发射线星系[OⅡ]λ3727/Hα谱线流量比的研究

利用从斯隆数字巡天(Sloan Digital Sky Survey,简称SDSS)第4次释放的光谱数据中选取的10~5个发射线星系样本,研究了[O_Ⅱ]λ3727/Hα流量比与星系尘埃消光、气体电离态和金属丰度的关系.发现尘埃消光改正对[O_Ⅱ]λ3727/Hα谱线流量比影响显著,消光改正前、后的[O_Ⅱ]λ3727/Hα谱线流量比的中值分别为0.48和0.89;尘埃消光改正后,F([O_Ⅱ]λ3727)-F(Hα)的弥散显著减小.贫金属星系的[O_Ⅱ]λ3727/Hα谱线流量比随星系气体的电离度增高而减小,而富金属星系不存在这种关系.另外,[O_Ⅱ]λ3727/Hα流量比与星系金属丰度相关.当12+lg(O/H)8.5时,星系[O_Ⅱ]λ3727/Hα流量比随金属丰度增加而下降;12+lg(O/H)8.5的星系,谱线流量比与金属丰度正相关.最后,利用气体电离度参数和星系的金属丰度,给出了计算不同类型星系[O_Ⅱ]λ3727/Hα流量比的公式.LAMOST望远镜将观测到大量红移z0.4的星系光谱,利用该公式可以给出星系的[O_Ⅱ]λ3727/Hα流量比,从而可以利用[O_Ⅱ]λ3727谱线流量计算z0.4星系的恒星形成率.     

EfficientNetV2-S-Triplet7: 一种改进的星系newline 形态学分类算法

星系的形态与星系的形成和演化息息相关, 其形态学分类是星系天文学后续研究的重要一环. 当前海量天文观测数据的出现使得天文数据自动分析方法越来越得到重视, 针对此问题, 利用先进的深度学习骨干网络EfficientNetV2, 分析不同的注意力机制类型和使用节点对网络性能的影响, 构建了一种命名为EfficientNetV2-S-Triplet7 (即在EfficientNetV2-S stage7的$1\times1$卷积层后加入Triplet模块)的改进算法模型来实现星系形态学的自动分类. 使用第二期星系动物园(Galaxy Zoo 2, GZ2)中超过24万张的测光图像作为初始数据进行实验测试. 在对数据进行预处理时采取了尺寸抖动、翻转、色彩畸变等图像增强手段来解决图像数量的不平衡问题. 在同一系列经典和前沿的深度学习算法模型AlexNet、ResNet-34、MobileNetV2、RegNet进行对比实验后, 得出EfficientNetV2-S-Triplet7算法在分类准确率、查全率和F1分数等指标上具有最好的测试结果. 在9375张测试图像中的3项指标值分别可达到89.03%、90.21%、89.93%, 查准率达到89.69%, 在其他模型中排在第3位. 该结果表明将EfficientNetV2-S-Triplet7算法应用于大规模星系数据的形态学分类任务中有很好的效果.     

快速射电暴寄主星系色散量的估计

定位快速射电暴(Fast Radio Burst, FRB)以及确认其寄主星系至今仍是一个具有挑战性的难题,截至2021年4月已确认13个快速射电暴的寄主星系,其中只有3个重复暴,其余都是非重复暴.快速射电暴的寄主星系对快速射电暴起源的探索起着非常重要的作用,约束着快速射电暴前身星模型.对这些已确认寄主星系的FRB进行研究,发现FRB寄主星系对色散量(Dispersion Measure, DM)的贡献在一定范围内波动(0–240 pc·cm-3),并且寄主星系对DM的贡献与寄主星系的性质(恒星形成率、金属丰度)也可能具有关联性.寄主星系恒星形成率、金属丰度与色散量的统计关系对FRB邻近环境的研究有着重要意义.     

