The study of carbon-enhanced metal-poor (CEMP) stars is of great significance for understanding the chemical evolution of the early universe and stellar formation.CEMP stars are characterized by carbon overabundance a...The study of carbon-enhanced metal-poor (CEMP) stars is of great significance for understanding the chemical evolution of the early universe and stellar formation.CEMP stars are characterized by carbon overabundance and are classified into several subclasses based on the abundance patterns of neutron-capture elements,including CEMP-s,CEMP-no,CEMP-r,and CEMP-r/s.These subclasses provide important insights into the formation of thefirst stars,early stellar nucleosynthesis,and supernova explosions.However,one of the major challenges in CEMP star research is the relatively small sample size of identified stars,which limits statistical analyses and hinders a comprehensive understanding of their properties.Fortunately,a series of large-scale spectroscopic survey projects have been launched and developed in recent years,providing unprecedented opportunities and technical challenges for the search and study of CEMP stars.To this end,this paper draws on the progress and future prospects of existing methods in constructing large CEMP data sets and offers an in-depth discussion from a technical standpoint,focusing on the strengths and limitations.In addition,we review recent advancements in the identification of CEMP stars,emphasizing the growing role of machine learning in processing and analyzing the increasingly large data sets generated by modern astronomical surveys.Compared to traditional spectral analysis methods,machine learning offers greater efficiency in handling complex data,automatic extraction of stellar parameters,and improved prediction accuracy.Despite these advancements,the research faces persistent challenges,including the scarcity of labeled samples,limitations imposed by low-resolution spectra,and the lack of interpretability in machine learning models.To address these issues,the paper proposes potential solutions and future research directions aimed at advancing the study of CEMP stars and enhancing our understanding of their role in the chemical evolution of the universe.展开更多
The recent surge in computer vision and deep learning has attracted significant attention within the galaxy morphology community.Various models have been implemented for galaxy morphology prediction with nearperfect a...The recent surge in computer vision and deep learning has attracted significant attention within the galaxy morphology community.Various models have been implemented for galaxy morphology prediction with nearperfect accuracy for certain classes.However,many studies treat deep learning models as black-box entities,lacking interpretability of their predictions.To address these limitations while ensuring good performance,we introduced an Improved SqueezeNet(I-SqueezeNet)by incorporating unique residual connections to improve the prediction performance,and we utilize Local Interpretable Model-Agnostic Explanations(LIME)to understand the interpretability.We evaluated the simplified SqueezeNet and I-SqueezeNet,with both channel and vertical concatenation,and compared their performances with those of some exiting methods such as Dieleman’s CNN,VGG13,DenseNet121,ResNet50,ResNext50,ResNext101,DSCNN and customized CNN in classifying galaxy objects using a dataset from the publicly available Galaxy Zoo Data Challenge Project.Our experiments showed that I-SqueezeNet with vertical concatenation achieved the highest average accuracy of 94.08%compared to other methods.Beyond achieving high accuracy,the application of LIME for model interpretation sheds light on the machine learning features and reasoning processes behind the model’s predictions.This information provides valuable insight into the galaxy morphology decision-making process,paving the way for further functional enhancements.展开更多
Pulsar candidate identification is an indispensable task in pulsar science.Based on the characteristics of imbalanced and diverse pulsar data sets,and the lack of a unified processing framework,we first used dimension...Pulsar candidate identification is an indispensable task in pulsar science.Based on the characteristics of imbalanced and diverse pulsar data sets,and the lack of a unified processing framework,we first used dimensionality reduction and visualization to analyze potential deficiencies caused by the incompleteness of current data set extraction methods.We found that the limited use of non-pulsar data may lead to bias in the result,which may limit the generalization ability.Based on the dimensionality reduction results,we propose a Grid Group Uniform Sampling(GGUS) method.This data preprocessing method improves the performance of Random Forest,Support Vector Machine,Convolutional Neural Network,and Res Net50 models on Lyon’s features,diagnostic plots,and perioddispersion measure (period-DM) plots in the HTRU1 data set.The average recall increased by approximately0.5%,precision by nearly 2%,and F_(1) score by around 1.2%for all models and in all data sets.In the period-DM plots testing,the high-performance Res Net50 algorithm achieved over 98%F_(1) using random sampling.GGUS demonstrated further improvements in this test,enhancing the average F_(1) score,precision,and recall by approximately 0.07%,0.1%,and 0.03%,respectively.展开更多
