一种低表面亮度星系的自动搜索算法newline--YOLOX-CS

低表面亮度星系(Low Surface Brightness Galaxy, LSBG)的特征对于理解星系整体特征非常重要, 通过现代的机器学习特别是深度学习算法来搜寻扩充低表面亮度星系样本具有重要意义. LSBG因特征不明显而难以用传统方法进行自动和准确辨别, 但深度学习确具有自动找出复杂且有效特征的优势, 针对此问题提出了一种可用于在大样本巡天观测项目中搜寻LSBG的算法---YOLOX-CS (You Only Look Once version X-CS). 首先通过实验对比5种经典目标检测算法并选择较优的YOLOX算法作为基础算法, 然后结合不同注意力机制和不同优化器, 构建了YOLOX-CS的框架结构. 数据集使用的是斯隆数字化巡天(Sloan Digital Sky Survey, SDSS)中的图像, 其标签来自于$\alpha.40$-SDSS DR7 (40%中性氢苜蓿巡天与第7次数据发布的斯隆数字化巡天的交叉覆盖天区)巡天项目中的LSBG, 由于该数据集样本较少, 还采用了深度卷积生成对抗网络(Deep Convolutional Generative Adversarial Networks, DCGAN)模型扩充了实验测试数据. 通过与一系列目标检测算法对比后, YOLOX-CS在扩充前后两个数据集中搜索LSBG的召回率和AP (Average Precision)值都有较好的测试结果, 其在未扩充数据集的测试集中的召回率达到97.75%, AP值达到97.83%, 在DCGAN模型扩充的数据集中, 同样测试集下进行实验的召回率达到99.10%, AP值达到98.94%, 验证了该算法在LSBG搜索中具有优秀的性能. 最后, 将该算法应用到SDSS部分测光数据上, 搜寻得到了765个LSBG候选体.     

Correlation between radio and broad-line emission in radio-loud quasars

We present a correlation between radio and broad-line emission for a sample of radio-loud quasars that supports a close link between accretion processes and relativistic jets. BL Lac objects seem to follow the statistical behaviour of quasars, but with fainter broad-line emission.     

Color-Redshift Relations and Photometric Redshift Estimations of Quasars in Large Sky Surveys

With a recently constructed composite quasar spectrum and the X2 minimization technique, we describe a general method for estimating the photometric redshifts of a large sample of quasars by deriving theoretical color-redshift relations and comparing the theoretical colors with the observed ones. We estimated the photometric redshifts from the 5-band SDSS photometric data of 18678 quasars in the first major data release of SDSS and compared them with their spectroscopic redshifts. The difference is less than 0.1 for 47% of the quasars and less than 0.2 for 68%. Based on the calculation of the theoretical color-color diagrams of stars, galaxies and quasars both on the SDSS system and on the BATC system, we expect that we would be able to select candidates of high redshift quasars more efficaciously with the latter than with the former, provided the BATC survey can detect objects with magnitudes fainter than 21.     

The cluster substructure–alignment connection

Using a sample of 903 APM clusters we investigate whether their dynamical status, as evidenced by the presence of significant substructures, is related to the large-scale structure of the Universe. We find that the cluster dynamical activity is strongly correlated with the tendency of clusters to be aligned with their nearest neighbour and in general with the nearby clusters that belong to the same supercluster. Furthermore, dynamically active clusters are more clustered than the overall cluster population. These are strong indications that clusters develop in a hierarchical fashion by anisotropic merging along the large-scale filaments within which they are embedded.     

Mass estimation in the outer regions of galaxy clusters

We present a technique for estimating the mass in the outskirts of galaxy clusters where the usual assumption of dynamical equilibrium is not valid. The method assumes that clusters form through hierarchical clustering and requires only galaxy redshifts and positions on the sky. We apply the method to dissipationless cosmological N -body simulations where galaxies form and evolve according to semi-analytic modelling. The method recovers the actual cluster mass profile within a factor of 2 to several megaparsecs from the cluster centre. This error originates from projection effects, sparse sampling, and contamination by foreground and background galaxies. In the absence of velocity biases, this method can provide an estimate of the mass-to-light ratio on scales ∼1–10  h ⁻¹ Mpc where this quantity is still poorly known.     

The impact of dust on the scaling properties of galaxy clusters

We investigate the effect of dust on the scaling properties of galaxy clusters based on hydrodynamic N -body simulations of structure formation. We have simulated five dust models plus radiative cooling and adiabatic models using the same initial conditions for all runs. The numerical implementation of dust was based on the analytical computations of Montier & Giard. We set up dust simulations to cover different combinations of dust parameters that make evident the effects of size and abundance of dust grains. Comparing our radiative plus dust cooling runs with a purely radiative cooling simulation, we find that dust has an impact on cluster scaling relations. It mainly affects the normalization of the scalings (and their evolution), whereas it introduces no significant differences in their slopes. The strength of the effect critically depends on the dust abundance and grain size parameters as well as on the cluster scaling. Indeed, cooling due to dust is effective in the cluster regime and has a stronger effect on the 'baryon driven' statistical properties of clusters such as   L _X– M , Y – M , S – M   scaling relations. Major differences, relative to the radiative cooling model, are as high as 25 per cent for the   L _X– M   normalization, and about 10 per cent for the Y – M and S – M normalizations at redshift zero. On the other hand, we find that dust has almost no impact on the 'dark matter driven'   T _mw– M   scaling relation. The effects are found to be dependent in equal parts on both dust abundances and grain size distributions for the scalings investigated in this paper. Higher dust abundances and smaller grain sizes cause larger departures from the radiative cooling (i.e. with no dust) model.