As the performance of dedicated facilities has continually improved, large numbers of pulsar candidates are being received, which makes selecting valuable pulsar signals from the candidates challenging. In this paper,...As the performance of dedicated facilities has continually improved, large numbers of pulsar candidates are being received, which makes selecting valuable pulsar signals from the candidates challenging. In this paper, we describe the design for a deep convolutional neural network(CNN) with 11 layers for classifying pulsar candidates. Compared to artificially designed features, the CNN chooses the subintegrations plot and sub-bands plot for each candidate as inputs without carrying biases. To address the imbalance problem, a data augmentation method based on synthetic minority samples is proposed according to the characteristics of pulsars. The maximum pulses of pulsar candidates were first translated to the same position, and then new samples were generated by adding up multiple subplots of pulsars. The data augmentation method is simple and effective for obtaining varied and representative samples which keep pulsar characteristics. In experiments on the HTRU 1 dataset, it is shown that this model can achieve recall of 0.962 and precision of 0.963.展开更多
Reviewing the empirical and theoretical parameter relationships between various parameters is a good way to understand more about contact binary systems.In this investigation,two-dimensional(2D)relationships for P–MV...Reviewing the empirical and theoretical parameter relationships between various parameters is a good way to understand more about contact binary systems.In this investigation,two-dimensional(2D)relationships for P–MV(system),P–L1,2,M1,2–L1,2,and q–Lratiowere revisited.The sample used is related to 118 contact binary systems with an orbital period shorter than 0.6 days whose absolute parameters were estimated based on the Gaia Data Release 3 parallax.We reviewed previous studies on 2D relationships and updated six parameter relationships.Therefore,Markov chain Monte Carlo and Machine Learning methods were used,and the outcomes were compared.We selected 22 contact binary systems from eight previous studies for comparison,which had light curve solutions using spectroscopic data.The results show that the systems are in good agreement with the results of this study.展开更多
With the availability of multi-object spectrometers and the design and operation of some large scale sky surveys, the issue of how to deal with enormous quantities of spectral data efficiently and accurately is becomi...With the availability of multi-object spectrometers and the design and operation of some large scale sky surveys, the issue of how to deal with enormous quantities of spectral data efficiently and accurately is becoming more and more important. This work investigates the classification problem of stellar spectra under the assumption that there is no perfect absolute flux calibration, for example, when considering spectra from the Guo Shou Jing Telescope(the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, LAMOST). The proposed scheme consists of the following two procedures: Firstly, a spectrum is normalized based on a 17 th order polynomial fitting;secondly, a random forest(RF) is utilized to classify the stellar spectra. Experiments on four stellar spectral libraries show that the RF has good classification performance. This work also studied the spectral feature evaluation problem based on RF. The evaluation is helpful in understanding the results of the proposed stellar classification scheme and exploring its potential improvements in the future.展开更多
We have conducted a comprehensive investigation into the bright single pulse emission from PSR B1133+16using the Giant Metrewave Radio Telescope.High time resolution data(61μs)were obtained at a center frequency of 3...We have conducted a comprehensive investigation into the bright single pulse emission from PSR B1133+16using the Giant Metrewave Radio Telescope.High time resolution data(61μs)were obtained at a center frequency of 322 MHz with a bandwidth of 32 MHz over a continuous observation period of 7.45 hr.A total of 1082 bright pulses were sporadically detected with peak flux densities ranging from 10 to 23 times stronger than the average pulse profile.However,no giant pulse-like emission with a relative pulse energy larger than 10 and extremely short duration was detected,indicating that these bright pulses cannot be categorized as giant pulse emission.The majority of these bright pulses are concentrated in pulse phases at both the leading and trailing windows of the average pulse profile,with an occurrence ratio of approximately 2.74.The pulse energy distribution for all individual pulses can be described by a combination of two Gaussian components and a cutoff power-law with an index of α=-3.2.An updated nulling fraction of 15.35%±0.45% was determined from the energy distribution.The emission of individual pulses follows a log-normal distribution in peak flux density ratio.It is imperative that regular phase drifting in bright pulse sequence is identified in both the leading and trailing components for the first time.Possible physical mechanisms are discussed in detail to provide insights into these observations.展开更多
We present a study of low surface brightness galaxies(LSBGs) selected by fitting the images for all the galaxies inα.40 SDSS DR7 sample with two kinds of single-component models and two kinds of two-component models(...We present a study of low surface brightness galaxies(LSBGs) selected by fitting the images for all the galaxies inα.40 SDSS DR7 sample with two kinds of single-component models and two kinds of two-component models(disk+bulge):single exponential,single sersic,exponential+deVaucular(exp+deV),and exponential+sérsic(exp+ser).Under the criteria of the B band disk central surface brightness μ_(0,disk)(B)≥22.5 mag arcsec^(-2) and the axis ratio b/a> 0.3,we selected four none-edge-on LSBG samples from each of the models which contain 1105,1038,207,and 75 galaxies,respectively.There are 756 galaxies in common between LSBGs selected by exponential and sersic models,corresponding to 68.42% of LSBGs selected by the exponential model and 72.83% of LSBGs selected by the sersic model,the rest of the discrepancy is due to the difference in obtaining μ_(0) between the exponential and sersic models.Based on the fitting,in the range of 0.5≤n≤1.5,the relation of μ_(0) from two models can be written as μ_(0,sérsic)-μ_(0,exp)=-1.34(n-1).The LSBGs selected by disk+bulge models(LSBG_(2)comps) are more massive than LSBGs selected by single-component models(LSBG_1comp),and also show a larger disk component.Though the bulges in the majority of our LSBG_(2)comps are not prominent,more than 60% of our LSBG_(2)comps will not be selected if we adopt a single-component model only.We also identified 31 giant low surface brightness galaxies(gLSBGs) from LSBG_(2)comps.They are located at the same region in the color-magnitude diagram as other gLSBGs.After we compared different criteria of gLSBGs selection,we find that for gas-rich LSBGs,M_(*)> 10^(10)M_⊙ is the best to distinguish between gLSBGs and normal LSBGs with bulge.展开更多
The Solar Polar-orbit Observatory(SPO),proposed by Chinese scientists,is designed to observe the solar polar regions in an unprecedented way with a spacecraft traveling in a large solar inclination angle and a small e...The Solar Polar-orbit Observatory(SPO),proposed by Chinese scientists,is designed to observe the solar polar regions in an unprecedented way with a spacecraft traveling in a large solar inclination angle and a small ellipticity.However,one of the most significant challenges lies in ultra-long-distance data transmission,particularly for the Magnetic and Helioseismic Imager(MHI),which is the most important payload and generates the largest volume of data in SPO.In this paper,we propose a tailored lossless data compression method based on the measurement mode and characteristics of MHI data.The background out of the solar disk is removed to decrease the pixel number of an image under compression.Multiple predictive coding methods are combined to eliminate the redundancy utilizing the correlation(space,spectrum,and polarization)in data set,improving the compression ratio.Experimental results demonstrate that our method achieves an average compression ratio of 3.67.The compression time is also less than the general observation period.The method exhibits strong feasibility and can be easily adapted to MHI.展开更多