Fast radio bursts(FRBs)are among the most studied radio transients in astrophysics,but their origin and radiation mechanism are still unknown.It is a challenge to search for FRB events in a huge amount of observationa...Fast radio bursts(FRBs)are among the most studied radio transients in astrophysics,but their origin and radiation mechanism are still unknown.It is a challenge to search for FRB events in a huge amount of observational data with high speed and high accuracy.With the rapid advancement of the FRB research process,FRB searching has changed from archive data mining to either long-term monitoring of the repeating FRBs or all-sky surveys with specialized equipments.Therefore,establishing a highly efficient and high quality FRB search pipeline is the primary task in FRB research.Deep learning techniques provide new ideas for FRB search processing.We have detected radio bursts from FRB 20201124A in the L-band observational data of the Nanshan 26 m radio telescope(NSRT-26m)using the constructed deep learning based search pipeline named dispersed dynamic spectra search(DDSS).Afterwards,we further retrained the deep learning model and applied the DDSS framework to S-band observations.In this paper,we present the FRB observation system and search pipeline using the S-band receiver.We carried out search experiments,and successfully detected the radio bursts from the magnetar SGR J1935+2145and FRB 20220912A.The experimental results show that the search pipeline can complete the search efficiently and output the search results with high accuracy.展开更多
Radiation pattern captures the electromagnetic performance of reflector antennas,which is significantly affected by the deformation of the primary reflector due to gravity and the displacement of the secondary reflect...Radiation pattern captures the electromagnetic performance of reflector antennas,which is significantly affected by the deformation of the primary reflector due to gravity and the displacement of the secondary reflector.During the design process of large reflector antennas,a substantial amount of time is often dedicated to iteratively adjusting structural parameters and validating electromagnetic performance.To improve the efficiency of the design process,we first propose an approximate calculation method of optical path difference(OPD)for the deformation of the primary reflector under gravity and the displacement of the secondary reflector.Then an OPD fitting function based on the modified Zernike polynomials is proposed to capture the phase difference of radiation over the aperture plane,based on which the radiation pattern will be obtained quickly by the aperture field integration method.Numerical experiments demonstrate the effectiveness of the proposed quick calculation method for analyzing the radiation pattern of a 10.4 m submillimeter telescope antenna at its highest operating frequency of 856 GHz.In comparison with the numerical simulation method based on GRASP(which is an antenna electromagnetic analysis tool combining physical optics(PO)and physical theory of diffraction(PTD)),the quick calculation method reduces the time for radiation pattern analysis from more than one hour to less than two minutes.Furthermore,the quick calculation method exhibits excellent accuracy for the figure of merit(FOM)of the radiation pattern.Therefore,the proposed quick calculation method can obtain the radiation pattern with high speed and accuracy.Compared to the time-consuming numerical simulation method(PO and PTD),it can be employed for quick analysis of the radiation pattern for the lateral displacement of the secondary reflector and the deformation of the primary reflector under gravity in the design process of a reflector antenna.展开更多
With its high duty cycle, wide field of view and high detection sensitivity, Water Chereknov Detector Array as one of sub-arrays of Large High Altitude Air Shower Observatory is a promising facility to monitor transie...With its high duty cycle, wide field of view and high detection sensitivity, Water Chereknov Detector Array as one of sub-arrays of Large High Altitude Air Shower Observatory is a promising facility to monitor transient phenomena in the very high energy gamma-ray band. In this work, a real-time monitor for selected TeV extragalactic sources is introduced, this flare monitor is developed to detect very high energy flare events and for further studying the power-providing mechanism of blazar relativistic jets. The detailed information such as the searching method and sensitivity of this real-time flare monitor is also presented. In the end, successful multiwavelength and multi-messenger observation of 1ES 1959+650 and IC 310 also confirms the capabilities and reliability of the monitoring system.展开更多