基于卷积神经网络的恒星光谱型和光度型的分类模型

恒星光谱分类是天文学中一个重要的研究问题.对于已经采集到的海量高维恒星光谱数据的分类,采用模式匹配方法对光谱型分类较为成功,但其缺点在于标准恒星模版之间的差异性在匹配实际观测数据中不能体现出来,尤其是当需要进行光谱型和光度型的二元分类时模版匹配法往往会失败.而采用谱线特征测量的光度型分类强烈地依赖谱线拟合的准确性.为了解决二元分类的问题,介绍了一种基于卷积神经网络的恒星光谱型和光度型分类模型(Classification model of Stellar Spectral type and Luminosity type based on Convolution Neural Network, CSSL CNN).这一模型使用卷积神经网络来提取光谱的特征,通过注意力模块学习到了重要的光谱特征,借助池化操作降低了光谱的维度并压缩了模型参数的数量,使用全连接层来学习特征并对恒星光谱进行分类.实验中使用了大天区面积多目标光纤光谱天文望远镜(Large Sky Area Multi-Object Fiber Spectroscopy Telescope, LAMOST)公开数据集Data Release 5 (DR5,用了其中71282条恒星光谱数据,每条光谱包含了3000多维的特征)对该模型的性能进行验证与评估.实验结果表明,基于卷积神经网络的模型在恒星的光谱型分类上准确率达到92.04%,而基于深度神经网络的模型(Celestial bodies Spectral Classification Model, CSC Model)只有87.54%的准确率; CSSL CNN在恒星的光谱型和光度型二元分类上准确率达到83.91%,而模式匹配方法MKCLASS仅有38.38%的准确率且效率较低.     

CDFS天区中喑蓝星系的测光红移研究

从COMBO-17数字巡天数据里,选择了CDFS(Chandra Deep Field South)天区中1231个测光红移在0.1～0.3之间的暗蓝星系作为样本,研究了这些星系分别在只有光学波段和光学加近红外波段数据情况下做测光红移得到的红移分布,以及这些星系在静止参考系下的能谱分布(Spectral Energy Distributions,SEDs)特征.结果表明有183个星系在利用光学加近红外波段数据做测光红移时得到的红移大于1.2,它们的误差为0.046,提高测光的信噪比也有利于区分这类被光学波段误认为低红移的星系.这些暗蓝星系中高红移星系的观测近红外流量相对于光学流量有上升的趋势,而低红移星系的观测近红外流量相对于光学流量有下降的趋势.     

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.     

E+A星系的研究进展

E+A星系的光谱具有很强的巴耳末吸收线,缺乏与恒星形成相关的发射线,将典型的椭圆星系(E)和A型恒星的光谱进行线性组合就能够拟合出这类星系的光谱.它们的颜色、形态、星族年龄等参数介于典型的早型和晚型星系之间.E+A星系近期经历了星暴活动,在星系演化进程中,它们处于晚型到早型的过渡阶段,可能在演变过程中扮演着重要角色.介...     

星系团Abell 85的动力学子结构

Abell 85是位于南半天区红移为0.055的cD星系团.基于前人的光谱观测数据和SDSS(Sloan Digital Sky Survey)数据,利用3σ方法筛选出该星系团的370个成员星系,并对其动力学情况进行了分析.从这些成员星系的空间分布和局域视向速度分布中,发现了该星系团含有4个明显的子结构,且正处于两两并合之中.这表明Abell 85处在动力学活跃的状态,远未达到动力学平衡.     