This study introduces a novel convolutional neural network,the WISE Galaxy Classification Network(WGC),for classifying spiral and elliptical galaxies using Wide-field Infrared Survey Explorer(WISE)images.WGC attains a...This study introduces a novel convolutional neural network,the WISE Galaxy Classification Network(WGC),for classifying spiral and elliptical galaxies using Wide-field Infrared Survey Explorer(WISE)images.WGC attains an accuracy of 89.03%,surpassing the combined use of K-means or SVM with the Color-Color method in more accurately identifying galaxy morphologies.The enhanced variant,WGC_mag,integrates magnitude parameters with image features,further boosting the accuracy to 89.89%.The research also delves into the criteria for galaxy classification,discovering that WGC primarily categorizes dust-rich images as elliptical galaxies,corresponding to their lower star formation rates,and classifies less dusty images as spiral galaxies.The paper explores the consistency and complementarity of WISE infrared images with SDSS optical images in galaxy morphology classification.The SDSS Galaxy Classification Network(SGC),trained on SDSS images,achieved an accuracy of 94.64%.The accuracy reached 99.30% when predictions from SGC and WGC were consistent.Leveraging the complementarity of features in WISE and SDSS images,a novel variant of a classifier,namely the Multi-band Galaxy Morphology Integrated Classifier,has been developed.This classifier elevates the overall prediction accuracy to 95.39%.Lastly,the versatility of WGC was validated in other data sets.On the HyperLEDA data set,the distinction between elliptical galaxies and Sc,Scd and Sd spiral galaxies was most pronounced,achieving an accuracy of 90%,surpassing the classification results of the Galaxy Zoo 2 labeled WISE data set.This research not only demonstrates the effectiveness of WISE images in galaxy morphology classification but also represents an attempt to integrate multi-band astronomical data to enhance understanding of galaxy structures and evolution.展开更多
Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometri...Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometric observations,outliers may exist in the obtained light curves due to various reasons.Therefore,preprocessing is required to remove these outliers to obtain high quality light curves.Through statistical analysis,the reasons leading to outliers can be categorized into two main types:first,the brightness of the object significantly increases due to the passage of a star nearby,referred to as“stellar contamination,”and second,the brightness markedly decreases due to cloudy cover,referred to as“cloudy contamination.”The traditional approach of manually inspecting images for contamination is time-consuming and labor-intensive.However,we propose the utilization of machine learning methods as a substitute.Convolutional Neural Networks and SVMs are employed to identify cases of stellar contamination and cloudy contamination,achieving F1 scores of 1.00 and 0.98 on a test set,respectively.We also explore other machine learning methods such as ResNet-18 and Light Gradient Boosting Machine,then conduct comparative analyses of the results.展开更多
For the ASO-S/HXI payload, the accuracy of the flare reconstruction is reliant on important factors such as the alignment of the dual grating and the precise measurement of observation orientation. To guarantee optima...For the ASO-S/HXI payload, the accuracy of the flare reconstruction is reliant on important factors such as the alignment of the dual grating and the precise measurement of observation orientation. To guarantee optimal functionality of the instrument throughout its life cycle, the Solar Aspect System (SAS) is imperative to ensure that measurements are accurate and reliable. This is achieved by capturing the target motion and utilizing a physical model-based inversion algorithm. However, the SAS optical system’s inversion model is a typical ill-posed inverse problem due to its optical parameters, which results in small target sampling errors triggering unacceptable shifts in the solution. To enhance inversion accuracy and make it more robust against observation errors, we suggest dividing the inversion operation into two stages based on the SAS spot motion model. First, the as-rigid-aspossible (ARAP) transformation algorithm calculates the relative rotations and an intermediate variable between the substrates. Second, we solve an inversion linear equation for the relative translation of the substrates, the offset of the optical axes, and the observation orientation. To address the ill-posed challenge, the Tikhonov method grounded on the discrepancy criterion and the maximum a posteriori (MAP) method founded on the Bayesian framework are utilized. The simulation results exhibit that the ARAP method achieves a solution with a rotational error of roughly±3 5 (1/2-quantile);both regularization techniques are successful in enhancing the stability of the solution, the variance of error in the MAP method is even smaller—it achieves a translational error of approximately±18μm (1/2-quantile) in comparison to the Tikhonov method’s error of around±24μm (1/2-quantile). Furthermore, the SAS practical application data indicates the method’s usability in this study. Lastly, this paper discusses the intrinsic interconnections between the regularization methods.展开更多
Deriving atmospheric parameters of a large sample of stars is of vital importance to understand the formation and evolution of the Milky Way.Photometric surveys,especially those with near-ultraviolet filters,can offer...Deriving atmospheric parameters of a large sample of stars is of vital importance to understand the formation and evolution of the Milky Way.Photometric surveys,especially those with near-ultraviolet filters,can offer accurate measurements of stellar parameters,with the precision comparable to that from low/medium resolution spectroscopy.In this study,we explore the capability of measuring stellar atmospheric parameters from Chinese Space Station Telescope(CSST)broad-band photometry(particularly in the near-ultraviolet bands),based on synthetic colors derived from model spectra.We find that colors from the optical and near-ultraviolet filter systems adopted by CSST show significant sensitivities to the stellar atmospheric parameters,especially the metallicity.According to our mock data tests,the precision of the photometric metallicity is quite high,with typical values of0.17 and 0.20 dex for dwarf and giant stars,respectively.The precision of the effective temperature estimated from broad-band colors are within 50 K.展开更多
Astronomical knowledge entities,such as celestial object identifiers,are crucial for literature retrieval and knowledge graph construction,and other research and applications in the field of astronomy.Traditional meth...Astronomical knowledge entities,such as celestial object identifiers,are crucial for literature retrieval and knowledge graph construction,and other research and applications in the field of astronomy.Traditional methods of extracting knowledge entities from texts face numerous challenging obstacles that are difficult to overcome.Consequently,there is a pressing need for improved methods to efficiently extract them.This study explores the potential of pre-trained Large Language Models(LLMs)to perform astronomical knowledge entity extraction(KEE)task from astrophysical journal articles using prompts.We propose a prompting strategy called PromptKEE,which includes five prompt elements,and design eight combination prompts based on them.We select four representative LLMs(Llama-2-70B,GPT-3.5,GPT-4,and Claude 2)and attempt to extract the most typical astronomical knowledge entities,celestial object identifiers and telescope names,from astronomical journal articles using these eight combination prompts.To accommodate their token limitations,we construct two data sets:the full texts and paragraph collections of 30 articles.Leveraging the eight prompts,we test on full texts with GPT-4and Claude 2,on paragraph collections with all LLMs.The experimental results demonstrate that pre-trained LLMs show significant potential in performing KEE tasks,but their performance varies on the two data sets.Furthermore,we analyze some important factors that influence the performance of LLMs in entity extraction and provide insights for future KEE tasks in astrophysical articles using LLMs.Finally,compared to other methods of KEE,LLMs exhibit strong competitiveness in multiple aspects.展开更多