Ground-based optical observation has unique advantages in space target observation.However,due to the weak light-gathering ability of small-aperture optoelectronic observation telescopes,the space debris in the image ...Ground-based optical observation has unique advantages in space target observation.However,due to the weak light-gathering ability of small-aperture optoelectronic observation telescopes,the space debris in the image is weak and easily drowned in noise.In order to solve the above problems,we use digital image processing technology to extract faint space debris.We propose a high detection rate space debris automatic extraction algorithm,aiming to automatically detect space debris.We first establish a new space target description model.Our algorithm is mainly divided into two stages.The purpose of the first stage is to reduce the influence of a large number of stars.We perform wavelet transform and guided filtering for three consecutive frames,and the reconstructed wavelet that takes the median value can achieve the effect of eliminating stars.In the second stage,we adopt the method of robust principal component analysis and attribute the problem of target detection to the problem of separating the target and background of a single frame of image.After a large number of experimental results analysis,it is proved that the algorithm can effectively detect faint debris in the monitoring system of small aperture telescope,and has high precision and low computational complexity.展开更多
The origin and phenomenology of Fast Radio Bursts(FRBs) remain unknown. Fast and efficient search technology for FRBs is critical for triggering immediate multi-wavelength follow-up and voltage data dump. This paper p...The origin and phenomenology of Fast Radio Bursts(FRBs) remain unknown. Fast and efficient search technology for FRBs is critical for triggering immediate multi-wavelength follow-up and voltage data dump. This paper proposes a dispersed dynamic spectra search(DDSS) pipeline for FRB searching based on deep learning, which performs the search directly from observational raw data, rather than relying on generated FRB candidates from single-pulse search algorithms that are based on de-dispersion. We train our deep learning network model using simulated FRBs as positive and negative samples extracted from the observational data of the Nanshan 26 m radio telescope(NSRT)at Xinjiang Astronomical Observatory. The observational data of PSR J1935+1616 are fed into the pipeline to verify the validity and performance of the pipeline. Results of the experiment show that our pipeline can efficiently search single-pulse events with a precision above 99.6%, which satisfies the desired precision for selective voltage data dump. In March 2022, we successfully detected the FRBs emanating from the repeating case of FRB 20201124A with the DDSS pipeline in L-band observations using the NSRT. The DDSS pipeline shows excellent sensitivity in identifying weak single pulses, and its high precision greatly reduces the need for manual review.展开更多
A 30-m TeraHertz（THz） radio telescope is proposed to operate at 200 μm with an active primary surface.This paper presents sensitivity analysis of active surface panel positioning errors with optical performance in ...A 30-m TeraHertz（THz） radio telescope is proposed to operate at 200 μm with an active primary surface.This paper presents sensitivity analysis of active surface panel positioning errors with optical performance in terms of the Strehl ratio.Based on Ruze＇s surface error theory and using a Monte Carlo simulation,the effects of six rigid panel positioning errors,such as piston,tip,tilt,radial,azimuthal and twist displacements,were directly derived.The optical performance of the telescope was then evaluated using the standard Strehl ratio.We graphically illustrated the various panel error effects by presenting simulations of complete ensembles of full reflector surface errors for the six different rigid panel positioning errors.Study of the panel error sensitivity analysis revealed that the piston error and tilt/tip errors are dominant while the other rigid errors are much less important.Furthermore,as indicated by the results,we conceived of an alternative Master-Slave Concept-based（MSC-based） active surface by implementating a special Series-Parallel Concept-based（SPC-based） hexapod as the active panel support mechanism.A new 30-m active reflector based on the two concepts was demonstrated to achieve correction for all the six rigid panel positioning errors in an economically feasible way.展开更多
Extreme ultraviolet(EUV)observations are widely used in solar activity research and space weather forecasting since they can observe both the solar eruptions and the source regions of the solar wind.Flat field process...Extreme ultraviolet(EUV)observations are widely used in solar activity research and space weather forecasting since they can observe both the solar eruptions and the source regions of the solar wind.Flat field processing is indispensable to remove the instrumental non-uniformity of a solar EUV imager in producing high-quality scientific data from original observed data.FengYun-3E(FY-3E)is a meteorological satellite operated in a Sunsynchronous orbit,and the routine EUV imaging data from the Solar X-ray and Extreme Ultraviolet Imager(X-EUVI)onboard FY-3E has the characteristic of concentric rotation.Taking advantage of the concentric rotation,we propose a post-hoc flat field measurement method for its EUV 195A channel in this paper.This method removes the small-scale and time-varying component of coronal activities by taking the median value for each pixel along the time axis of a concentric rotation data cube,and then derives the large-scale and invariable component of the quiet coronal radiation,and finally generates a flat field image.The flat field can be generated with cadences from hundreds of minutes(one orbit)to several days.Higher flat field accuracy can be achieved by employing more data.Further