赛弗特星系恒星速度弥散度的测量

星系中心黑洞质量和核球恒星速度弥散度的紧密关系揭示出准确测量恒星速度弥散度对测定星系中心黑洞质量尤为重要.文中提供了一种利用SDSS(Sloan Digital SkySurvey)光谱测定速度弥散度及其不确定性的方法.通过对像素空间包含显著特征吸收线的4个不同谱区的拟合,得到准确测量恒星速度弥散度σ的光谱区域.文中4个拟合波段主要包含的吸收线为CaⅡK,MgⅠb三重线(波长5167.5,5172.7,5183.6(?))和CaT(CaⅡ三重线,波长8498.0,8542.1,8662.1(?)).不同区域结果表明,MgⅠb区由于受到铁族发射线影响,拟合的σ值偏低;CaⅡK线区谱线强度很弱,易受限于最小二乘法搜索算法;CaT+CaⅡK联合区得出的速度弥散度和只计算CaT区域的结果相当.利用该方法,测试了一个红移小于0.05的赛弗特星系样本,发现CaT区是测速度弥散度的最佳谱区.     

一种新的基于2维傅里叶谱图像的恒星光谱特征提取方法和深度网络分类应用

天体光谱分类是天文学研究的重要内容之一,其关键是从光谱数据中选择和提取对分类识别最有效的特征构建特征空间.提出一种新的基于2维傅里叶谱图像的特征提取方法,并应用于LAMOST (the Large Sky Area Multi-Object Fiber Spectroscopic Telescope)恒星光谱数据的分类研究中.光谱数据来源于LAMOST Data Release 5(DR5),选取30000条F、 G和K型星光谱数据,利用短时傅里叶变换(Short-Time Fourier Transform, STFT)将1维光谱数据变换成2维傅里叶谱图像,对得到的2维傅里叶谱图像采用深度卷积网络模型进行分类,得到的分类准确率是92.90%.实验结果表明通过对LAMOST恒星光谱数据进行STFT可得到光谱的2维傅里叶谱图像,谱图像构成了新的光谱数据特征和特征空间,新的特征对于光谱数据分类是有效的.此方法是对光谱分类的一种全新尝试,对海量天体光谱的分类和挖掘处理有一定的开创意义.     

Accurate parameter estimation for star formation history in galaxies using SDSS spectra

To further our knowledge of the complex physical process of galaxy formation, it is essential that we characterize the formation and evolution of large data bases of galaxies. The spectral synthesis starlight code of Cid Fernandes et al. was designed for this purpose. Results of starlight are highly dependent on the choice of input basis of simple stellar population (SSP) spectra. Speed of the code, which uses random walks through the parameter space, scales as the square of the number of the basis spectra, making it computationally necessary to choose a small number of SSPs that are coarsely sampled in age and metallicity. In this paper, we develop methods based on a diffusion map that, for the first time, choose appropriate bases of prototype SSP spectra from a large set of SSP spectra designed to approximate the continuous grid of age and metallicity of SSPs of which galaxies are truly composed. We show that our techniques achieve better accuracy of physical parameter estimation for simulated galaxies. Specifically, we show that our methods significantly decrease the age–metallicity degeneracy that is common in galaxy population synthesis methods. We analyse a sample of 3046 galaxies in Sloan Digital Sky Survey Data Release 6 and compare the parameter estimates obtained from different basis choices.     

The star formation histories of low surface brightness galaxies

We have performed deep imaging of a diverse sample of 26 low surface brightness galaxies (LSBGs) in the optical and the near-infrared. Using stellar population synthesis models, we find that it is possible to place constraints on the ratio of young to old stars (which we parametrize in terms of the average age of the galaxy), as well as the metallicity of the galaxy, using optical and near-infrared colours. LSBGs have a wide range of morphologies and stellar populations, ranging from older, high-metallicity earlier types to much younger and lower-metallicity late-type galaxies. Despite this wide range of star formation histories, we find that colour gradients are common in LSBGs. These are most naturally interpreted as gradients in mean stellar age, with the outer regions of LSBGs having lower ages than their inner regions. In an attempt to understand what drives the differences in LSBG stellar populations, we compare LSBG average ages and metallicities with their physical parameters. Strong correlations are seen between an LSBG's star formation history and its K -band surface brightness, K -band absolute magnitude and gas fraction. These correlations are consistent with a scenario in which the star formation history of an LSBG primarily correlates with its surface density and its metallicity correlates with both its mass and its surface density.     