The radio telescope possesses high sensitivity and strong signal collection capabilities.While receiving celestial radiation signals,it also captures Radio Frequency Interferences(RFIs)introduced by human activities.R...The radio telescope possesses high sensitivity and strong signal collection capabilities.While receiving celestial radiation signals,it also captures Radio Frequency Interferences(RFIs)introduced by human activities.RFI,as signals originating from sources other than the astronomical targets,significantly impacts the quality of astronomical data.This paper presents an RFI fast mitigation algorithm based on block Least Mean Square(LMS)algorithm.It enhances the traditional adaptive LMS filter by grouping L adjacent time-sampled points into one block and applying the same filter coefficients for filtering within each block.This transformation reduces multiplication calculations and enhances algorithm efficiency by leveraging the time-domain convolution theorem.The algorithm is tested using baseband data from the Parkes 64 m radio telescope's pulsar observations and simulated data.The results confirm the algorithm's effectiveness,as the pulsar profile after RFI mitigation closely matches the original pulsar profile.展开更多
To address the problem of real-time processing of ultra-wide bandwidth pulsar baseband data,we designed and implemented a pulsar baseband data processing algorithm(PSRDP)based on GPU parallel computing technology.PSRD...To address the problem of real-time processing of ultra-wide bandwidth pulsar baseband data,we designed and implemented a pulsar baseband data processing algorithm(PSRDP)based on GPU parallel computing technology.PSRDP can perform operations such as baseband data unpacking,channel separation,coherent dedispersion,Stokes detection,phase and folding period prediction,and folding integration in GPU clusters.We tested the algorithm using the J0437-4715 pulsar baseband data generated by the CASPSR and Medusa backends of the Parkes,and the J0332+5434 pulsar baseband data generated by the self-developed backend of the Nan Shan Radio Telescope.We obtained the pulse profiles of each baseband data.Through experimental analysis,we have found that the pulse profiles generated by the PSRDP algorithm in this paper are essentially consistent with the processing results of Digital Signal Processing Software for Pulsar Astronomy(DSPSR),which verified the effectiveness of the PSRDP algorithm.Furthermore,using the same baseband data,we compared the processing speed of PSRDP with DSPSR,and the results showed that PSRDP was not slower than DSPSR in terms of speed.The theoretical and technical experience gained from the PSRDP algorithm research in this article lays a technical foundation for the real-time processing of QTT(Qi Tai radio Telescope)ultra-wide bandwidth pulsar baseband data.展开更多
Very low frequency(VLF)signals are propagated between the ground-ionosphere.Multimode interference will cause the phase to show oscillatory changes with distance while propagating at night,leading to abnormalities in ...Very low frequency(VLF)signals are propagated between the ground-ionosphere.Multimode interference will cause the phase to show oscillatory changes with distance while propagating at night,leading to abnormalities in the received VLF signal.This study uses the VLF signal received in Qingdao City,Shandong Province,from the Russian Alpha navigation system to explore the multimode interference problem of VLF signal propagation.The characteristics of the effect of multimode interference phenomena on the phase are analyzed according to the variation of the phase of the VLF signal.However,the phase of VLF signals will also be affected by the X-ray and energetic particles that are released during the eruption of solar flares,therefore the two phenomena are studied in this work.It is concluded that the X-ray will not affect the phase of VLF signals at night,but the energetic particles will affect the phase change,and the influence of energetic particles should be excluded in the study of multimode interference phenomena.Using VLF signals for navigation positioning in degraded or unavailable GPS conditions is of great practical significance for VLF navigation systems as it can avoid the influence of multimode interference and improve positioning accuracy.展开更多
Seeing is an important index to evaluate the quality of an astronomical site.To estimate seeing at the Muztagh-Ata site with height and time quantitatively,the European Centre for Medium-Range Weather Forecasts reanal...Seeing is an important index to evaluate the quality of an astronomical site.To estimate seeing at the Muztagh-Ata site with height and time quantitatively,the European Centre for Medium-Range Weather Forecasts reanalysis database(ERA5)is used.Seeing calculated from ERA5 is compared consistently with the Differential Image Motion Monitor seeing at the height of 12 m.Results show that seeing decays exponentially with height at the Muztagh-Ata site.Seeing decays the fastest in fall in 2021 and most slowly with height in summer.The seeing condition is better in fall than in summer.The median value of seeing at 12 m is 0.89 arcsec,the maximum value is1.21 arcsec in August and the minimum is 0.66 arcsec in October.The median value of seeing at 12 m is 0.72arcsec in the nighttime and 1.08 arcsec in the daytime.Seeing is a combination of annual and about biannual variations with the same phase as temperature and wind speed indicating that seeing variation with time is influenced by temperature and wind speed.The Richardson number Ri is used to analyze the atmospheric stability and the variations of seeing are consistent with Ri between layers.These quantitative results can provide an important reference for a telescopic observation strategy.展开更多
This paper presents a relative flux calibration method for the Guoshoujing Telescope （LAMOST）, which may be applied to connect a blue spectrum to a red spectrum to build the whole spectrum across the total wavelengt...This paper presents a relative flux calibration method for the Guoshoujing Telescope （LAMOST）, which may be applied to connect a blue spectrum to a red spectrum to build the whole spectrum across the total wavelength range （3700 ～ 9000 A）. In each spectrograph, we estimate the effective temperatures of selected stars using a grid of spectral line indices in the blue spectral range and a comparison with stellar atmosphere models. For each spectrograph, stars of types A and F are selected as pseudo-standard stars, and the theoretical spectra are used to calibrate both the blue （3700 ～ 5900 A） and red spectrograph arms （5700 ～ 9000 A）. Then the spectral response function for these pseudo-standard stars could be used to correct the raw spectra provided by the other fibers of the spectrograph, after a fiber efficiency function has been derived from twilight flat-field exposures. A key problem in this method is the fitting of a pseudo stellar continuum, so we also give a detailed description of this step. The method is tested by comparing a small sample of LAMOST spectra calibrated in this way on stars also observed by the Sloan Digital Sky Survey. The result shows that the T eff estimation and relative flux calibration method are adequate.展开更多
