The Xinjiang Astronomical Observatory Data Center faces issues related to delay-affected services. As a result, these services cannot be implemented in a timely manner due to the overloading of transmission links. In ...The Xinjiang Astronomical Observatory Data Center faces issues related to delay-affected services. As a result, these services cannot be implemented in a timely manner due to the overloading of transmission links. In this paper, the software-defined network technology is applied to the Xinjiang Astronomical Observatory Data Center Network(XAODCN). Specifically, a novel reconfiguration method is proposed to realise the software-defined Xinjiang Astronomical Observatory Data Center Network(SDXAO-DCN), and a network model is constructed. To overcome the congestion problem, a traffic load-balancing algorithm is designed for fast transmission of the service traffic by combining three factors: network structure, congestion level and transmission service. The proposed algorithm is compared with current commonly load-balancing algorithms which are used in data center to verify its efficiency. Simulation experiments show that the algorithm improved transmission performance and transmission quality for the SDXAO-DCN.展开更多
Cross-matching is a key technique to achieve fusion of multi-band astronomical catalogs. Due to different equipment such as various astronomical telescopes, the existence of measurement errors, and proper motions of t...Cross-matching is a key technique to achieve fusion of multi-band astronomical catalogs. Due to different equipment such as various astronomical telescopes, the existence of measurement errors, and proper motions of the celestial bodies, the same celestial object will have different positions in different catalogs, making it difficult to integrate multi-band or full-band astronomical data. In this study, we propose an online cross-matching method based on pseudo-spherical indexing techniques and develop a service combining with high performance computing system(Taurus) to improve cross-matching efficiency, which is designed for the Data Center of Xinjiang Astronomical Observatory. Specifically, we use Quad Tree Cube to divide the spherical blocks of the celestial object and map the 2D space composed of R.A. and decl. to 1D space and achieve correspondence between real celestial objects and spherical patches. Finally, we verify the performance of the service using Gaia 3 and PPMXL catalogs. Meanwhile, we send the matching results to VO tools-Topcat and Aladin respectively to get visual results. The experimental results show that the service effectively solves the speed bottleneck problem of crossmatching caused by frequent I/O, and significantly improves the retrieval and matching speed of massive astronomical data.展开更多
Astronomical spectroscopy is crucial for exploring the physical properties,chemical composition,and kinematic behavior of celestial objects.With continuous advancements in observational technology,astronomical spectro...Astronomical spectroscopy is crucial for exploring the physical properties,chemical composition,and kinematic behavior of celestial objects.With continuous advancements in observational technology,astronomical spectroscopy faces the dual challenges of rapidly expanding data volumes and relatively lagging data processing capabilities.In this context,the rise of artificial intelligence technologies offers an innovative solution to address these challenges.This paper analyzes the latest developments in the application of machine learning for astronomical spectral data mining and discusses future research directions in AI-based spectral studies.However,the application of machine learning technologies presents several challenges.The high complexity of models often comes with insufficient interpretability,complicating scientific understanding.Moreover,the large-scale computational demands place higher requirements on hardware resources,leading to a significant increase in computational costs.AI-based astronomical spectroscopy research should advance in the following key directions.First,develop efficient data augmentation techniques to enhance model generalization capabilities.Second,explore more interpretable model designs to ensure the reliability and transparency of scientific conclusions.Third,optimize computational efficiency and reduce the threshold for deep-learning applications through collaborative innovations in algorithms and hardware.Furthermore,promoting the integration of cross-band data processing is essential to achieve seamless integration and comprehensive analysis of multi-source data,providing richer,multidimensional information to uncover the mysteries of the universe.展开更多