The anatomy of the NGC 5044 group – II. Stellar populations and star formation histories

The distribution of galaxy properties in groups and clusters holds important information on galaxy evolution and growth of structure in the Universe. While clusters have received appreciable attention in this regard, the role of groups as fundamental to formation of the present-day galaxy population has remained relatively unaddressed. Here, we present stellar ages, metallicities and α-element abundances derived using Lick indices for 67 spectroscopically confirmed members of the NGC 5044 galaxy group with the aim of shedding light on galaxy evolution in the context of the group environment.
We find that galaxies in the NGC 5044 group show evidence for a strong relationship between stellar mass and metallicity, consistent with their counterparts in both higher and lower mass groups and clusters. Galaxies show no clear trend of age or α-element abundance with mass, but these data form a tight sequence when fitted simultaneously in age, metallicity and stellar mass. In the context of the group environment, our data support the tidal disruption of low-mass galaxies at small group-centric radii, as evident from an apparent lack of galaxies below  ∼10⁹ M_⊙  within ∼100 kpc of the brightest group galaxy. Using a joint analysis of absorption- and emission-line metallicities, we are able to show that the star-forming galaxy population in the NGC 5044 group appears to require gas removal to explain the ∼1.5 dex offset between absorption- and emission-line metallicities observed in some cases. A comparison with other stellar population properties suggests that this gas removal is dominated by galaxy interactions with the hot intragroup medium.     

The stellar populations of spiral galaxies

We have used a large sample of low-inclination spiral galaxies with radially resolved optical and near-infrared photometry to investigate trends in star formation history with radius as a function of galaxy structural parameters. A maximum-likelihood method was used to match all the available photometry of our sample to the colours predicted by stellar population synthesis models. The use of simplistic star formation histories, uncertainties in the stellar population models and considering the importance of dust all compromise the absolute ages and metallicities derived in this work; however, our conclusions are robust in a relative sense. We find that most spiral galaxies have stellar population gradients, in the sense that their inner regions are older and more metal rich than their outer regions. Our main conclusion is that the surface density of a galaxy drives its star formation history, perhaps through a local density dependence in the star formation law. The mass of a galaxy is a less important parameter; the age of a galaxy is relatively unaffected by its mass; however, the metallicity of galaxies depends on both surface density and mass. This suggests that galaxy‐mass-dependent feedback is an important process in the chemical evolution of galaxies. In addition, there is significant cosmic scatter suggesting that mass and density may not be the only parameters affecting the star formation history of a galaxy.     

Recovering physical parameters from galaxy spectra using MOPED

We derive physical parameters of galaxies from their observed spectra using MOPED, the optimized data compression algorithm of Heavens, Jimenez & Lahav. Here we concentrate on parametrizing galaxy properties, and apply the method to the NGC galaxies in Kennicutt's spectral atlas. We focus on deriving the star formation history, metallicity and dust content of galaxies. The method is very fast, taking a few seconds of CPU time to estimate ∼17 parameters, and is therefore specially suited to studying large data sets, such as the Anglo-Australian two-degree-field (2dF) galaxy survey and the Sloan Digital Sky Survey (SDSS). Without the power of MOPED, the recovery of star formation histories in these surveys would be impractical. In Kennicutt's atlas, we find that for the spheroidals a small recent burst of star formation is required to provide the best fit to the spectrum. There is clearly a need for theoretical stellar atmospheric models with spectral resolution better than 1 Å if we are to extract all the rich information that large redshift surveys contain in their galaxy spectra.     