The Five-hundred-meter Aperture Spherical radio Telescope(FAST)will be fully commissioned later in 2019.Once commissioned,operation and maintenance of FAST will be the most prominent task.The unique working mode of ac...The Five-hundred-meter Aperture Spherical radio Telescope(FAST)will be fully commissioned later in 2019.Once commissioned,operation and maintenance of FAST will be the most prominent task.The unique working mode of active shape-changing of FAST cable-net structure makes the traditional maintenance way,which combines routine inspection with preventive maintenances not only expensive,but also unable to effectively avoid potential risks in operations.Therefore,it is necessary to develop an economical and reliable operation/maintenance technology for FAST cable-net structure.In this paper,a Prognostics and Health Management(PHM)system is proposed based on the advanced Digital Twin(DT)technology.Through the finite element analysis of DT model,the current safety status of FAST cablenet is evaluated,and the fatigue life of components in the cable-net is predicted.Hence Condition-Based Maintenance(CBM)of FAST cable-net structure can be realized.The PHM system described in this paper can effectively guarantee the healthy and safe operation of the FAST cable-net structure,greatly improve the maintenance efficiency and reduce the cost for maintenance works.展开更多
In the neutral hydrogen(H I)galaxy survey,a significant challenge is to identify and extract the H I galaxy signal from the observational data contaminated by radio frequency interference(RFI).For a drift-scan survey,...In the neutral hydrogen(H I)galaxy survey,a significant challenge is to identify and extract the H I galaxy signal from the observational data contaminated by radio frequency interference(RFI).For a drift-scan survey,or more generally a survey of a spatially continuous region,in the time-ordered spectral data,the H I galaxies and RFI all appear as regions that extend an area in the time-frequency waterfall plot,so the extraction of the H I galaxies and RFI from such data can be regarded as an image segmentation problem,and machine-learning methods can be applied to solve such problems.In this study,we develop a method to effectively detect and extract signals of H I galaxies based on a Mask R-CNN network combined with the PointRend method.By simulating FAST-observed galaxy signals and potential RFI impact,we created a realistic data set for the training and testing of our neural network.We compared five different architectures and selected the best-performing one.This architecture successfully performs instance segmentation of H I galaxy signals in the RFI-contaminated time-ordered data,achieving a precision of 98.64%and a recall of 93.59%.展开更多
This paper presents an automatic multi-band source cross-identification method based on deep learning to identify the hosts of extragalactic radio emission structures.The aim is to satisfy the increased demand for aut...This paper presents an automatic multi-band source cross-identification method based on deep learning to identify the hosts of extragalactic radio emission structures.The aim is to satisfy the increased demand for automatic radio source identification and analysis of large-scale survey data from next-generation radio facilities such as the Square Kilometre Array and the Next Generation Very Large Array.We demonstrate a 97%overall accuracy in distinguishing quasi-stellar objects,galaxies and stars using their optical morphologies plus their corresponding mid-infrared information by training and testing a convolutional neural network on Pan-STARRS imaging and WISE photometry.Compared with an expert-evaluated sample,we show that our approach has 95%accuracy at identifying the hosts of extended radio components.We also find that improving radio core localization,for instance by locating its geodesic center,could further increase the accuracy of locating the hosts of systems with a complex radio structure,such as C-shaped radio galaxies.The framework developed in this work can be used for analyzing data from future large-scale radio surveys.展开更多
We have carried out the Galactic Plane Pulsar Snapshot(GPPS)survey by using the Five-hundred-meter Aperture Spherical radio Telescope(FAST),the most sensitive systematic pulsar survey in the Galactic plane.In addition...We have carried out the Galactic Plane Pulsar Snapshot(GPPS)survey by using the Five-hundred-meter Aperture Spherical radio Telescope(FAST),the most sensitive systematic pulsar survey in the Galactic plane.In addition to more than 500 pulsars already discovered through normal periodical search,we report here the discovery of 76 new transient radio sources with sporadic strong pulses,detected by using the newly developed module for a sensitive single-pulse search.Their small DM values suggest that they all are Galactic rotating radio transients(RRATs).They show different properties in the follow-up observations.More radio pulses have been detected from 26 transient radio sources but no periods can be found due to a limited small number of pulses from all FAST observations.The followup observations show that 16 transient sources are newly identified as being the prototypes of RRATs with a period already determined from more detected sporadic pulses,and 10 sources are extremely nulling pulsars,and 24 sources are weak pulsars with sparse strong pulses.On the other hand,48 previously known RRATs have been detected by the FAST,either during verification observations for the GPPS survey or through targeted observations of applied normal FAST projects.Except for one RRAT with four pulses detected in a session of 5-minute observation and four RRATs with only one pulse detected in a session,sensitive FAST observations reveal that 43 RRATs are just generally weak pulsars with sporadic strong pulses or simply very nulling pulsars,so that the previously known RRATs always have an extreme emission state together with a normal hardly detectable weak emission state.This is echoed by the two normal pulsars J1938+2213 and J1946+1449 with occasional brightening pulses.Though strong pulses of RRATs are very outstanding in the energy distribution,their polarization angle variations follow the polarization angle curve of the averaged normal pulse profile,suggesting that the predominant sparse pulses of RRATs are emitted in the same re展开更多
文摘As the performance of dedicated facilities has continually improved, large numbers of pulsar candidates are being received, which makes selecting valuable pulsar signals from the candidates challenging. In this paper, we describe the design for a deep convolutional neural network(CNN) with 11 layers for classifying pulsar candidates. Compared to artificially designed features, the CNN chooses the subintegrations plot and sub-bands plot for each candidate as inputs without carrying biases. To address the imbalance problem, a data augmentation method based on synthetic minority samples is proposed according to the characteristics of pulsars. The maximum pulses of pulsar candidates were first translated to the same position, and then new samples were generated by adding up multiple subplots of pulsars. The data augmentation method is simple and effective for obtaining varied and representative samples which keep pulsar characteristics. In experiments on the HTRU 1 dataset, it is shown that this model can achieve recall of 0.962 and precision of 0.963.
基金The Binary Systems of South and North(BSN)project(https://bsnp.info/)。
文摘Reviewing the empirical and theoretical parameter relationships between various parameters is a good way to understand more about contact binary systems.In this investigation,two-dimensional(2D)relationships for P–MV(system),P–L1,2,M1,2–L1,2,and q–Lratiowere revisited.The sample used is related to 118 contact binary systems with an orbital period shorter than 0.6 days whose absolute parameters were estimated based on the Gaia Data Release 3 parallax.We reviewed previous studies on 2D relationships and updated six parameter relationships.Therefore,Markov chain Monte Carlo and Machine Learning methods were used,and the outcomes were compared.We selected 22 contact binary systems from eight previous studies for comparison,which had light curve solutions using spectroscopic data.The results show that the systems are in good agreement with the results of this study.