analysis shows that our method is able to measure the instrumental spot-like nonuniformity possibly caused by contamination on the detector,which mostly disappears after the in-orbit selfcleaning process.It can also measure the quasi-periodic grid-like non-uniformity,possibly from the obscuration of the support mesh on the rear filter.After flat field correction,these instrumental non-uniformities from the original data are effectively removed.Moreover,the X-EUVI 195A data after dark and flat field corrections are consistent with the 193A imaging data from the Atmospheric Imaging Assembly onboard the Solar Dynamics Observatory,verifying the suitability of the method.The post-hoc method does not occupy observation time,which is advantageous for space weather operations.Our method is not only suitable for FY-3E/X-EUVI but also a candidate method for the flat field measurement of future solar EUV telescopes.展开更多
Obtaining the wind load distribution on the telescope aperture is very important to estimate its influence and reduce the wind disturbance on the telescope system.The aperture of the radio telescope structure can be a...Obtaining the wind load distribution on the telescope aperture is very important to estimate its influence and reduce the wind disturbance on the telescope system.The aperture of the radio telescope structure can be as large as 100 m and therefore,the uniform wind load on the aperture assumption is not suitable for the radio telescope with large aperture.In this paper,a gradient segments superposition method for calculating the wind load has been proposed.The proposed method has been constructed by combining two regional divisions.First,reflecting surface has been evenly divided in the altitudinal direction.Second,the reflecting surface has been divided into several uniform rings assuming that the wind load coefficient on different rings are different.For the 110 m aperture radio telescope,the wind load estimation results differ by 28%.After that,a structural dynamics model of telescope has been established and a fuzzy PID controller has been designed to reduce wind disturbance.The Root Mean Square Error of telescope pointing under wind disturbance has been reduced by 67.8%.It is suggested that the proposed wind load estimation method has lay a solid foundation for the design of the large telescope system under wind disturbance.展开更多
The abrupt aperiodic modulation of cosmic ray(CR)flux intensity,often referred to as Forbush decrease(FD),plays a significant role in our understanding of the Sun-Earth electrodynamics.Accurate and precise determinati...The abrupt aperiodic modulation of cosmic ray(CR)flux intensity,often referred to as Forbush decrease(FD),plays a significant role in our understanding of the Sun-Earth electrodynamics.Accurate and precise determinations of FD magnitude and timing are among the intractable problems in FD-based analysis.FD identification is complicated by CR diurnal anisotropy.CR anisotropy can increase or reduce the number and amplitude of FDs.It is therefore important to remove its contributions from CR raw data before FD identification.Recently,an attempt was made,using a combination of the Fourier transform technique and FD-location machine,to address this.Thus,two FD catalogs and amplitude diurnal variation(ADV)were calculated from filtered(FD1 and ADV)and raw(FD2)CR data.In the current work,we test the empirical relationship between FD1,FD2,ADV and solar-geophysical characteristics.Our analysis shows that two types of magnetic fields-interplanetary and geomagnetic(Dst)-govern the evolution of CR flux intensity reductions.展开更多
The Mingantu Spectral Radioheliograph(MUSER),a new generation of solar dedicated radio imagingspectroscopic telescope,has realized high-time,high-angular,and high-frequency resolution imaging of the Sun over an ultra-...The Mingantu Spectral Radioheliograph(MUSER),a new generation of solar dedicated radio imagingspectroscopic telescope,has realized high-time,high-angular,and high-frequency resolution imaging of the Sun over an ultra-broadband frequency range.Each pair of MUSER antennas measures the complex visibility in the aperture plane for each integration time and frequency channel.The corresponding radio image for each integration time and frequency channel is then obtained by inverse Fourier transformation of the visibility data.However,the phase of the complex visibility is severely corrupted by instrumental and propagation effects.Therefore,robust calibration procedures are vital in order to obtain high-fidelity radio images.While there are many calibration techniques available—e.g.,using redundant baselines,observing standard cosmic sources,or fitting the solar disk—to correct the visibility data for the above-mentioned phase errors,MUSER is configured with non-redundant baselines and the solar disk structure cannot always be exploited.Therefore it is desirable to develop alternative calibration methods in addition to these available techniques whenever appropriate for MUSER to obtain reliable radio images.In the case where a point-like calibration source contains an unknown position error,we have for the first time derived a mathematical model to describe the problem and proposed an optimization method to calibrate this unknown error by studying the offset of the positions of radio images over a certain period of the time interval.Simulation experiments and actual observational data analyses indicate that this method is valid and feasible.For MUSER’s practical data the calibrated position errors are within the spatial angular resolution of the instrument.This calibration method can also be used in other situations for radio aperture synthesis observations.展开更多
