The double revolving fiber positioning technology employed in the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST)represents one of the most successful advancements in large-scale multiobjective spect...The double revolving fiber positioning technology employed in the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST)represents one of the most successful advancements in large-scale multiobjective spectroscopy.The precision of fiber positioning is crucial,as it directly impacts the observational efficiency of LAMOST.A critical component of the fiber positioning system is the closed-loop control system,which traditionally utilizes the light spot generated at fiber end.However,this study introduces a novel approach based on front-illuminated LAMOST focal plane image measurements.Unlike back-illumination,front-illumination does not necessitate internal lighting in the spectrograph,thus reducing light pollution and eliminating the need for additional photography.This method employs an artificial intelligence model to analyze images captured at the focal plane unit(FPU),using the image of the white ceramic head on the FPU as the data set for training,the model is capable of accurately measuring the fiber positions solely through front-illumination.Preliminary trials indicate that the measurement accuracy achieved using the frontillumination method is approximately 0."13.This level of precision meets the stringent fiber positioning accuracy requirement of LAMOST,set at 0."2.Furthermore,this novel approach demonstrates compatibility with LAMOST’s existing closed-loop fiber control system,offering potential for seamless integration and enhanced operational efficiency.展开更多
Our knowledge of galaxy creation and evolution has significantly improved in recent years because of the substantial advancements made in the classification of galaxy morphology using machine learning techniques.Never...Our knowledge of galaxy creation and evolution has significantly improved in recent years because of the substantial advancements made in the classification of galaxy morphology using machine learning techniques.Nevertheless,the vast amount of unlabeled astronomical image data restricts the application of these techniques,and it is expensive to manually label enormous volumes of astronomical data.Current semi-supervised approaches have used pseudo-labeling and consistency regularization to get good results.However,many pseudo-labels are underutilized because of their excessively high confidence levels.Furthermore,confirmation bias in the model may result from the overconfidence commonly seen in softmax outputs,which is usually disregarded in current research.In order to decrease confirmation bias throughout the learning process,this study introduces uncertainty quantification.Specifically,the suggested approach fully utilizes pseudo-labeled data by using distinct training procedures according to different confidence levels.This method lowers errors brought on by the model’s overconfidence while simultaneously improving the quality of pseudo-labels.Results from experiments show that our approach performs well on the Galaxy Zoo 2 data set and the Galaxy10 DECaLS data set.In particular,our approach obtains an accuracy of 76.8%on the Galaxy10 DECaLS data set,which contains 2000 labeled samples,while fully supervised approaches only achieve 70.8%.In comparison to the supervised approach,our strategy lowers the error rate by 32.34%for the 1000 labeled samples in the Galaxy Zoo 2 data set.Our method accomplishes accurate categorization of galaxy morphology by using a large amount of unlabeled data and a small amount of labeled data.The public can get the source code at https://github.com/CZSGC/SSLGMCBDEUE.展开更多
Quantitative and analytical analysis of the modulation process of the collimator is a great challenge,and is also of great value to the design and development of Fourier transform imaging telescopes.The Hard X-ray Ima...Quantitative and analytical analysis of the modulation process of the collimator is a great challenge,and is also of great value to the design and development of Fourier transform imaging telescopes.The Hard X-ray Imager(HXI),as one of the three payloads onboard the Advanced Space-based Solar Observatory(ASO-S) mission,adopts modulating Fourier-Transformation imaging technique and will be used to explore the mechanism of energy release and transmission in solar flare activities.As an important step to reconstruct the images of solar flares,accurate modulation functions of HXI are needed.In this paper,a mathematical model is developed to analyze the modulation function under a simplified condition first.Then its behavior under six degrees of freedom is calculated after adding the rotation matrix and translation change to the model.In addition,unparalleled light and extended sources are also considered so that our model can be used to analyze the X-ray beam experiment.Next,applied to the practical HXI conditions,the model has been confirmed not only by Geant4 simulations but also by some verification experiments.Furthermore,how this model helps to improve the image reconstruction process after the launch of ASO-S is also presented.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
The Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST)has been in normal operation for more than 10 yr,and routine maintenance is performed on the fiber positioner every summer.The positioning accuracy ...The Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST)has been in normal operation for more than 10 yr,and routine maintenance is performed on the fiber positioner every summer.The positioning accuracy of the fiber positioner directly affects the observation performance of LAMOST,and incorrect fiber positioner positioning accuracy will not only increase the interference probability of adjacent fiber positioners but also reduces the observation efficiency of LAMOST.At present,during the manual maintenance process of the positioner,the fault cause of the positioner is determined and analyzed when the positioning accuracy does not meet the preset requirements.This causes maintenance to take a long time,and the efficiency is low.To quickly locate the fault cause of the positioner,the repeated positioning accuracy and open-loop calibration curve data of each positioner are obtained in this paper through the photographic measurement method.Based on a systematic analysis of the operational characteristics of the faulty positioner,the fault causes are classified.After training a deep learning model based on long short-term memory,the positioner fault causes can be quickly located to effectively improve the efficiency of positioner fault cause analysis.The relevant data can also provide valuable information for annual routine maintenance methods and positioner designs in the future.The method of using a deep learning model to analyze positioner operation failures introduced in this paper is also of general significance for the maintenance and design optimization of fiber positioners using a similar double-turn gear transmission system.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
Accurate flux density calibration is essential for precise analysis and interpretation of observations across different observation modes and instruments.In this research,we first introduce the flux calibration model ...Accurate flux density calibration is essential for precise analysis and interpretation of observations across different observation modes and instruments.In this research,we first introduce the flux calibration model that incorporated in Hi FAST pipeline,and designed for processing HⅠ21 cm spectra.Furthermore,we investigate different calibration techniques and assess the dependence of the gain parameter on the time and environmental factors.A comparison is carried out in various observation modes(e.g.,tracking and scanning modes)to determine the flux density gain(G),revealing insignificant discrepancies in G among different methods.Long-term monitoring data shows a linear correlation between G and atmospheric temperature.After subtracting the G-Temperature dependence,the dispersion of G is reduced to<3%over a one-year timescale.The stability of the receiver response of Five-hundred-meter Aperture Spherical radio Telescope(FAST)is considered sufficient to facilitate HⅠobservations that can accommodate a moderate error in flux calibration(e.g.,>~5%)when utilizing a constant G for calibration purposes.Our study will serve as a useful addition to the results provided by Jiang et al.Detailed measurement of G for the 19 beams of FAST,covering the frequency range 1000-1500 MHz,can be found on the Hi FAST homepage:https://hifast.readthedocs.io/fluxgain.展开更多
To date,the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST)has been in operation for 12 yr.To improve the telescope's astronomical observation accuracy,the original open-loop fiber positioning sy...To date,the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST)has been in operation for 12 yr.To improve the telescope's astronomical observation accuracy,the original open-loop fiber positioning system of LAMOST is in urgent need of upgrading.The upgrade plan is to install several fiber view cameras(FVCs)around primary mirror B to build a closed-loop feedback control system.The FVCs are 20 m from the focal surface.To reduce a series of errors when the cameras detect the positions of the optical fibers,we designed fiducial fibers on the focal surface to be fiducial points for the cameras.Increasing the number of fiducial fibers can improve the detection accuracy of the FVC system,but it will also certainly reduce the number of fiber positioners that can be used for observation.Therefore,the focus of this paper is how to achieve the quantity and distribution that meet the requirements of system detection.In this paper,we introduce the necessity of using fiducial fibers,propose a method for selecting their number and present several methods for assessing the uniformity of their distribution.Finally,we implement particle swarm optimization to find the best distribution of fiducial fibers.展开更多
The double revolving fiber positioning technology is one of the key technologies for the success of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST).The accuracy of fiber positioning will directly...The double revolving fiber positioning technology is one of the key technologies for the success of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST).The accuracy of fiber positioning will directly affect the observation efficiency of LAMOST.To achieve higher fiber positioning accuracy,the original open-loop controlled fiber positioning system urgently needs to be upgraded into a closed-loop control system.The fiber detection is the most important part of the closed-loop controlled fiber positioning system.The back-illuminated detection method is usually used to detect the fiber position by directly detecting the light spot generated at the fiber end in the multi-fiber spectral surveys.In this paper,we introduce a new method to measure the fiber position based on the image of the front-illuminated LAMOST focal plane.The front-illuminated image does not require lighting devices inside the spectrograph,and it could reduce the instability and light pollution in the spectrograph end.Our method measures the fiber position by fitting the profile of the fiber pinhole with a 2D Gaussian function.A series of tests show that the relative position measurement precision of the front-illuminated method is about 012,and the method could have the same accuracy as the back-illuminated method once the system bias is calibrated by a simple radial correction function.The required fiber positioning accuracy of LAMOST is 04,and the new method satisfies the requirement of LAMOST fiber detection accuracy and could be used in the closed-loop fiber control system.展开更多
基金supported by NSFC under grant Nos.12073046 and 12261141689the project has been provided by the National Development and Reform Commission.