基金supported by the National Natural Science Foundation of China (Grant Nos: 61273248 and 61075033)the Natural Science Foundation of Guangdong Province (2014A030313425 and S2011010003348)China Scholarship Council (201706755006) and the Joint Research Fund in Astronomy (U1531242) under cooperative agreement between the National Natural Science Foundation of China and Chinese Academy of Sciences
文摘With the availability of multi-object spectrometers and the design and operation of some large scale sky surveys, the issue of how to deal with enormous quantities of spectral data efficiently and accurately is becoming more and more important. This work investigates the classification problem of stellar spectra under the assumption that there is no perfect absolute flux calibration, for example, when considering spectra from the Guo Shou Jing Telescope(the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, LAMOST). The proposed scheme consists of the following two procedures: Firstly, a spectrum is normalized based on a 17 th order polynomial fitting;secondly, a random forest(RF) is utilized to classify the stellar spectra. Experiments on four stellar spectral libraries show that the RF has good classification performance. This work also studied the spectral feature evaluation problem based on RF. The evaluation is helpful in understanding the results of the proposed stellar classification scheme and exploring its potential improvements in the future.
基金supported by the open project of the Key Laboratory in Xinjiang Uygur Autonomous Region of China(No.2023D04058)the Major Science and Technology Program of Xinjiang Uygur Autonomous Region(No.2022A03013-1)+12 种基金the National Key Research and Development Program of China(No.2022YFC2205203)the National Natural Science Foundation of China(NSFC,Grant Nos.12303053,12288102,11988101,U1838109,12041304,12041301,11873080,12133004,12203094 and U1631106)the Chinese Academy of Sciences Foundation of the young scholars of western(No.2020XBQNXZ-019)the National SKA Program of China(2020SKA0120100)Z.G.W.is supported by the Tianshan Talent Training Program(NO.2023TSYCCX0100)2021 project Xinjiang Uygur autonomous region of China for Tianshan elitesthe Youth Innovation Promotion Association of CAS under No.2023069J.L.C.is supported by the Natural Science Foundation of Shanxi Province(20210302123083)H.W.is supported by the ScientificTechnological Innovation Programs of Higher Education Institutions in Shanxi(grant No.2021L480)W.M.Y.is supported by the CAS Jianzhihua projectH.G.W.is supported by the 2018 project of Xinjiang Uygur autonomous region of China for flexibly fetching in upscale talentsW.H.is supported by the CAS Light of West China Program No.2019-XBQNXZ-B-019。
文摘We have conducted a comprehensive investigation into the bright single pulse emission from PSR B1133+16using the Giant Metrewave Radio Telescope.High time resolution data(61μs)were obtained at a center frequency of 322 MHz with a bandwidth of 32 MHz over a continuous observation period of 7.45 hr.A total of 1082 bright pulses were sporadically detected with peak flux densities ranging from 10 to 23 times stronger than the average pulse profile.However,no giant pulse-like emission with a relative pulse energy larger than 10 and extremely short duration was detected,indicating that these bright pulses cannot be categorized as giant pulse emission.The majority of these bright pulses are concentrated in pulse phases at both the leading and trailing windows of the average pulse profile,with an occurrence ratio of approximately 2.74.The pulse energy distribution for all individual pulses can be described by a combination of two Gaussian components and a cutoff power-law with an index of α=-3.2.An updated nulling fraction of 15.35%±0.45% was determined from the energy distribution.The emission of individual pulses follows a log-normal distribution in peak flux density ratio.It is imperative that regular phase drifting in bright pulse sequence is identified in both the leading and trailing components for the first time.Possible physical mechanisms are discussed in detail to provide insights into these observations.
基金supported by the National Key R&D Program of China (grant No.2022YFA1602901)support of the National Natural Science Foundation of China(NSFC) grant Nos. 12090040, 12090041, and 12003043+5 种基金supported by the Youth Innovation Promotion AssociationCAS (No. 2020057)the science research grants of CSST from the China Manned Space Projectsupport of the NSFC grant Nos.11733006 and U1931109supported by the Strategic Priority Research Program of the Chinese Academy of Sciences,Grant No. XDB0550100partially supported by the Open Project Program of the Key Laboratory of Optical Astronomy,National Astronomical Observatories,Chinese Academy of Sciences。
文摘We present a study of low surface brightness galaxies(LSBGs) selected by fitting the images for all the galaxies inα.40 SDSS DR7 sample with two kinds of single-component models and two kinds of two-component models(disk+bulge):single exponential,single sersic,exponential+deVaucular(exp+deV),and exponential+sérsic(exp+ser).Under the criteria of the B band disk central surface brightness μ_(0,disk)(B)≥22.5 mag arcsec^(-2) and the axis ratio b/a> 0.3,we selected four none-edge-on LSBG samples from each of the models which contain 1105,1038,207,and 75 galaxies,respectively.There are 756 galaxies in common between LSBGs selected by exponential and sersic models,corresponding to 68.42% of LSBGs selected by the exponential model and 72.83% of LSBGs selected by the sersic model,the rest of the discrepancy is due to the difference in obtaining μ_(0) between the exponential and sersic models.Based on the fitting,in the range of 0.5≤n≤1.5,the relation of μ_(0) from two models can be written as μ_(0,sérsic)-μ_(0,exp)=-1.34(n-1).The LSBGs selected by disk+bulge models(LSBG_(2)comps) are more massive than LSBGs selected by single-component models(LSBG_1comp),and also show a larger disk component.Though the bulges in the majority of our LSBG_(2)comps are not prominent,more than 60% of our LSBG_(2)comps will not be selected if we adopt a single-component model only.We also identified 31 giant low surface brightness galaxies(gLSBGs) from LSBG_(2)comps.They are located at the same region in the color-magnitude diagram as other gLSBGs.After we compared different criteria of gLSBGs selection,we find that for gas-rich LSBGs,M_(*)> 10^(10)M_⊙ is the best to distinguish between gLSBGs and normal LSBGs with bulge.
基金supported by the National Key R&D Program of China(grant No.2022YFF0503800)by the National Natural Science Foundation of China(NSFC)(grant No.11427901)+1 种基金by the Strategic Priority Research Program of the Chinese Academy of Sciences(CAS-SPP)(grant No.XDA15320102)by the Youth Innovation Promotion Association(CAS No.2022057)。
文摘The Solar Polar-orbit Observatory(SPO),proposed by Chinese scientists,is designed to observe the solar polar regions in an unprecedented way with a spacecraft traveling in a large solar inclination angle and a small ellipticity.However,one of the most significant challenges lies in ultra-long-distance data transmission,particularly for the Magnetic and Helioseismic Imager(MHI),which is the most important payload and generates the largest volume of data in SPO.In this paper,we propose a tailored lossless data compression method based on the measurement mode and characteristics of MHI data.The background out of the solar disk is removed to decrease the pixel number of an image under compression.Multiple predictive coding methods are combined to eliminate the redundancy utilizing the correlation(space,spectrum,and polarization)in data set,improving the compression ratio.Experimental results demonstrate that our method achieves an average compression ratio of 3.67.The compression time is also less than the general observation period.The method exhibits strong feasibility and can be easily adapted to MHI.