基金supported by the National Natural Science Foundation of China (grant No.12373108)。
文摘The study of carbon-enhanced metal-poor (CEMP) stars is of great significance for understanding the chemical evolution of the early universe and stellar formation.CEMP stars are characterized by carbon overabundance and are classified into several subclasses based on the abundance patterns of neutron-capture elements,including CEMP-s,CEMP-no,CEMP-r,and CEMP-r/s.These subclasses provide important insights into the formation of thefirst stars,early stellar nucleosynthesis,and supernova explosions.However,one of the major challenges in CEMP star research is the relatively small sample size of identified stars,which limits statistical analyses and hinders a comprehensive understanding of their properties.Fortunately,a series of large-scale spectroscopic survey projects have been launched and developed in recent years,providing unprecedented opportunities and technical challenges for the search and study of CEMP stars.To this end,this paper draws on the progress and future prospects of existing methods in constructing large CEMP data sets and offers an in-depth discussion from a technical standpoint,focusing on the strengths and limitations.In addition,we review recent advancements in the identification of CEMP stars,emphasizing the growing role of machine learning in processing and analyzing the increasingly large data sets generated by modern astronomical surveys.Compared to traditional spectral analysis methods,machine learning offers greater efficiency in handling complex data,automatic extraction of stellar parameters,and improved prediction accuracy.Despite these advancements,the research faces persistent challenges,including the scarcity of labeled samples,limitations imposed by low-resolution spectra,and the lack of interpretability in machine learning models.To address these issues,the paper proposes potential solutions and future research directions aimed at advancing the study of CEMP stars and enhancing our understanding of their role in the chemical evolution of the universe.
文摘The recent surge in computer vision and deep learning has attracted significant attention within the galaxy morphology community.Various models have been implemented for galaxy morphology prediction with nearperfect accuracy for certain classes.However,many studies treat deep learning models as black-box entities,lacking interpretability of their predictions.To address these limitations while ensuring good performance,we introduced an Improved SqueezeNet(I-SqueezeNet)by incorporating unique residual connections to improve the prediction performance,and we utilize Local Interpretable Model-Agnostic Explanations(LIME)to understand the interpretability.We evaluated the simplified SqueezeNet and I-SqueezeNet,with both channel and vertical concatenation,and compared their performances with those of some exiting methods such as Dieleman’s CNN,VGG13,DenseNet121,ResNet50,ResNext50,ResNext101,DSCNN and customized CNN in classifying galaxy objects using a dataset from the publicly available Galaxy Zoo Data Challenge Project.Our experiments showed that I-SqueezeNet with vertical concatenation achieved the highest average accuracy of 94.08%compared to other methods.Beyond achieving high accuracy,the application of LIME for model interpretation sheds light on the machine learning features and reasoning processes behind the model’s predictions.This information provides valuable insight into the galaxy morphology decision-making process,paving the way for further functional enhancements.
基金supported by the National Key Research and Development Program of China under grant No.2018YFA0404603supported by the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China (MOF) and administered by the Chinese Academy of Sciences (CAS)。
文摘Pulsar candidate identification is an indispensable task in pulsar science.Based on the characteristics of imbalanced and diverse pulsar data sets,and the lack of a unified processing framework,we first used dimensionality reduction and visualization to analyze potential deficiencies caused by the incompleteness of current data set extraction methods.We found that the limited use of non-pulsar data may lead to bias in the result,which may limit the generalization ability.Based on the dimensionality reduction results,we propose a Grid Group Uniform Sampling(GGUS) method.This data preprocessing method improves the performance of Random Forest,Support Vector Machine,Convolutional Neural Network,and Res Net50 models on Lyon’s features,diagnostic plots,and perioddispersion measure (period-DM) plots in the HTRU1 data set.The average recall increased by approximately0.5%,precision by nearly 2%,and F_(1) score by around 1.2%for all models and in all data sets.In the period-DM plots testing,the high-performance Res Net50 algorithm achieved over 98%F_(1) using random sampling.GGUS demonstrated further improvements in this test,enhancing the average F_(1) score,precision,and recall by approximately 0.07%,0.1%,and 0.03%,respectively.
