分类： 天文学 >> 天文学 提交时间： 2023-02-19
Panping Li
Qian-Qing Yin
Zhengwei Li
Lian Tao
Xiangyang Wen
Shuang-Nan Zhang
Liqiang Qi
Juan Zhang
Donghua Zhao
Dalin Li
Xizheng Yu
Qingcui Bu
Wen Chen
Yupeng Chen
Yiming Huang
Yue Huang
Ge Jin
Gang Li
Hongbang Liu
Xiaojing Liu
摘要： In time-domain astronomy, a substantial number of transients will be discovered by multi-wavelength and multi-messenger observatories, posing a great challenge for follow-up capabilities. We have thus proposed an intelligent X-ray constellation, the Chasing All Transients Constellation Hunters (CATCH) space mission. Consisting of 126 micro-satellites in three types, CATCH will have the capability to perform follow-up observations for a large number of different types of transients simultaneously. Each satellite in the constellation will carry lightweight X-ray optics and use a deployable mast to increase the focal length. The combination of different optics and detector systems enables different types of satellites to have multiform observation capabilities, including timing, spectroscopy, imaging, and polarization. Controlled by the intelligent system, different satellites can cooperate to perform uninterrupted monitoring, all-sky follow-up observations, and scanning observations with a flexible field of view (FOV) and multi-dimensional observations. Therefore, CATCH will be a powerful mission to study the dynamic universe. Here, we present the current design of the spacecraft, optics, detector system, constellation configuration and observing modes, as well as the development plan.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Dong Li
Fanpeng Shi
Haisheng Zhao
Shaolin Xiong
Liming Song
Wenxi Peng
Xinqiao Li
Wei Chen
Zongjun Ning
摘要： Quasi-periodic pulsations (QPPs), which carry time features and plasma characteristics of flare emissions, are frequently observed in light curves of solar/stellar flares. In this paper, we investigated non-stationary QPPs associated with recurrent jets during an M1.2 flare on 2022 July 14. A quasi-period of about 45$\pm$10 s, determined by the wavelet transform technique, is simultaneously identified at wavelengths of soft/hard X-ray and microwave emissions, which are recorded by the Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor, Fermi, and the Nobeyama Radio Polarimeters, respectively. A group of recurrent jets with an intermittent cadence of about 45$\pm$10 s are found in Atmospheric Imaging Assembly (AIA) image series at 304 {\AA}, but they are 180-s earlier than the flare QPP. All observational facts suggest that the flare QPP could be excited by recurrent jets, and they should be associated with nonthermal electrons that are periodically accelerated by a repeated energy release process, like repetitive magnetic reconnection. Moreover, the same quasi-period is discovered at double footpoints connected by a hot flare loop in AIA 94 {\AA}, and the phase speed is measured to 1420 km/s. Based on the differential emission measure, the average temperatures, number densities, and magnetic field strengths at the loop top and footpoint are estimated to 7.7/6.7 MK, 7.5/3.6*10^{10} cm ^{-3}, and 143/99 G, respectively. Our measurements indicate that the 45-s QPP is probably modulated by the kink-mode wave of the flare loop.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Dali Zhang
Chao Zheng
Jiacong Liu
Zhenghua An
Chenwei Wang
Xiangyang Wen
Xinqiao Li
Xilei Sun
Ke Gong
Yaqing Liu
Xiaojing Liu
Sheng Yang
Wenxi Peng
Rui Qiao
Dongya Guo
Peiyi Feng
Yanqiu Zhang
Wangchen Xue
Wenjun Tan
Ce Cai
摘要： As a new member of GECAM mission, the GECAM-C (also called High Energy Burst Searcher, HEBS) is a gamma-ray all-sky monitor onboard SATech-01 satellite, which was launched on July 27th, 2022 to detect gamma-ray transients from 6 keV to 6 MeV, such as Gamma-Ray Bursts (GRBs), high energy counterpart of Gravitational Waves (GWs) and Fast Radio Bursts (FRBs), and Soft Gamma-ray Repeaters (SGRs). Together with GECAM-A and GECAM-B launched in December 2020, GECAM-C will greatly improve the monitoring coverage, localization, as well as temporal and spectral measurements of gamma-ray transients. GECAM-C employs 12 SiPM-based Gamma-Ray Detectors (GRDs) to detect gamma-ray transients . In this paper, we firstly give a brief description of the design of GECAM-C GRDs, and then focus on the on-ground tests and in-flight performance of GRDs. We also did the comparison study of the SiPM in-flight performance between GECAM-C and GECAM-B. The results show GECAM-C GRD works as expected and is ready to make scientific observations.
