分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： Hierarchical clustering is a common algorithm in data analysis. It is unique among many clustering algorithms in that it draws dendrograms based on the distance of data under a certain metric, and group them. It is widely used in all areas of astronomical research, covering various scales from asteroids and molecular clouds, to galaxies and galaxy cluster. This paper systematically reviews the history and current status of the development of hierarchical clustering methods in various branches of astronomy. These applications can be grouped into two broad categories, one revealing the intrinsic hierarchical structure of celestial systems and the other classifying large samples of celestial objects automatically. By reviewing these applications, we can clarify the conditions and limitations of the hierarchical clustering algorithm, and make more reasonable and reliable astronomical discoveries.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Yi Zhao
Wangchen Xue
Shaolin Xiong
Qi Luo
Yuanhao Wang
Jiacong Liu
Heng Yu
Xiaoyun Zhao
Yue Huang
Jinyuan Liao
Jianchao Sun
Xiaobo Li
Qibin Yi
Ce Cai
Shuo Xiao
Shenglun Xie
Chao Zheng
Yanqiu Zhang
Chenwei Wang
Wenjun Tan
摘要： Fast and reliable localization of high-energy transients is crucial for characterizing the burst properties and guiding the follow-up observations. Localization based on the relative counts of different detectors has been widely used for all-sky gamma-ray monitors. There are two major methods for this counts distribution localization: $\chi^{2}$ minimization method and the Bayesian method. Here we propose a modified Bayesian method that could take advantage of both the accuracy of the Bayesian method and the simplicity of the $\chi^{2}$ method. With comprehensive simulations, we find that our Bayesian method with Poisson likelihood is generally more applicable for various bursts than $\chi^{2}$ method, especially for weak bursts. We further proposed a location-spectrum iteration approach based on the Bayesian inference, which could alleviate the problems caused by the spectral difference between the burst and location templates. Our method is very suitable for scenarios with limited computation resources or time-sensitive applications, such as in-flight localization software, and low-latency localization for rapid follow-up observations.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： One-side head-tail (OHT) galaxies are radio galaxies with a peculiar shape. They usually appear in galaxy clusters, but they have never been cataloged systematically. We design an automatic procedure to search for them in the Faint Images of the Radio Sky at Twenty-Centimeters source catalog and compile a sample with 115 HT candidates. After cross-checking with the Sloan Digital Sky Survey photometric data and catalogs of galaxy clusters, we find that 69 of them are possible OHT galaxies. Most of them are close to the center of galaxy clusters. The lengths of their tails do not correlate with the projection distance to the center of the nearest galaxy clusters, but show weak anticorrelation with the cluster richness, and are inversely proportional to the radial velocity differences between clusters and host galaxies. Our catalog provides a unique sample to study this special type of radio galaxies.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： Hierarchical clustering is a common algorithm in data analysis. It is unique among many clustering algorithms in that it draws dendrograms based on the distance of data under a certain metric, and group them. It is widely used in all areas of astronomical research, covering various scales from asteroids and molecular clouds, to galaxies and galaxy cluster. This paper systematically reviews the history and current status of the development of hierarchical clustering methods in various branches of astronomy. These applications can be grouped into two broad categories, one revealing the intrinsic hierarchical structure of celestial systems and the other classifying large samples of celestial objects automatically. By reviewing these applications, we can clarify the conditions and limitations of the hierarchical clustering algorithm, and make more reasonable and reliable astronomical discoveries.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Yi Zhao
Wangchen Xue
Shaolin Xiong
Qi Luo
Yuanhao Wang
Jiacong Liu
Heng Yu
Xiaoyun Zhao
Yue Huang
Jinyuan Liao
Jianchao Sun
Xiaobo Li
Qibin Yi
Ce Cai
Shuo Xiao
Shenglun Xie
Chao Zheng
Yanqiu Zhang
Chenwei Wang
Wenjun Tan