We evaluate the performance of the first generation scientific CMOS （sC- MOS） camera used for astronomical observations. The sCMOS camera was attached to a 25 cm telescope at Xinglong Observatory, in order to estima...We evaluate the performance of the first generation scientific CMOS （sC- MOS） camera used for astronomical observations. The sCMOS camera was attached to a 25 cm telescope at Xinglong Observatory, in order to estimate its photometric capabilities. We further compared the capabilities of the sCMOS camera with that of full-frame and electron multiplying CCD cameras in laboratory tests and observations. The results indicate the sCMOS camera is capable of performing photometry of bright sources, especially when high spatial resolution or temporal resolution is desired.展开更多
Artificial Intelligence(AI)is an interdisciplinary research field with widespread applications.It aims at developing theoretical,methodological,technological,and applied systems that simulate,enhance,and assist human ...Artificial Intelligence(AI)is an interdisciplinary research field with widespread applications.It aims at developing theoretical,methodological,technological,and applied systems that simulate,enhance,and assist human intelligence.Recently,notable accomplishments of artificial intelligence technology have been achieved in astronomical data processing,establishing this technology as central to numerous astronomical research areas such as radio astronomy,stellar and galactic(Milky Way)studies,exoplanets surveys,cosmology,and solar physics.This article systematically reviews representative applications of artificial intelligence technology to astronomical data processing,with comprehensive description of specific cases:pulsar candidate identification,fast radio burst detection,gravitational wave detection,spectral classification,and radio frequency interference mitigation.Furthermore,it discusses possible future applications to provide perspectives for astronomical research in the artificial intelligence era.展开更多
Selecting a good site for ground-based astronomy is very important. Based on the ERA-Interim global reanalysis data, this paper studied the atmospheric conditions of the Qitai Telescope(QTT) site from the aspects of a...Selecting a good site for ground-based astronomy is very important. Based on the ERA-Interim global reanalysis data, this paper studied the atmospheric conditions of the Qitai Telescope(QTT) site from the aspects of absolute humidity, mixing ratio and precipitable water vapor(PWV). Error estimations of meteorological parameters are also analyzed. These primary results show that the QTT site has obvious advantages in terms of conditions with much less atmospheric water vapor than two well-known existing sites with 100-meter-aperture radio telescopes in the world. In addition, due to the influence of atmospheric water vapor on radio observations, the atmospheric transmittance for each frequency band of the site are simulated, and the atmospheric opacity is also calculated as well as Planck radiation brightness. Based on these results, the effective observational time of different bands is further estimated.展开更多
Digital channelization decomposes a wideband signal into multiple adjacent sub-bands using Parallel Technology.Channelization can effectively reduce the pressure on the radio astronomy digital backends system and make...Digital channelization decomposes a wideband signal into multiple adjacent sub-bands using Parallel Technology.Channelization can effectively reduce the pressure on the radio astronomy digital backends system and make wideband signal processing possible.Aiming at the problems of signal attenuation at sub-band edge,spectral leakage and aliasing encountered in wideband signal channelization,algorithms to reduce the problems are studied.We design a Critically Sampled Polyphase Filter Bank(CS-PFB)based on the Finite Impulse Response digital filter with a Hamming Window and systematically analyze the frequency response characteristics of the CS-PFB.Based on the channelized structure of the CS-PFB,an Over Sampled Polyphase Filter Bank(OS-PFB)is designed by data reuse,and the filtering frequency response characteristics of CS-PFB and OS-PFB are compared and analyzed.Using the wideband baseband data generated by the CASPSR(Collaboration for Astronomy Signal processing and electronics research Parkes Swinburne Recorder),we implement sub-band division and 16-band output of these data based on the 2×oversampling OS-PFB,and the problem of spectrum inversion in the sub-bands is corrected.After removing 25%of redundant data in the head and tail of each sub-band,we recombine the sub-bands into a wideband.The wideband signal is almost identical to the original observed signal.Therefore,the experimental results show that the OS-PFB can improve the channel response.For the 400 MHz baseband data of J0437-4715,we compare the pulse profile obtained from the original baseband data with the pulse profile obtained after the channelization and recombination.The phase and amplitude information of the pulse profiles are consistent,which verifies the correctness of our channelization algorithm.展开更多