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
Dong Li
Fanpeng Shi
Haisheng Zhao
Shaolin Xiong
Liming Song
Wenxi Peng
Xinqiao Li
Wei Chen
Zongjun Ning
摘要： Quasi-periodic pulsations (QPPs), which carry time features and plasma characteristics of flare emissions, are frequently observed in light curves of solar/stellar flares. In this paper, we investigated non-stationary QPPs associated with recurrent jets during an M1.2 flare on 2022 July 14. A quasi-period of about 45$\pm$10 s, determined by the wavelet transform technique, is simultaneously identified at wavelengths of soft/hard X-ray and microwave emissions, which are recorded by the Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor, Fermi, and the Nobeyama Radio Polarimeters, respectively. A group of recurrent jets with an intermittent cadence of about 45$\pm$10 s are found in Atmospheric Imaging Assembly (AIA) image series at 304 {\AA}, but they are 180-s earlier than the flare QPP. All observational facts suggest that the flare QPP could be excited by recurrent jets, and they should be associated with nonthermal electrons that are periodically accelerated by a repeated energy release process, like repetitive magnetic reconnection. Moreover, the same quasi-period is discovered at double footpoints connected by a hot flare loop in AIA 94 {\AA}, and the phase speed is measured to 1420 km/s. Based on the differential emission measure, the average temperatures, number densities, and magnetic field strengths at the loop top and footpoint are estimated to 7.7/6.7 MK, 7.5/3.6*10^{10} cm ^{-3}, and 143/99 G, respectively. Our measurements indicate that the 45-s QPP is probably modulated by the kink-mode wave of the flare loop.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Peng Zhang
Bing Li
RenZhou Gui
Shaolin Xiong
Ze-Cheng Zou
Xianggao Wang
Xiaobo Li
Ce Cai
Yi Zhao
Yanqiu Zhang
Wangchen Xue
Chao Zheng
Hongyu Zhao
摘要： To research the burst phenomenon of gamma-ray bursts (GRBs) in depth, it is necessary to explore an effective and accurate identification of GRBs. Onboard blind search, ground blind search, and target search method are popular methods in identifying GRBs. However, they undeniably miss GRBs due to the influence of threshold, especially for sub-threshold triggers. We present a new approach to distinguish GRB by using convolutional neural networks (CNNs) to classify count maps that contain bursting information in more dimensions. For comparison, we design three supervised CNN models with different structures. Thirteen years Time-Tagged Event (TTE) format data from Fermi/GBM is employed to construct useful data sets and to train, validate and test these models. We find an optimal model, i.e. the ResNet-CBAM model trained on the 64 ms data set, which contains residual and attention mechanism modules. We track this deep learning model through two visualization analysis methods separately, Gradient-weighted Class Activation Mapping (Grad-CAM) and T-distributed Stochastic Neighbor Embedding (t-SNE) method, and find it focused on the main features of GRBs. By applying it on one-year data, about 96% of GRBs in the Fermi burst catalog were distinguished accurately, six out of ten GRBs of sub-threshold triggers were identified correctly, and meaningfully thousands of new candidates were obtained and listed according to their SNR information. Our study implies that the deep learning method could distinguish GRBs from background-like maps effectively and reliably. In the future, it can be implemented into real-time analysis pipelines to reduce manual inspection and improve accuracy, enabling follow-up observations with multi-band telescopes.
