Subjects: Astronomy >> Astrophysical processes submitted time 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
Abstract： 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.
Peer Review Status:
Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
Peng Zhang
Xiang Ma
Yue Huang
Shaolin Xiong
Shijie Zheng
Liming Song
Ge Ou
Yanqi Du
Jing Liang
Hong Wu
Abstract： 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.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 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
Abstract： 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.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 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
Abstract： 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.
Peer Review Status:Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 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
Abstract： 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.
Peer Review Status:Awaiting Review
Subjects: Optics >> Quantum optics submitted time 2023-02-19
Jian Li
Jie Pang
Zhen-dong Yan
Junghoon Jahng
Jin Li
William Morrison
Jing Liang
Qing-Ying Zhang
Xing-Hua Xia
Abstract： Tip enhanced IR spectra and imaging have been widely used in cutting-edge studies for the in-depth understanding of the composition, structure and function of interfaces at the nanoscale. However, molecular monolayer sensitivity has only been demonstrated on solid/gas interfaces. In aqueous environment, the reduced sensitivity due to strong damping of the cantilever oscillation and background IR absorption extremely limits the practical applications of tip enhanced IR nanospectroscopy. Here, we demonstrate hypersensitive nanoscale IR spectra and imaging in aqueous environment with the combination of photoinduced force (PiF) microscopy and resonant antennas. The highly confined electromagnetic field inbetween the tip end and antenna extremely amplifies the photoinduced force to the detectable level, while the excitation via plasmon internal reflection mode minimizes the environmental absorption. A polydimethylsiloxane (PDMS) layer (~1-2 nm thickness) functionalized on the AFM tip has been successfully identified in water with antennas of different sizes. Sampling volume of ~604 chemical bonds from PDMS was demonstrated with sub-10 nm spatial resolution confirmed by electric (E) field distribution mapping on antennas, which strongly suggests the desired requirements for interfacial spectroscopy. This platform demonstrates for the first time the application of photoinduced force microscopy in aqueous environments, providing a brand-new configuration to achieve highly enhanced nanoscale IR signals, which is extremely promising for future research of interfaces and nanosystems in aqueous environments.
Peer Review Status:Awaiting Review
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