摘要： Fast and reliable localization of high-energy transients is crucial for characterizing the burst properties and guiding the follow-up observations. Localization based on the relative counts of different detectors has been widely used for all-sky gamma-ray monitors. There are two major methods for this counts distribution localization: $\chi^{2}$ minimization method and the Bayesian method. Here we propose a modified Bayesian method that could take advantage of both the accuracy of the Bayesian method and the simplicity of the $\chi^{2}$ method. With comprehensive simulations, we find that our Bayesian method with Poisson likelihood is generally more applicable for various bursts than $\chi^{2}$ method, especially for weak bursts. We further proposed a location-spectrum iteration approach based on the Bayesian inference, which could alleviate the problems caused by the spectral difference between the burst and location templates. Our method is very suitable for scenarios with limited computation resources or time-sensitive applications, such as in-flight localization software, and low-latency localization for rapid follow-up observations.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Yi Zhao
Wang-Chen Xue
Shao-Lin Xiong
Yuan-Hao Wang
Jia-Cong Liu
Qi Liuo
Yan-Qiu Zhang
Jian-Chao Sun
Xiao-Yun Zhao
Ce Cai
Shuo Xiao
Yue Huang
Xiao-Bo Li
Zhen Zhang
Jin-Yuan Liao
Sheng Yang
Rui Qiao
Dong-Ya Guo
Chao Zheng
Qi-Bin Yi
摘要： Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is a pair of microsatellites (i.e. GECAM-A and GECAM-B) dedicated to monitoring gamma-ray transients including gravitational waves high-energy electromagnetic counterparts, Gamma-ray Bursts, Soft Gamma-ray Repeaters, Solar Flares and Terrestrial Gamma-ray Flashes. Since launch in December 2020, GECAM-B has detected hundreds of astronomical and terrestrial events. For these bursts, localization is the key for burst identification and classification as well as follow-up observations in multi-wavelength. Here, we propose a Bayesian localization method with Poisson data with Gaussian background profile likelihood to localize GECAM bursts based on the burst counts distribution in detectors with different orientations. We demonstrate that this method can work well for all kinds of bursts, especially for extremely short ones. In addition, we propose a new method to estimate the systematic error of localization based on a confidence level test, which can overcome some problems of the existing method in literature. We validate this method by Monte Carlo simulations, and then apply it to a burst sample with accurate location and find that the mean value of the systematic error of GECAM-B localization is $\sim 2.5^{\circ}$. By considering this systematic error, we can obtain a reliable localization probability map for GECAM bursts. Our methods can be applied to other gamma-ray monitors.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Yi Zhao
Wang-Chen Xue
Shao-Lin Xiong
Yuan-Hao Wang
Jia-Cong Liu
Qi Liuo
Yan-Qiu Zhang
Jian-Chao Sun
Xiao-Yun Zhao
Ce Cai
Shuo Xiao
Yue Huang
Xiao-Bo Li
Zhen Zhang
Jin-Yuan Liao
Sheng Yang
Rui Qiao
Dong-Ya Guo
Chao Zheng
Qi-Bin Yi
摘要： Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is a pair of microsatellites (i.e. GECAM-A and GECAM-B) dedicated to monitoring gamma-ray transients including gravitational waves high-energy electromagnetic counterparts, Gamma-ray Bursts, Soft Gamma-ray Repeaters, Solar Flares and Terrestrial Gamma-ray Flashes. Since launch in December 2020, GECAM-B has detected hundreds of astronomical and terrestrial events. For these bursts, localization is the key for burst identification and classification as well as follow-up observations in multi-wavelength. Here, we propose a Bayesian localization method with Poisson data with Gaussian background profile likelihood to localize GECAM bursts based on the burst counts distribution in detectors with different orientations. We demonstrate that this method can work well for all kinds of bursts, especially for extremely short ones. In addition, we propose a new method to estimate the systematic error of localization based on a confidence level test, which can overcome some problems of the existing method in literature. We validate this method by Monte Carlo simulations, and then apply it to a burst sample with accurate location and find that the mean value of the systematic error of GECAM-B localization is $\sim 2.5^{\circ}$. By considering this systematic error, we can obtain a reliable localization probability map for GECAM bursts. Our methods can be applied to other gamma-ray monitors.
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