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
Peng Zhang
Xiang Ma
Yue Huang
Shaolin Xiong
Shijie Zheng
Liming Song
Ge Ou
Yanqi Du
Jing Liang
Hong Wu
摘要： Background The Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is primarily designed to spot gamma-ray bursts corresponding to gravitational waves. In order to achieve stable observations from various astronomical phenomena, the payload performance need to be monitored during the in-orbit operation. Method This article describes the design and implementation of GECAM satellite payload performance monitoring (GPPM) software. The software extracts the payload status and telescope observations (light curves, energy spectrums, characteristic peak fitting of energy spectrums, etc) from the payload data. Considering the large amount of payload status parameters in the engineering data, we have designed a method of parameter processing based on the configuration tables. This method can deal with the frequent changes of the data formats and facilitate program maintenance. Payload status and performance are monitored through defined thresholds and monitoring reports. The entire software is implemented in python language and the huge amount of observation data is stored in MongoDB. Conclusion The design and implementation of GPPM software have been completed, tested with ground and in-orbit payload data. The software can monitor the performance of GECAM payload effectively. The overall design of the software and the data processing method can be applied to other satellites.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Panping Li
Qian-Qing Yin
Zhengwei Li
Lian Tao
Xiangyang Wen
Shuang-Nan Zhang
Liqiang Qi
Juan Zhang
Donghua Zhao
Dalin Li
Xizheng Yu
Qingcui Bu
Wen Chen
Yupeng Chen
Yiming Huang
Yue Huang
Ge Jin
Gang Li
Hongbang Liu
Xiaojing Liu
摘要： In time-domain astronomy, a substantial number of transients will be discovered by multi-wavelength and multi-messenger observatories, posing a great challenge for follow-up capabilities. We have thus proposed an intelligent X-ray constellation, the Chasing All Transients Constellation Hunters (CATCH) space mission. Consisting of 126 micro-satellites in three types, CATCH will have the capability to perform follow-up observations for a large number of different types of transients simultaneously. Each satellite in the constellation will carry lightweight X-ray optics and use a deployable mast to increase the focal length. The combination of different optics and detector systems enables different types of satellites to have multiform observation capabilities, including timing, spectroscopy, imaging, and polarization. Controlled by the intelligent system, different satellites can cooperate to perform uninterrupted monitoring, all-sky follow-up observations, and scanning observations with a flexible field of view (FOV) and multi-dimensional observations. Therefore, CATCH will be a powerful mission to study the dynamic universe. Here, we present the current design of the spacecraft, optics, detector system, constellation configuration and observing modes, as well as the development plan.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Dali Zhang
Chao Zheng
Jiacong Liu
Zhenghua An
Chenwei Wang
Xiangyang Wen
Xinqiao Li
Xilei Sun
Ke Gong
Yaqing Liu
Xiaojing Liu
Sheng Yang
Wenxi Peng
Rui Qiao
Dongya Guo
Peiyi Feng
Yanqiu Zhang
Wangchen Xue
Wenjun Tan
Ce Cai
摘要： As a new member of GECAM mission, the GECAM-C (also called High Energy Burst Searcher, HEBS) is a gamma-ray all-sky monitor onboard SATech-01 satellite, which was launched on July 27th, 2022 to detect gamma-ray transients from 6 keV to 6 MeV, such as Gamma-Ray Bursts (GRBs), high energy counterpart of Gravitational Waves (GWs) and Fast Radio Bursts (FRBs), and Soft Gamma-ray Repeaters (SGRs). Together with GECAM-A and GECAM-B launched in December 2020, GECAM-C will greatly improve the monitoring coverage, localization, as well as temporal and spectral measurements of gamma-ray transients. GECAM-C employs 12 SiPM-based Gamma-Ray Detectors (GRDs) to detect gamma-ray transients . In this paper, we firstly give a brief description of the design of GECAM-C GRDs, and then focus on the on-ground tests and in-flight performance of GRDs. We also did the comparison study of the SiPM in-flight performance between GECAM-C and GECAM-B. The results show GECAM-C GRD works as expected and is ready to make scientific observations.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Peng Zhang
Bing Li
RenZhou Gui
Shaolin Xiong
Ze-Cheng Zou
Xianggao Wang
Xiaobo Li
Ce Cai
Yi Zhao
Yanqiu Zhang
Wangchen Xue
Chao Zheng
Hongyu Zhao
摘要： To research the burst phenomenon of gamma-ray bursts (GRBs) in depth, it is necessary to explore an effective and accurate identification of GRBs. Onboard blind search, ground blind search, and target search method are popular methods in identifying GRBs. However, they undeniably miss GRBs due to the influence of threshold, especially for sub-threshold triggers. We present a new approach to distinguish GRB by using convolutional neural networks (CNNs) to classify count maps that contain bursting information in more dimensions. For comparison, we design three supervised CNN models with different structures. Thirteen years Time-Tagged Event (TTE) format data from Fermi/GBM is employed to construct useful data sets and to train, validate and test these models. We find an optimal model, i.e. the ResNet-CBAM model trained on the 64 ms data set, which contains residual and attention mechanism modules. We track this deep learning model through two visualization analysis methods separately, Gradient-weighted Class Activation Mapping (Grad-CAM) and T-distributed Stochastic Neighbor Embedding (t-SNE) method, and find it focused on the main features of GRBs. By applying it on one-year data, about 96% of GRBs in the Fermi burst catalog were distinguished accurately, six out of ten GRBs of sub-threshold triggers were identified correctly, and meaningfully thousands of new candidates were obtained and listed according to their SNR information. Our study implies that the deep learning method could distinguish GRBs from background-like maps effectively and reliably. In the future, it can be implemented into real-time analysis pipelines to reduce manual inspection and improve accuracy, enabling follow-up observations with multi-band telescopes.
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