基金supported by the Joint Research Fund in AstronomyNational Natural Science Foundation of China(NSFC,grant No.U1931134)+1 种基金the Natural Science Foundation of Hebei,A2020202001the Natural Science Foundation of Tianjin Municipality,22JCYBJC00410。
文摘This study introduces a novel convolutional neural network,the WISE Galaxy Classification Network(WGC),for classifying spiral and elliptical galaxies using Wide-field Infrared Survey Explorer(WISE)images.WGC attains an accuracy of 89.03%,surpassing the combined use of K-means or SVM with the Color-Color method in more accurately identifying galaxy morphologies.The enhanced variant,WGC_mag,integrates magnitude parameters with image features,further boosting the accuracy to 89.89%.The research also delves into the criteria for galaxy classification,discovering that WGC primarily categorizes dust-rich images as elliptical galaxies,corresponding to their lower star formation rates,and classifies less dusty images as spiral galaxies.The paper explores the consistency and complementarity of WISE infrared images with SDSS optical images in galaxy morphology classification.The SDSS Galaxy Classification Network(SGC),trained on SDSS images,achieved an accuracy of 94.64%.The accuracy reached 99.30% when predictions from SGC and WGC were consistent.Leveraging the complementarity of features in WISE and SDSS images,a novel variant of a classifier,namely the Multi-band Galaxy Morphology Integrated Classifier,has been developed.This classifier elevates the overall prediction accuracy to 95.39%.Lastly,the versatility of WGC was validated in other data sets.On the HyperLEDA data set,the distinction between elliptical galaxies and Sc,Scd and Sd spiral galaxies was most pronounced,achieving an accuracy of 90%,surpassing the classification results of the Galaxy Zoo 2 labeled WISE data set.This research not only demonstrates the effectiveness of WISE images in galaxy morphology classification but also represents an attempt to integrate multi-band astronomical data to enhance understanding of galaxy structures and evolution.
基金funded by the National Natural Science Foundation of China(NSFC,Nos.12373086 and 12303082)CAS“Light of West China”Program+2 种基金Yunnan Revitalization Talent Support Program in Yunnan ProvinceNational Key R&D Program of ChinaGravitational Wave Detection Project No.2022YFC2203800。
文摘Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometric observations,outliers may exist in the obtained light curves due to various reasons.Therefore,preprocessing is required to remove these outliers to obtain high quality light curves.Through statistical analysis,the reasons leading to outliers can be categorized into two main types:first,the brightness of the object significantly increases due to the passage of a star nearby,referred to as“stellar contamination,”and second,the brightness markedly decreases due to cloudy cover,referred to as“cloudy contamination.”The traditional approach of manually inspecting images for contamination is time-consuming and labor-intensive.However,we propose the utilization of machine learning methods as a substitute.Convolutional Neural Networks and SVMs are employed to identify cases of stellar contamination and cloudy contamination,achieving F1 scores of 1.00 and 0.98 on a test set,respectively.We also explore other machine learning methods such as ResNet-18 and Light Gradient Boosting Machine,then conduct comparative analyses of the results.
基金the Strategic Priority Research Program on Space Science of the Chinese Academy of Sciences,the grant No.XDA15320104,with additional contributions from the Purple Mountain Observatory(PMO)of the Chinese Academy of Sciences and the National Space Science Center(NSSC).
文摘For the ASO-S/HXI payload, the accuracy of the flare reconstruction is reliant on important factors such as the alignment of the dual grating and the precise measurement of observation orientation. To guarantee optimal functionality of the instrument throughout its life cycle, the Solar Aspect System (SAS) is imperative to ensure that measurements are accurate and reliable. This is achieved by capturing the target motion and utilizing a physical model-based inversion algorithm. However, the SAS optical system’s inversion model is a typical ill-posed inverse problem due to its optical parameters, which results in small target sampling errors triggering unacceptable shifts in the solution. To enhance inversion accuracy and make it more robust against observation errors, we suggest dividing the inversion operation into two stages based on the SAS spot motion model. First, the as-rigid-aspossible (ARAP) transformation algorithm calculates the relative rotations and an intermediate variable between the substrates. Second, we solve an inversion linear equation for the relative translation of the substrates, the offset of the optical axes, and the observation orientation. To address the ill-posed challenge, the Tikhonov method grounded on the discrepancy criterion and the maximum a posteriori (MAP) method founded on the Bayesian framework are utilized. The simulation results exhibit that the ARAP method achieves a solution with a rotational error of roughly±3 5 (1/2-quantile);both regularization techniques are successful in enhancing the stability of the solution, the variance of error in the MAP method is even smaller—it achieves a translational error of approximately±18μm (1/2-quantile) in comparison to the Tikhonov method’s error of around±24μm (1/2-quantile). Furthermore, the SAS practical application data indicates the method’s usability in this study. Lastly, this paper discusses the intrinsic interconnections between the regularization methods.
基金the science research grants from the China Manned Space Project with No.CMS-CSST-2021-A08.Y.Hthe science research grants from the China Manned Space Project with No.CMS-CSST-2021-B05+3 种基金the NSFC for grant Nos.11903027 and11833006the NSFC for grant Nos.11973001,12090040,and 12090044the National Key R&D Program of China for grant No.2019YFA0405503.H.W.Zthe National Key R&D Program of China for grant No.2019YFA0405504。
文摘Deriving atmospheric parameters of a large sample of stars is of vital importance to understand the formation and evolution of the Milky Way.Photometric surveys,especially those with near-ultraviolet filters,can offer accurate measurements of stellar parameters,with the precision comparable to that from low/medium resolution spectroscopy.In this study,we explore the capability of measuring stellar atmospheric parameters from Chinese Space Station Telescope(CSST)broad-band photometry(particularly in the near-ultraviolet bands),based on synthetic colors derived from model spectra.We find that colors from the optical and near-ultraviolet filter systems adopted by CSST show significant sensitivities to the stellar atmospheric parameters,especially the metallicity.According to our mock data tests,the precision of the photometric metallicity is quite high,with typical values of0.17 and 0.20 dex for dwarf and giant stars,respectively.The precision of the effective temperature estimated from broad-band colors are within 50 K.