基金supported by the Chinese Academy of Sciences(CAS)“Light of West China”Program(No.2022-XBQNXZ-015)the National Natural Science Foundation of China(NSFC,grant No.11903071)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance(MOF)of China and administered by the Chinese Academy of Sciences(CAS)。
文摘Fast radio bursts(FRBs)are among the most studied radio transients in astrophysics,but their origin and radiation mechanism are still unknown.It is a challenge to search for FRB events in a huge amount of observational data with high speed and high accuracy.With the rapid advancement of the FRB research process,FRB searching has changed from archive data mining to either long-term monitoring of the repeating FRBs or all-sky surveys with specialized equipments.Therefore,establishing a highly efficient and high quality FRB search pipeline is the primary task in FRB research.Deep learning techniques provide new ideas for FRB search processing.We have detected radio bursts from FRB 20201124A in the L-band observational data of the Nanshan 26 m radio telescope(NSRT-26m)using the constructed deep learning based search pipeline named dispersed dynamic spectra search(DDSS).Afterwards,we further retrained the deep learning model and applied the DDSS framework to S-band observations.In this paper,we present the FRB observation system and search pipeline using the S-band receiver.We carried out search experiments,and successfully detected the radio bursts from the magnetar SGR J1935+2145and FRB 20220912A.The experimental results show that the search pipeline can complete the search efficiently and output the search results with high accuracy.
基金supported by Open Fund of State Key Laboratory of Infrared Physics,Shanghai Institute of Technical Physics,Chinese Academy of Sciences。
文摘Radiation pattern captures the electromagnetic performance of reflector antennas,which is significantly affected by the deformation of the primary reflector due to gravity and the displacement of the secondary reflector.During the design process of large reflector antennas,a substantial amount of time is often dedicated to iteratively adjusting structural parameters and validating electromagnetic performance.To improve the efficiency of the design process,we first propose an approximate calculation method of optical path difference(OPD)for the deformation of the primary reflector under gravity and the displacement of the secondary reflector.Then an OPD fitting function based on the modified Zernike polynomials is proposed to capture the phase difference of radiation over the aperture plane,based on which the radiation pattern will be obtained quickly by the aperture field integration method.Numerical experiments demonstrate the effectiveness of the proposed quick calculation method for analyzing the radiation pattern of a 10.4 m submillimeter telescope antenna at its highest operating frequency of 856 GHz.In comparison with the numerical simulation method based on GRASP(which is an antenna electromagnetic analysis tool combining physical optics(PO)and physical theory of diffraction(PTD)),the quick calculation method reduces the time for radiation pattern analysis from more than one hour to less than two minutes.Furthermore,the quick calculation method exhibits excellent accuracy for the figure of merit(FOM)of the radiation pattern.Therefore,the proposed quick calculation method can obtain the radiation pattern with high speed and accuracy.Compared to the time-consuming numerical simulation method(PO and PTD),it can be employed for quick analysis of the radiation pattern for the lateral displacement of the secondary reflector and the deformation of the primary reflector under gravity in the design process of a reflector antenna.
基金supported in China by NSFC grant No.12393853the Department of Science and Technology of Sichuan Province China with grant No.24NSFSC0449NSFC grant No.U2031205。
文摘With its high duty cycle, wide field of view and high detection sensitivity, Water Chereknov Detector Array as one of sub-arrays of Large High Altitude Air Shower Observatory is a promising facility to monitor transient phenomena in the very high energy gamma-ray band. In this work, a real-time monitor for selected TeV extragalactic sources is introduced, this flare monitor is developed to detect very high energy flare events and for further studying the power-providing mechanism of blazar relativistic jets. The detailed information such as the searching method and sensitivity of this real-time flare monitor is also presented. In the end, successful multiwavelength and multi-messenger observation of 1ES 1959+650 and IC 310 also confirms the capabilities and reliability of the monitoring system.
基金supported in part by the National Natural Science Foundation of China(NSFC)(U2031129 and 12003052)Youth Innovation Promotion Association of the Chinese Academy of Sciences(2018079)。
文摘Ground-based optical observation has unique advantages in space target observation.However,due to the weak light-gathering ability of small-aperture optoelectronic observation telescopes,the space debris in the image is weak and easily drowned in noise.In order to solve the above problems,we use digital image processing technology to extract faint space debris.We propose a high detection rate space debris automatic extraction algorithm,aiming to automatically detect space debris.We first establish a new space target description model.Our algorithm is mainly divided into two stages.The purpose of the first stage is to reduce the influence of a large number of stars.We perform wavelet transform and guided filtering for three consecutive frames,and the reconstructed wavelet that takes the median value can achieve the effect of eliminating stars.In the second stage,we adopt the method of robust principal component analysis and attribute the problem of target detection to the problem of separating the target and background of a single frame of image.After a large number of experimental results analysis,it is proved that the algorithm can effectively detect faint debris in the monitoring system of small aperture telescope,and has high precision and low computational complexity.