A large ground-based optical/infrared telescope is being planned for a world-class astronomical site in China.The cloud-free night percentage is the primary meteorological consideration for evaluating candidate sites....A large ground-based optical/infrared telescope is being planned for a world-class astronomical site in China.The cloud-free night percentage is the primary meteorological consideration for evaluating candidate sites.The data from GMS and NOAA satellites and the MODIS instrument were utilized in this research,covering the period from 1996 to 2015.Our data analysis benefits from overlapping results from different independent teams as well as a uniform analysis of selected sites using GMS+NOAA data.Although significant ground-based monitoring is needed to validate these findings,we identify three different geographical regions with a high percentage of cloud-free conditions(~83%on average),which is slightly lower than at Mauna Kea and Cerro Armazones(~85%on average)and were chosen for the large international projects TMT and ELT respectively.Our study finds evidence that cloud distributions and the seasonal changes affected by the prevailing westerly winds and summer monsoons reduce the cloud cover in areas influenced by the westerlies.This is consistent with the expectations from climate change models and is suggestive that most of the identified sites will have reduced cloud cover in the future.展开更多
Location-based cross-matching is a preprocessing step in astronomy that aims to identify records belonging to the same celestial body based on the angular distance formula. The traditional approach involves comparing ...Location-based cross-matching is a preprocessing step in astronomy that aims to identify records belonging to the same celestial body based on the angular distance formula. The traditional approach involves comparing each record in one catalog with every record in the other catalog, resulting in a one-to-one comparison with high computational complexity. To reduce the computational time, index partitioning methods are used to divide the sky into regions and perform local cross-matching. In addition, cross-matching algorithms have been adopted on highperformance architectures to improve their efficiency. But the index partitioning methods and computation architectures only increase the degree of parallelism, and cannot decrease the complexity of pairwise-based crossmatching algorithm itself. A better algorithm is needed to further improve the performance of cross-matching algorithm. In this paper, we propose a 3d-tree-based cross-matching algorithm that converts the angular distance formula into an equivalent 3dEuclidean distance and uses 3d-tree method to reduce the overall computational complexity and to avoid boundary issues. Furthermore, we demonstrate the superiority of the 3d-tree approach over the 2d-tree method and implement it using a multi-threading technique during both the construction and querying phases. We have experimentally evaluated the proposed 3d-tree cross-matching algorithm using publicly available catalog data. The results show that our algorithm applied on two 32-core CPUs achieves equivalent performance than previous experiments conducted on a six-node CPU-GPU cluster.展开更多
Aiming at the subband division of ultra-wide bandwidth low-frequency(UWL)signal(frequency coverage range:704–4032 MHz)of the Xinjiang 110 m QiTai radio Telescope(QTT),a scheme of ultra-wide bandwidth signal is design...Aiming at the subband division of ultra-wide bandwidth low-frequency(UWL)signal(frequency coverage range:704–4032 MHz)of the Xinjiang 110 m QiTai radio Telescope(QTT),a scheme of ultra-wide bandwidth signal is designed.First,we analyze the effect of different window functions such as the Hanning window,Hamming window,and Kaiser window on the performance of finite impulse response(FIR)digital filters,and implement a critical sampling polyphase filter bank(CS-PFB)based on the Hamming window FIR digital filter.Second,we generate 3328 MHz simulation data of ultra-wideband pulsar baseband in the frequency range of 704–4032 MHz using the ultra-wide bandwidth pulsar baseband data generation algorithm based on the 400 MHz bandwidth pulsar baseband data obtained from Parkes CASPSR observations.Third,we obtain 26 subbands of 128 MHz based on CS-PFB and the simulation data,and the pulse profile of each subband by coherent dispersion,integration,and folding.Finally,the phase of each subband pulse profile is aligned by non-coherent dedispersion,and to generate a broadband pulse profile,which is basically the same as the pulse profile obtained from the original data using DSPSR.The experimental results show that the scheme for the QTT UWL receiving system is feasible,and the proposed channel algorithm in this paper is effective.展开更多