基于胶囊网络的恒星光谱分类研究

大型巡天项目的快速发展,产生大量的恒星光谱数据,也使得实现恒星光谱数据的自动分类成为一项具有挑战性的工作.提出一种新的基于胶囊网络的恒星光谱分类方法,首先利用1维卷积网络和短时傅里叶变换将来源于LAMOST(Large Sky Area Multi-Object Fiber Spectroscopy Telescope)Data Release 5(DR5)的F5、G5、K5型1维恒星光谱转化成2维傅里叶谱图像,再通过胶囊网络对2维谱图像进行自动分类.由于胶囊网络具有保留图像中实体之间的分层位姿关系和无需池化层的优点,实验结果表明:胶囊网络具有较好的分类性能,对于F5、G5、K5型恒星光谱的分类,准确率优于其他分类方法.     

Spatially resolved kinematics and stellar populations of brightest cluster and group galaxies

We present an examination of the kinematics and stellar populations of a sample of three brightest group galaxies (BGGs) and three brightest cluster galaxies (BCGs) in X-ray groups and clusters. We have obtained high signal-to-noise ratio Gemini/Gemini South Multi-Object Spectrograph (GMOS) long-slit spectra of these galaxies and use Lick indices to determine ages, metallicities and α-element abundance ratios out to at least their effective radii. We find that the BGGs and BCGs have very uniform masses, central ages and central metallicities. Examining the radial dependence of their stellar populations, we find no significant velocity dispersion, age, or α-enhancement gradients. However, we find a wide range of metallicity gradients, suggesting a variety of formation mechanisms. The range of metallicity gradients observed is surprising, given the homogeneous environment these galaxies probe and their uniform central stellar populations. However, our results are inconsistent with any single model of galaxy formation and emphasize the need for more theoretical understanding of both the origins of metallicity gradients and galaxy formation itself. We postulate two possible physical causes for the different formation mechanisms.     

Evolutionary history of the elliptical galaxy NGC 1052

We have obtained Keck spectra for 16 globular clusters (GCs) associated with the merger remnant elliptical NGC 1052, as well as a long-slit spectrum of the galaxy. We derive ages, metallicities and abundance ratios from simple stellar population models using the recently published methods of Proctor & Sansom , applied to extragalactic GCs for the first time. A number of GCs indicate the presence of strong blue horizontal branches that are not fully accounted for in the current stellar population models. We find all of the GCs to be ∼13 Gyr old according to simple stellar populations, with a large range of metallicities. From the galaxy spectrum we find NGC 1052 to have a luminosity-weighted central age of ∼2 Gyr and metallicity of  [Fe/H]∼+0.6  . No strong gradients in either age or metallicity were found to the maximum radius measured  (0.3  r _e≃ 1 kpc)  . However, we do find a strong radial gradient in α-element abundance, which reaches a very high central value. The young central starburst age is consistent with the age inferred from the H  i tidal tails and infalling gas of ∼1 Gyr. Thus, although NGC 1052 shows substantial evidence for a recent merger and an associated starburst, it appears that the merger did not induce the formation of new GCs, perhaps suggesting that little recent star formation occurred. This interpretation is consistent with 'frosting' models for early-type galaxy formation.     

Kinematics and stellar populations of the dwarf elliptical galaxy IC 3653

We present the first 3D observations of a diffuse elliptical galaxy (dE). The good quality data (S/N up to 40) reveal the kinematical signature of an embedded stellar disc, reminiscent of what is commonly observed in elliptical galaxies, though similarity of their origins is questionable. Colour map built from Hubble Space Telescope Advanced Camera for Surveys (ACS) images confirms the presence of this disc. Its characteristic scale (about 3 arcsec =250 pc) is about a half of galaxy's effective radius, and its metallicity is 0.1–0.2 dex larger than the underlying population. Fitting the spectra with synthetic single stellar populations (SSP), we found an SSP-equivalent age of 5 Gyr and nearly solar metallicity [Fe/H]  =−0.06  dex. We checked that these determinations are consistent with those based on Lick indices, but have smaller error bars. The kinematical discovery of a stellar disc in dE gives additional support to an evolutionary link from dwarf irregular galaxies due to stripping of the gas against the intracluster medium.