基金supported by the National Natural Science Foundation of China (Grant No. 11903071)the Operation, Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments, budgeted from the Ministry of Finance (MOF) of China and administered by the Chinese Academy of Sciences (CAS)。
文摘The origin and phenomenology of Fast Radio Bursts(FRBs) remain unknown. Fast and efficient search technology for FRBs is critical for triggering immediate multi-wavelength follow-up and voltage data dump. This paper proposes a dispersed dynamic spectra search(DDSS) pipeline for FRB searching based on deep learning, which performs the search directly from observational raw data, rather than relying on generated FRB candidates from single-pulse search algorithms that are based on de-dispersion. We train our deep learning network model using simulated FRBs as positive and negative samples extracted from the observational data of the Nanshan 26 m radio telescope(NSRT)at Xinjiang Astronomical Observatory. The observational data of PSR J1935+1616 are fed into the pipeline to verify the validity and performance of the pipeline. Results of the experiment show that our pipeline can efficiently search single-pulse events with a precision above 99.6%, which satisfies the desired precision for selective voltage data dump. In March 2022, we successfully detected the FRBs emanating from the repeating case of FRB 20201124A with the DDSS pipeline in L-band observations using the NSRT. The DDSS pipeline shows excellent sensitivity in identifying weak single pulses, and its high precision greatly reduces the need for manual review.
基金the National Natural Science Foundation of China (Grant Nos. 10973025 and 10833004)
文摘A 30-m TeraHertz（THz） radio telescope is proposed to operate at 200 μm with an active primary surface.This paper presents sensitivity analysis of active surface panel positioning errors with optical performance in terms of the Strehl ratio.Based on Ruze＇s surface error theory and using a Monte Carlo simulation,the effects of six rigid panel positioning errors,such as piston,tip,tilt,radial,azimuthal and twist displacements,were directly derived.The optical performance of the telescope was then evaluated using the standard Strehl ratio.We graphically illustrated the various panel error effects by presenting simulations of complete ensembles of full reflector surface errors for the six different rigid panel positioning errors.Study of the panel error sensitivity analysis revealed that the piston error and tilt/tip errors are dominant while the other rigid errors are much less important.Furthermore,as indicated by the results,we conceived of an alternative Master-Slave Concept-based（MSC-based） active surface by implementating a special Series-Parallel Concept-based（SPC-based） hexapod as the active panel support mechanism.A new 30-m active reflector based on the two concepts was demonstrated to achieve correction for all the six rigid panel positioning errors in an economically feasible way.
基金supported by the National Key R&D Program of China(2021YFA0718600)the National Natural Science Foundations of China(NSFC,Grant Nos.41931073,41774195)+2 种基金Ten-thousand Talents Program of JingSong Wang,and the Specialized Research Fund for State Key Laboratoriessupported by the Strategic Priority Research Program of the Chinese Academy of Sciences,Grant No.XDA 15018400supported by the China Postdoctoral Science Foundation(2021M700246)。
文摘Extreme ultraviolet(EUV)observations are widely used in solar activity research and space weather forecasting since they can observe both the solar eruptions and the source regions of the solar wind.Flat field processing is indispensable to remove the instrumental non-uniformity of a solar EUV imager in producing high-quality scientific data from original observed data.FengYun-3E(FY-3E)is a meteorological satellite operated in a Sunsynchronous orbit,and the routine EUV imaging data from the Solar X-ray and Extreme Ultraviolet Imager(X-EUVI)onboard FY-3E has the characteristic of concentric rotation.Taking advantage of the concentric rotation,we propose a post-hoc flat field measurement method for its EUV 195A channel in this paper.This method removes the small-scale and time-varying component of coronal activities by taking the median value for each pixel along the time axis of a concentric rotation data cube,and then derives the large-scale and invariable component of the quiet coronal radiation,and finally generates a flat field image.The flat field can be generated with cadences from hundreds of minutes(one orbit)to several days.Higher flat field accuracy can be achieved by employing more data.Further analysis shows that our method is able to measure the instrumental spot-like nonuniformity possibly caused by contamination on the detector,which mostly disappears after the in-orbit selfcleaning process.It can also measure the quasi-periodic grid-like non-uniformity,possibly from the obscuration of the support mesh on the rear filter.After flat field correction,these instrumental non-uniformities from the original data are effectively removed.Moreover,the X-EUVI 195A data after dark and flat field corrections are consistent with the 193A imaging data from the Atmospheric Imaging Assembly onboard the Solar Dynamics Observatory,verifying the suitability of the method.The post-hoc method does not occupy observation time,which is advantageous for space weather operations.Our method is not only suitable for FY-3E/X-EUVI but also a candidate method for the flat field measurement of future solar EUV telescopes.