A telecommunication network used for the transmission of astronomical observation data,telescope remote control and other astronomical research purposes is a critical infrastructure.The monitoring and analysis of netw...A telecommunication network used for the transmission of astronomical observation data,telescope remote control and other astronomical research purposes is a critical infrastructure.The monitoring and analysis of network traffic,which help improve the network performance and the utilization of network resources,are a challenging task.The accurate identification of the astronomical data traffic will effectively improve transmission efficiency.In this paper,a classification method applied to types of traffic containing astronomical data using deep learning is proposed.The advantages of a convolutional neural network model in image classification are exploited to classify types of traffic containing astronomical data.The objective is to identify the mixed traffic in the network and accurately identify types of traffic containing astronomical data.The effectiveness of the model in improving classification accuracy is also discussed.Actual traffic data captured by Tcpdump and Wireshark are tested,and the experimental results indicate that the proposed method can accurately classify types of traffic containing astronomical data.展开更多
The extremely low frequency(f<40 MHz)is a very important frequency band for modern radio astronomy observations.It is also a key frequency band for solar radio bursts,planetary radio bursts,fast radio bursts detect...The extremely low frequency(f<40 MHz)is a very important frequency band for modern radio astronomy observations.It is also a key frequency band for solar radio bursts,planetary radio bursts,fast radio bursts detected in the lunar space electromagnetic environment,and the Earth’s middle and upper atmosphere with low dispersion values.In this frequency band,the solar stellar activity,the early state of the universe,and the radiation characteristics of the planetary magnetosphere and plasma layer can be explored.Since there are few observations with effective spatial resolution in the extremely low frequency,it is highly possible to discover unknown astronomical phenomena on such a band in the future.In conjunction with low frequency radio observation on the far side of the Moon,we initially set up a novel low-frequency radio array in the Qitai station of Xinjiang Astronomical Observatory deep in Tianshan Mountains,Xinjiang,China on 2021 August 23.The array covers an operating frequency range of 1~90 MHz with a sensitivity of-78 dBm/125kHz,a dynamic range of 72 dB,and a typical gain value of 6 dBi,which can realize unattended all-weather observations.The two antennas due south of the Qitai Low-Frequency Radio Array were put into trial observations on 2021 May 28,and the very quiet electromagnetic environment of the station has been confirmed.So far,many solar radio bursts and other foreign signals have been detected.The results show that this novel low frequency radio array has the advantages of good performance,strong direction,and high antenna efficiency.It can play a unique role in Solar Cycle 25,and has a potential value in prospective collaborative observation between the Earth and space for extremely low frequency radio astronomy.展开更多
Using the new soft X-ray data from the Macao Science Satellite-1,we studied a solar flare that occurred on 22 June 2023.We found that the centroids of the Ca(around 3.9 keV)and Fe(around 6.7 keV)line features exhibit ...Using the new soft X-ray data from the Macao Science Satellite-1,we studied a solar flare that occurred on 22 June 2023.We found that the centroids of the Ca(around 3.9 keV)and Fe(around 6.7 keV)line features exhibit a rapid shift toward higher energy channels during the flare's rising phase,followed by a gradual decrease during the decay phase.Through precise energy calibration,the centroids are determined with high accuracy.Temperature and velocity are then self-consistently derived by comparing the centroids with those calculated from the synthesized line features using the latest CHIANTI atomic database(ver.10.1).The calculated maximum velocity reaches up to 710±60 km s-1,which significantly exceeds the previously reported values.Our results suggest that the entire shift of soft X-ray lines may occur during the process of chromospheric evaporation.展开更多
As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and...As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and it has been widely applied across various fields.In the field of astronomy,AI techniques have demonstrated unique advantages,particularly in the identification of pulsars and their candidates.AI is able to address the challenges of pulsar celestial body identification and classification because of its accuracy and efficiency.This paper systematically surveys commonly used AI models for pulsar candidate identification,analyzing and discussing the typical applications of machine learning,artificial neural networks,convolutional neural networks,and generative adversarial networks in candidate identification.Furthermore,it explores how th.e introduction of AI techniques not only enhances the efficiency and accuracy of pulsar identification but also provides new perspectives and tools for pulsar survey data processing,thus playing a significant role in advancing pulsar research and the field of astronomy.展开更多