文摘The double revolving fiber positioning technology employed in the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST)represents one of the most successful advancements in large-scale multiobjective spectroscopy.The precision of fiber positioning is crucial,as it directly impacts the observational efficiency of LAMOST.A critical component of the fiber positioning system is the closed-loop control system,which traditionally utilizes the light spot generated at fiber end.However,this study introduces a novel approach based on front-illuminated LAMOST focal plane image measurements.Unlike back-illumination,front-illumination does not necessitate internal lighting in the spectrograph,thus reducing light pollution and eliminating the need for additional photography.This method employs an artificial intelligence model to analyze images captured at the focal plane unit(FPU),using the image of the white ceramic head on the FPU as the data set for training,the model is capable of accurately measuring the fiber positions solely through front-illumination.Preliminary trials indicate that the measurement accuracy achieved using the frontillumination method is approximately 0."13.This level of precision meets the stringent fiber positioning accuracy requirement of LAMOST,set at 0."2.Furthermore,this novel approach demonstrates compatibility with LAMOST’s existing closed-loop fiber control system,offering potential for seamless integration and enhanced operational efficiency.
基金supported by the National Natural Science Foundation of China(NSFC,grant No.62201398)the Open Project of Center for Applied Mathematics of Jiangsu Province(Nanjing University of Information Science and Technology).
文摘Our knowledge of galaxy creation and evolution has significantly improved in recent years because of the substantial advancements made in the classification of galaxy morphology using machine learning techniques.Nevertheless,the vast amount of unlabeled astronomical image data restricts the application of these techniques,and it is expensive to manually label enormous volumes of astronomical data.Current semi-supervised approaches have used pseudo-labeling and consistency regularization to get good results.However,many pseudo-labels are underutilized because of their excessively high confidence levels.Furthermore,confirmation bias in the model may result from the overconfidence commonly seen in softmax outputs,which is usually disregarded in current research.In order to decrease confirmation bias throughout the learning process,this study introduces uncertainty quantification.Specifically,the suggested approach fully utilizes pseudo-labeled data by using distinct training procedures according to different confidence levels.This method lowers errors brought on by the model’s overconfidence while simultaneously improving the quality of pseudo-labels.Results from experiments show that our approach performs well on the Galaxy Zoo 2 data set and the Galaxy10 DECaLS data set.In particular,our approach obtains an accuracy of 76.8%on the Galaxy10 DECaLS data set,which contains 2000 labeled samples,while fully supervised approaches only achieve 70.8%.In comparison to the supervised approach,our strategy lowers the error rate by 32.34%for the 1000 labeled samples in the Galaxy Zoo 2 data set.Our method accomplishes accurate categorization of galaxy morphology by using a large amount of unlabeled data and a small amount of labeled data.The public can get the source code at https://github.com/CZSGC/SSLGMCBDEUE.
基金supported by the Strategic Priority Research Program on Space ScienceChinese Academy of Sciences(No.XDA 15320104)+2 种基金the Scientific Instrument Developing Project of the Chinese Academy of Sciences(Grant No.YJKYYQ20200077)the National Natural Science Foundation of China(Nos.12173100,12022302,11803093 and 11973097)the Youth Innovation Promotion Association,CAS(No.2021317 and Y2021087)。
文摘Quantitative and analytical analysis of the modulation process of the collimator is a great challenge,and is also of great value to the design and development of Fourier transform imaging telescopes.The Hard X-ray Imager(HXI),as one of the three payloads onboard the Advanced Space-based Solar Observatory(ASO-S) mission,adopts modulating Fourier-Transformation imaging technique and will be used to explore the mechanism of energy release and transmission in solar flare activities.As an important step to reconstruct the images of solar flares,accurate modulation functions of HXI are needed.In this paper,a mathematical model is developed to analyze the modulation function under a simplified condition first.Then its behavior under six degrees of freedom is calculated after adding the rotation matrix and translation change to the model.In addition,unparalleled light and extended sources are also considered so that our model can be used to analyze the X-ray beam experiment.Next,applied to the practical HXI conditions,the model has been confirmed not only by Geant4 simulations but also by some verification experiments.Furthermore,how this model helps to improve the image reconstruction process after the launch of ASO-S is also presented.
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.
基金Funding for the research was provided by Cui Xiangqun’s Academician StudioFunding for the project has been provided by the National Development and Reform Commission。
文摘The Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST)has been in normal operation for more than 10 yr,and routine maintenance is performed on the fiber positioner every summer.The positioning accuracy of the fiber positioner directly affects the observation performance of LAMOST,and incorrect fiber positioner positioning accuracy will not only increase the interference probability of adjacent fiber positioners but also reduces the observation efficiency of LAMOST.At present,during the manual maintenance process of the positioner,the fault cause of the positioner is determined and analyzed when the positioning accuracy does not meet the preset requirements.This causes maintenance to take a long time,and the efficiency is low.To quickly locate the fault cause of the positioner,the repeated positioning accuracy and open-loop calibration curve data of each positioner are obtained in this paper through the photographic measurement method.Based on a systematic analysis of the operational characteristics of the faulty positioner,the fault causes are classified.After training a deep learning model based on long short-term memory,the positioner fault causes can be quickly located to effectively improve the efficiency of positioner fault cause analysis.The relevant data can also provide valuable information for annual routine maintenance methods and positioner designs in the future.The method of using a deep learning model to analyze positioner operation failures introduced in this paper is also of general significance for the maintenance and design optimization of fiber positioners using a similar double-turn gear transmission system.