基金supported by the National Natural Science Foundation of China(NSFC,Grant Nos.12273077,72101068,12373110,and 12103070)National Key Research and Development Program of China under grants(2022YFF0712400,2022YFF0711500)+2 种基金the 14th Five-year Informatization Plan of Chinese Academy of Sciences(CAS-WX2021SF-0204)supported by Astronomical Big Data Joint Research Centerco-founded by National Astronomical Observatories,Chinese Academy of Sciences and Alibaba Cloud。
文摘Astronomical knowledge entities,such as celestial object identifiers,are crucial for literature retrieval and knowledge graph construction,and other research and applications in the field of astronomy.Traditional methods of extracting knowledge entities from texts face numerous challenging obstacles that are difficult to overcome.Consequently,there is a pressing need for improved methods to efficiently extract them.This study explores the potential of pre-trained Large Language Models(LLMs)to perform astronomical knowledge entity extraction(KEE)task from astrophysical journal articles using prompts.We propose a prompting strategy called PromptKEE,which includes five prompt elements,and design eight combination prompts based on them.We select four representative LLMs(Llama-2-70B,GPT-3.5,GPT-4,and Claude 2)and attempt to extract the most typical astronomical knowledge entities,celestial object identifiers and telescope names,from astronomical journal articles using these eight combination prompts.To accommodate their token limitations,we construct two data sets:the full texts and paragraph collections of 30 articles.Leveraging the eight prompts,we test on full texts with GPT-4and Claude 2,on paragraph collections with all LLMs.The experimental results demonstrate that pre-trained LLMs show significant potential in performing KEE tasks,but their performance varies on the two data sets.Furthermore,we analyze some important factors that influence the performance of LLMs in entity extraction and provide insights for future KEE tasks in astrophysical articles using LLMs.Finally,compared to other methods of KEE,LLMs exhibit strong competitiveness in multiple aspects.
基金supported by the National Key R&D Program of China(Nos.2021YFC2203502 and 2022YFF0711502)the National Natural Science Foundation of China(NSFC)(12173077 and 12073067)+7 种基金the Tianshan Innovation Team Plan of Xinjiang Uygur Autonomous Region(2022D14020)the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(grant No.PTYQ2022YZZD01)China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of Sciences(CAS)Natural Science Foundation of Xinjiang Uygur AutonomousRegion(2022D01A360)the CAS“Light of West China”program under No.2022-XBQNXZ-012supported by Astronomical Big Data Joint Research Center,cofounded by National Astronomical Observatories,Chinese Academy of Sciences。
文摘The radio telescope possesses high sensitivity and strong signal collection capabilities.While receiving celestial radiation signals,it also captures Radio Frequency Interferences(RFIs)introduced by human activities.RFI,as signals originating from sources other than the astronomical targets,significantly impacts the quality of astronomical data.This paper presents an RFI fast mitigation algorithm based on block Least Mean Square(LMS)algorithm.It enhances the traditional adaptive LMS filter by grouping L adjacent time-sampled points into one block and applying the same filter coefficients for filtering within each block.This transformation reduces multiplication calculations and enhances algorithm efficiency by leveraging the time-domain convolution theorem.The algorithm is tested using baseband data from the Parkes 64 m radio telescope's pulsar observations and simulated data.The results confirm the algorithm's effectiveness,as the pulsar profile after RFI mitigation closely matches the original pulsar profile.
基金supported by the National Key R&D Program of China Nos.2021YFC2203502 and 2022YFF0711502the National Natural Science Foundation of China(NSFC)(12173077 and 12003062)+5 种基金the Tianshan Innovation Team Plan of Xinjiang Uygur Autonomous Region(2022D14020)the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095)the Scientific Instrument Developing Project of the Chinese Academy of Sciences,grant No.PTYQ2022YZZD01China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of Sciences(CAS)Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360)。
文摘To address the problem of real-time processing of ultra-wide bandwidth pulsar baseband data,we designed and implemented a pulsar baseband data processing algorithm(PSRDP)based on GPU parallel computing technology.PSRDP can perform operations such as baseband data unpacking,channel separation,coherent dedispersion,Stokes detection,phase and folding period prediction,and folding integration in GPU clusters.We tested the algorithm using the J0437-4715 pulsar baseband data generated by the CASPSR and Medusa backends of the Parkes,and the J0332+5434 pulsar baseband data generated by the self-developed backend of the Nan Shan Radio Telescope.We obtained the pulse profiles of each baseband data.Through experimental analysis,we have found that the pulse profiles generated by the PSRDP algorithm in this paper are essentially consistent with the processing results of Digital Signal Processing Software for Pulsar Astronomy(DSPSR),which verified the effectiveness of the PSRDP algorithm.Furthermore,using the same baseband data,we compared the processing speed of PSRDP with DSPSR,and the results showed that PSRDP was not slower than DSPSR in terms of speed.The theoretical and technical experience gained from the PSRDP algorithm research in this article lays a technical foundation for the real-time processing of QTT(Qi Tai radio Telescope)ultra-wide bandwidth pulsar baseband data.
基金supported by the National Natural Science Foundation of China(U1704134)。
文摘Very low frequency(VLF)signals are propagated between the ground-ionosphere.Multimode interference will cause the phase to show oscillatory changes with distance while propagating at night,leading to abnormalities in the received VLF signal.This study uses the VLF signal received in Qingdao City,Shandong Province,from the Russian Alpha navigation system to explore the multimode interference problem of VLF signal propagation.The characteristics of the effect of multimode interference phenomena on the phase are analyzed according to the variation of the phase of the VLF signal.However,the phase of VLF signals will also be affected by the X-ray and energetic particles that are released during the eruption of solar flares,therefore the two phenomena are studied in this work.It is concluded that the X-ray will not affect the phase of VLF signals at night,but the energetic particles will affect the phase change,and the influence of energetic particles should be excluded in the study of multimode interference phenomena.Using VLF signals for navigation positioning in degraded or unavailable GPS conditions is of great practical significance for VLF navigation systems as it can avoid the influence of multimode interference and improve positioning accuracy.
基金funded by the National Natural Science Foundation of China(NSFC)the Chinese Academy of Sciences(CAS)(grant No.U2031209)the National Natural Science Foundation of China(NSFC,grant Nos.11872128,42174192,and 91952111)。
文摘Seeing is an important index to evaluate the quality of an astronomical site.To estimate seeing at the Muztagh-Ata site with height and time quantitatively,the European Centre for Medium-Range Weather Forecasts reanalysis database(ERA5)is used.Seeing calculated from ERA5 is compared consistently with the Differential Image Motion Monitor seeing at the height of 12 m.Results show that seeing decays exponentially with height at the Muztagh-Ata site.Seeing decays the fastest in fall in 2021 and most slowly with height in summer.The seeing condition is better in fall than in summer.The median value of seeing at 12 m is 0.89 arcsec,the maximum value is1.21 arcsec in August and the minimum is 0.66 arcsec in October.The median value of seeing at 12 m is 0.72arcsec in the nighttime and 1.08 arcsec in the daytime.Seeing is a combination of annual and about biannual variations with the same phase as temperature and wind speed indicating that seeing variation with time is influenced by temperature and wind speed.The Richardson number Ri is used to analyze the atmospheric stability and the variations of seeing are consistent with Ri between layers.These quantitative results can provide an important reference for a telescopic observation strategy.
