌检测的统计量：多模（M）、强度（I）和偏差（D）统计量。我们通过训练机器学习分类器随机森林来展示它们的有效性，使用哈勃太空望远镜WFC 3在H波段观察到的1，639个星系，这些星系之前已经由CANDELS合作通过眼睛分类（Grogin et al. 2011，Koekemoer et al. 2011）。我们发现，MID统计（和Conselice 2003年的A统计）是最有用的识别扰动形态。我们还探讨了人类注释者是否有助于识别受干扰的形态。我们证明，他们表现出有限的能力，以检测在高红移的干扰，并增加他们的数量超过约10并不能证明产生更好的分类性能。我们提出了一种基于模拟的模型拟合算法，通过绕过注释来缓解这些问题。
英文摘要：
Testing theories of hierarchical structure formation requires estimating the distribution of galaxy morphologies and its change with redshift. One aspect of this investigation involves identifying galaxies with disturbed morphologies (e.g., merging galaxies). This is often done by summarizing galaxy images using, e.g., the CAS and Gini-M20 statistics of Conselice (2003) and Lotz et al. (2004), respectively, and associating particular statistic values with disturbance. We introduce three statistics that enhance detection of disturbed morphologies at high-redshift (z ~ 2): the multi-mode (M), intensity (I), and deviation (D) statistics. We show their effectiveness by training a machine-learning classifier, random forest, using 1,639 galaxies observed in the H band by the Hubble Space Telescope WFC3, galaxies that had been previously classified by eye by the CANDELS collaboration (Grogin et al. 2011, Koekemoer et al. 2011). We find that the MID statistics (and the A statistic of Conselice 2003) are the most useful for identifying disturbed morphologies.
We also explore whether human annotators are useful for identifying disturbed morphologies. We demonstrate that they show limited ability to detect disturbance at high redshift, and that increasing their number beyond approximately 10 does not provably yield better classification performance. We propose a simulation-based model-fitting algorithm that mitigates these issues by bypassing annotation.
Studying the properties of galaxy cluster morphology estimators
对星系团的X射线观测揭示了具有不同扰动程度的大范围的形态，表明用于从X射线数据确定星系团质量的流体静力平衡和球形假设并不总是满足。因此，在星系团的X射线图像中检测和量化子结构对于理解星系团的性质以及宇宙学应用都是非常重要的。两种有前途的方法是功率比和中心移位。由于这些估计可以受到泊松噪声和X射线背景的严重影响，我们进行了广泛的分析，他们的统计特性，使用大样本的模拟X射线观测的集群从流体动力学模拟。我们量化的测量偏差和误差的详细信息，并给出了形态分析是可行的范围。一种新的，计算快速的方法来纠正泊松偏差和X射线背景贡献的功率比和中心偏移测量，并测试典型的XMM牛顿观测数据集。我们研究了121个模拟集群图像的形态，并建立了结构边界，将样本分为松弛，轻度扰动和扰动集群。此外，我们提出了一个新的形态估计-峰值的0.3-1 r500 P3/P0的配置文件，以更好地识别合并集群。分析方法被应用到一个样本的80个星系团观测XMM-牛顿。我们给出了所有80个观察到的团簇的结构参数（P3/P0 in r500，w和P3/P0_max）。使用我们对P3/P0（w）子结构边界的定义，我们发现我们观察到的集群中有41%（47%）受到干扰。
We present structural parameters and morphological properties of faint 450-um selected submillimeter galaxies (SMGs) from the JCMT Large Program, STUDIES, in the COSMOS-CANDELS region. Their properties are compared to an 850um selected and a matched star-forming samples. We investigate stellar structures of 169 faint 450-um sources (S450=2.8-29.6mJy; S/N>4) at z<3 using HST near-infrared observations. Based on our spectral energy distribution fitting, half of such faint SMGs (LIR=10^11.65+-0.98Lsun) lie above the star-formation rate (SFR)/stellar mass plane. The size-mass relation shows that t…
Emission-Line Galaxies from the Hubble Space Telescope Probing Evolution and Reionization Spectroscopically (PEARS) Grism Survey. II: The Complete Sample
Radio halos are extended ($\sim{\rm Mpc}$), steep-spectrum sources found in the central region of dynamically disturbed clusters of galaxies. Only a handful of radio halos have been reported to reside in galaxy clusters with a mass $M_{500}\lesssim5\times10^{14}\,M_\odot$. In this paper we present a LOFAR 144 MHz detection of a radio halo in the galaxy cluster Abell 990 with a mass of $M_{500}=(4.9\pm0.3)\times10^{14}\,M_\odot$. The halo has a projected size of $\sim$700$\,{\rm kpc}$ and a flux density of $20.2\pm2.2\,{\rm mJy}$ or a radio power of $1.2\pm0.1\times10^{24}\,{\rm W\,Hz}^{-1}$ at…