基金the National Key Research and Development Program of China under No.2021YFC2203600the National Natural Science Foundation of China under Nos.52005377 and 52275268+2 种基金the National Defense Basic Scientific Research Program of China under No.JCKY2021210B007Wuhu and Xidian University Special Fund for Industry-University-Research Cooperation under No.XWYCXY-012021012Youth Innovation Team of Shaanxi Universities under No.201926.
文摘Obtaining the wind load distribution on the telescope aperture is very important to estimate its influence and reduce the wind disturbance on the telescope system.The aperture of the radio telescope structure can be as large as 100 m and therefore,the uniform wind load on the aperture assumption is not suitable for the radio telescope with large aperture.In this paper,a gradient segments superposition method for calculating the wind load has been proposed.The proposed method has been constructed by combining two regional divisions.First,reflecting surface has been evenly divided in the altitudinal direction.Second,the reflecting surface has been divided into several uniform rings assuming that the wind load coefficient on different rings are different.For the 110 m aperture radio telescope,the wind load estimation results differ by 28%.After that,a structural dynamics model of telescope has been established and a fuzzy PID controller has been designed to reduce wind disturbance.The Root Mean Square Error of telescope pointing under wind disturbance has been reduced by 67.8%.It is suggested that the proposed wind load estimation method has lay a solid foundation for the design of the large telescope system under wind disturbance.
文摘The abrupt aperiodic modulation of cosmic ray(CR)flux intensity,often referred to as Forbush decrease(FD),plays a significant role in our understanding of the Sun-Earth electrodynamics.Accurate and precise determinations of FD magnitude and timing are among the intractable problems in FD-based analysis.FD identification is complicated by CR diurnal anisotropy.CR anisotropy can increase or reduce the number and amplitude of FDs.It is therefore important to remove its contributions from CR raw data before FD identification.Recently,an attempt was made,using a combination of the Fourier transform technique and FD-location machine,to address this.Thus,two FD catalogs and amplitude diurnal variation(ADV)were calculated from filtered(FD1 and ADV)and raw(FD2)CR data.In the current work,we test the empirical relationship between FD1,FD2,ADV and solar-geophysical characteristics.Our analysis shows that two types of magnetic fields-interplanetary and geomagnetic(Dst)-govern the evolution of CR flux intensity reductions.
基金supported by NSFC grants(11790301,11790305,11773043,U2031134,and 12003049)the National Key R&D Program of China(2021YFA1600500,2021YFA1600503,and 2018YFA0404602)+1 种基金supported by the National Major Scientific Research Facility Program of China with the Grant No.ZDYZ2009-3The MUSER calibration system is a part of the Chinese Meridian Project funded by China’s National Development and Reform Commission。
文摘The Mingantu Spectral Radioheliograph(MUSER),a new generation of solar dedicated radio imagingspectroscopic telescope,has realized high-time,high-angular,and high-frequency resolution imaging of the Sun over an ultra-broadband frequency range.Each pair of MUSER antennas measures the complex visibility in the aperture plane for each integration time and frequency channel.The corresponding radio image for each integration time and frequency channel is then obtained by inverse Fourier transformation of the visibility data.However,the phase of the complex visibility is severely corrupted by instrumental and propagation effects.Therefore,robust calibration procedures are vital in order to obtain high-fidelity radio images.While there are many calibration techniques available—e.g.,using redundant baselines,observing standard cosmic sources,or fitting the solar disk—to correct the visibility data for the above-mentioned phase errors,MUSER is configured with non-redundant baselines and the solar disk structure cannot always be exploited.Therefore it is desirable to develop alternative calibration methods in addition to these available techniques whenever appropriate for MUSER to obtain reliable radio images.In the case where a point-like calibration source contains an unknown position error,we have for the first time derived a mathematical model to describe the problem and proposed an optimization method to calibrate this unknown error by studying the offset of the positions of radio images over a certain period of the time interval.Simulation experiments and actual observational data analyses indicate that this method is valid and feasible.For MUSER’s practical data the calibrated position errors are within the spatial angular resolution of the instrument.This calibration method can also be used in other situations for radio aperture synthesis observations.