基金funded by the National Natural Science Foundation of China (Grant No.10973021)
文摘This paper presents a relative flux calibration method for the Guoshoujing Telescope （LAMOST）, which may be applied to connect a blue spectrum to a red spectrum to build the whole spectrum across the total wavelength range （3700 ～ 9000 A）. In each spectrograph, we estimate the effective temperatures of selected stars using a grid of spectral line indices in the blue spectral range and a comparison with stellar atmosphere models. For each spectrograph, stars of types A and F are selected as pseudo-standard stars, and the theoretical spectra are used to calibrate both the blue （3700 ～ 5900 A） and red spectrograph arms （5700 ～ 9000 A）. Then the spectral response function for these pseudo-standard stars could be used to correct the raw spectra provided by the other fibers of the spectrograph, after a fiber efficiency function has been derived from twilight flat-field exposures. A key problem in this method is the fitting of a pseudo stellar continuum, so we also give a detailed description of this step. The method is tested by comparing a small sample of LAMOST spectra calibrated in this way on stars also observed by the Sloan Digital Sky Survey. The result shows that the T eff estimation and relative flux calibration method are adequate.
基金supported by the National Natural Science Foundation of China(Grant No.11673039)the Open Project Program of the Key Laboratory of FAST,National Astronomical Observatories,Chinese Academy of Sciences
文摘The Five-hundred-meter Aperture Spherical radio Telescope(FAST)will be fully commissioned later in 2019.Once commissioned,operation and maintenance of FAST will be the most prominent task.The unique working mode of active shape-changing of FAST cable-net structure makes the traditional maintenance way,which combines routine inspection with preventive maintenances not only expensive,but also unable to effectively avoid potential risks in operations.Therefore,it is necessary to develop an economical and reliable operation/maintenance technology for FAST cable-net structure.In this paper,a Prognostics and Health Management(PHM)system is proposed based on the advanced Digital Twin(DT)technology.Through the finite element analysis of DT model,the current safety status of FAST cablenet is evaluated,and the fatigue life of components in the cable-net is predicted.Hence Condition-Based Maintenance(CBM)of FAST cable-net structure can be realized.The PHM system described in this paper can effectively guarantee the healthy and safe operation of the FAST cable-net structure,greatly improve the maintenance efficiency and reduce the cost for maintenance works.
基金support by the National SKA Program of ChinaNo.2022SKA0110100+1 种基金the CAS Interdisciplinary Innovation Team(JCTD-2019-05)the science research grants from the China Manned Space Project with No.CMS-CSST-2021-B01。
文摘In the neutral hydrogen(H I)galaxy survey,a significant challenge is to identify and extract the H I galaxy signal from the observational data contaminated by radio frequency interference(RFI).For a drift-scan survey,or more generally a survey of a spatially continuous region,in the time-ordered spectral data,the H I galaxies and RFI all appear as regions that extend an area in the time-frequency waterfall plot,so the extraction of the H I galaxies and RFI from such data can be regarded as an image segmentation problem,and machine-learning methods can be applied to solve such problems.In this study,we develop a method to effectively detect and extract signals of H I galaxies based on a Mask R-CNN network combined with the PointRend method.By simulating FAST-observed galaxy signals and potential RFI impact,we created a realistic data set for the training and testing of our neural network.We compared five different architectures and selected the best-performing one.This architecture successfully performs instance segmentation of H I galaxy signals in the RFI-contaminated time-ordered data,achieving a precision of 98.64%and a recall of 93.59%.
基金supported by grants from the National Natural Science Foundation of China(Nos.11973051,12041302)funded by Chinese Academy of Sciences President’s International Fellowship Initiative.Grant No.2019PM0017。
文摘This paper presents an automatic multi-band source cross-identification method based on deep learning to identify the hosts of extragalactic radio emission structures.The aim is to satisfy the increased demand for automatic radio source identification and analysis of large-scale survey data from next-generation radio facilities such as the Square Kilometre Array and the Next Generation Very Large Array.We demonstrate a 97%overall accuracy in distinguishing quasi-stellar objects,galaxies and stars using their optical morphologies plus their corresponding mid-infrared information by training and testing a convolutional neural network on Pan-STARRS imaging and WISE photometry.Compared with an expert-evaluated sample,we show that our approach has 95%accuracy at identifying the hosts of extended radio components.We also find that improving radio core localization,for instance by locating its geodesic center,could further increase the accuracy of locating the hosts of systems with a complex radio structure,such as C-shaped radio galaxies.The framework developed in this work can be used for analyzing data from future large-scale radio surveys.
基金This project,as one of five key projects,is being carried out by using FAST,a Chinese national mega-science facility built and operated by the National Astronomical Observatories,Chinese Academy of Sciencessupported by the National Natural Science Foundation of China(NSFC,Nos.11988101 and 11833009)+5 种基金the Key Research Program of the Chinese Academy of Sciences(grant No.QYZDJ-SSWSLH021)supported by the Cultivation Project for the FAST scientific Payoff and Research Achievement of CAMS-CASsupported by NSFC No.12133004,partially supported by NSFC No.U1731120partially supported by the NSFC No.11873058,partially supported by NSFC No.U2031115partially supported by the National SKA program of China No.2020SKA0120200partially supported by the Guangzhou Science and Technology Project No.202102010466。
文摘We have carried out the Galactic Plane Pulsar Snapshot(GPPS)survey by using the Five-hundred-meter Aperture Spherical radio Telescope(FAST),the most sensitive systematic pulsar survey in the Galactic plane.In addition to more than 500 pulsars already discovered through normal periodical search,we report here the discovery of 76 new transient radio sources with sporadic strong pulses,detected by using the newly developed module for a sensitive single-pulse search.Their small DM values suggest that they all are Galactic rotating radio transients(RRATs).They show different properties in the follow-up observations.More radio pulses have been detected from 26 transient radio sources but no periods can be found due to a limited small number of pulses from all FAST observations.The followup observations show that 16 transient sources are newly identified as being the prototypes of RRATs with a period already determined from more detected sporadic pulses,and 10 sources are extremely nulling pulsars,and 24 sources are weak pulsars with sparse strong pulses.On the other hand,48 previously known RRATs have been detected by the FAST,either during verification observations for the GPPS survey or through targeted observations of applied normal FAST projects.Except for one RRAT with four pulses detected in a session of 5-minute observation and four RRATs with only one pulse detected in a session,sensitive FAST observations reveal that 43 RRATs are just generally weak pulsars with sporadic strong pulses or simply very nulling pulsars,so that the previously known RRATs always have an extreme emission state together with a normal hardly detectable weak emission state.This is echoed by the two normal pulsars J1938+2213 and J1946+1449 with occasional brightening pulses.Though strong pulses of RRATs are very outstanding in the energy distribution,their polarization angle variations follow the polarization angle curve of the averaged normal pulse profile,suggesting that the predominant sparse pulses of RRATs are emitted in the same re