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 support of the China National Key Program for Science and Technology Research and Development of China(2022YFA1602901,2023YFA1608204)the National Natural Science Foundation of China(Nos.11988101,11873051,12125302,12373011,12041305,12173016)the CAS Project for Young Scientists in Basic Research grant(No.YSBR-062)。
文摘Accurate flux density calibration is essential for precise analysis and interpretation of observations across different observation modes and instruments.In this research,we first introduce the flux calibration model that incorporated in Hi FAST pipeline,and designed for processing HⅠ21 cm spectra.Furthermore,we investigate different calibration techniques and assess the dependence of the gain parameter on the time and environmental factors.A comparison is carried out in various observation modes(e.g.,tracking and scanning modes)to determine the flux density gain(G),revealing insignificant discrepancies in G among different methods.Long-term monitoring data shows a linear correlation between G and atmospheric temperature.After subtracting the G-Temperature dependence,the dispersion of G is reduced to<3%over a one-year timescale.The stability of the receiver response of Five-hundred-meter Aperture Spherical radio Telescope(FAST)is considered sufficient to facilitate HⅠobservations that can accommodate a moderate error in flux calibration(e.g.,>~5%)when utilizing a constant G for calibration purposes.Our study will serve as a useful addition to the results provided by Jiang et al.Detailed measurement of G for the 19 beams of FAST,covering the frequency range 1000-1500 MHz,can be found on the Hi FAST homepage:https://hifast.readthedocs.io/fluxgain.
基金Funding for the research was provided by Cui Xiangqun’s Academician StudioGuoshoujing Telescope(the Large Sky Area Multi-Object Fiber Spectroscopic Telescope,LAMOST)is a National Major Scientific Project built by the Chinese Academy of SciencesFunding for the project has been provided by the National Development and Reform Commission。
文摘To date,the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST)has been in operation for 12 yr.To improve the telescope's astronomical observation accuracy,the original open-loop fiber positioning system of LAMOST is in urgent need of upgrading.The upgrade plan is to install several fiber view cameras(FVCs)around primary mirror B to build a closed-loop feedback control system.The FVCs are 20 m from the focal surface.To reduce a series of errors when the cameras detect the positions of the optical fibers,we designed fiducial fibers on the focal surface to be fiducial points for the cameras.Increasing the number of fiducial fibers can improve the detection accuracy of the FVC system,but it will also certainly reduce the number of fiber positioners that can be used for observation.Therefore,the focus of this paper is how to achieve the quantity and distribution that meet the requirements of system detection.In this paper,we introduce the necessity of using fiducial fibers,propose a method for selecting their number and present several methods for assessing the uniformity of their distribution.Finally,we implement particle swarm optimization to find the best distribution of fiducial fibers.
基金supported by the Maintenance and renovation project of Major Science and Technology foundational facility of the Chinese Academy of Sciences,DSS-WXGZ-2020-0009 and DSS-WXGZ-2021-0004the support of the National Key R&D Program of China(2019YFA0405000)+3 种基金NFSC 12090041,U1931207,U2031207 and U1931126the support of the National Natural Science for Youth Foundation of China(No.11603043)Guo Shou Jing Telescope(the Large sky Area Multi-Object fiber Spectroscopic Telescope,LAMOST)is a National Major Scientific Project built by the Chinese Academy of Sciences.Funding for the project has been provided by the National Development and Reform CommissionLAMOST is operated and managed by the National Astronomical Observatories,Chinese Academy of Sciences。
文摘The double revolving fiber positioning technology is one of the key technologies for the success of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST).The accuracy of fiber positioning will directly affect the observation efficiency of LAMOST.To achieve higher fiber positioning accuracy,the original open-loop controlled fiber positioning system urgently needs to be upgraded into a closed-loop control system.The fiber detection is the most important part of the closed-loop controlled fiber positioning system.The back-illuminated detection method is usually used to detect the fiber position by directly detecting the light spot generated at the fiber end in the multi-fiber spectral surveys.In this paper,we introduce a new method to measure the fiber position based on the image of the front-illuminated LAMOST focal plane.The front-illuminated image does not require lighting devices inside the spectrograph,and it could reduce the instability and light pollution in the spectrograph end.Our method measures the fiber position by fitting the profile of the fiber pinhole with a 2D Gaussian function.A series of tests show that the relative position measurement precision of the front-illuminated method is about 012,and the method could have the same accuracy as the back-illuminated method once the system bias is calibrated by a simple radial correction function.The required fiber positioning accuracy of LAMOST is 04,and the new method satisfies the requirement of LAMOST fiber detection accuracy and could be used in the closed-loop fiber control system.