Strong flares and/or coronal mass ejections(CMEs) could bring us disastrous space weather,destroy crucial technology in space,and cause a large-scale blackout during some extreme cases.They frequently cause geomagneti...Strong flares and/or coronal mass ejections(CMEs) could bring us disastrous space weather,destroy crucial technology in space,and cause a large-scale blackout during some extreme cases.They frequently cause geomagnetic storms,which is a sudden disturbance of the Earth's magnetosphere.It is well accepted that CMEs play a dominant role in causing geomagnetic storms by a direct impact,but it is still not very clear regarding their association with solar flares.The association would be helpful for forecasting geomagnetic storms directly from flares,which are much easier to observe.The Macao Science Satellite-1(MSS-1) mission,with the scientific aim of studying the origin and evolution of the geomagnetic field,is able to accurately measure the vector geomagnetic field.Besides,it measures rapid spectral evolution of the solar X-ray irradiance of solar flares.In this study,we analyzed measurements by MSS-1 during a series of X-class flares in October of 2024,and saw the relationship between the flares and the associated geomagnetic storms.The observations support that the major geomagnetic storms tend to be associated with flares' duration in addition to flare class.We also find that long duration ones have radiated more energy in the extreme ultraviolet waveband.Being equally important,our results show that the magnetic fields measured by MSS-1,especially its external(e_(1)^(0)) coefficient,can well be used for monitoring the geomagnetic disturbance.展开更多
The emission of anomalous X-ray pulsars(AXPs)and soft gamma-ray repeaters(SGRs)is believed to be powered by the dissipation of their strong magnetic fields,which coined the name“magnetar”.By combining timing and ene...The emission of anomalous X-ray pulsars(AXPs)and soft gamma-ray repeaters(SGRs)is believed to be powered by the dissipation of their strong magnetic fields,which coined the name“magnetar”.By combining timing and energy observational results,the magnetar model can be easily appreciated.From a timing perspective,the magnetic field strengths of AXPs and SGRs,which are calculated under the assumption of dipole radiation,are extremely strong.From an energy perspective,the X-ray/soft gamma-ray luminosities of AXPs and SGRs are larger than their rotational energy loss rates(i.e.,L_(x>E_(rot)).It is thus reasonable to assume that the high-energy radiation comes from magnetic energy decay,and the magnetar model has been extensively discussed(or accepted).However,we argue that:(ⅰ)Calculating magnetic fields by assuming that rotational energy loss is dominated by dipole radiation(i.e.,E_(rot)■E_(μ))may be controversial,and we suggest that the energies carried by outflowing particles should also be considered.(ⅱ)The fact that X-ray luminosity is greater than the rotational energy loss rate does not necessarily mean that the emission energy comes from the magnetic field decaying,which requires further observational testing.Furthermore,some observational facts conflict with the“magnetar”model,such as observations of anti-magnetars,high magnetic field pulsars,and radio and X-ray observations of AXPs/SGRs.Therefore,we propose a crusted strange star model as an alternative,which can explain many more observational facts of AXPs/SGRs.展开更多
The subsurface convective zones (CZs) of massive stars significantly influence many of their key characteristics.Previous studies have paid little attention to the impact of rotation on the subsurface CZ,so we aim to ...The subsurface convective zones (CZs) of massive stars significantly influence many of their key characteristics.Previous studies have paid little attention to the impact of rotation on the subsurface CZ,so we aim to investigate the evolution of this zone in rapidly rotating massive stars.We use the Modules for Experiments in Stellar Astrophysics to simulate the subsurface CZs of massive stars during the main sequence phase.We establish stellar models with initial masses ranging from 5 M⊙to 120 M⊙,incorporating four metallicities (Z=0.02,0.006,0.002,and 0.0001) and three rotational velocities (ω/ωcrit=0,ω/ωcrit=0.50,andω/ωcrit=0.75).We find that rapid rotation leads to an expansion of the subsurface CZ,increases convective velocities,and promotes the development of this zone.Additionally,subsurface CZs can also emerge in stars with lower metallicities.Comparing our models with observations of massive stars in the Galaxy,the Large Magellanic Cloud,and the Small Magellanic Cloud,we find that rotating models better encompass the observed samples.Rotation significantly influences the evolution of the subsurface CZ in massive stars.By comparing with the observed microturbulence on the surfaces of OB stars,we propose that the subsurface CZs may be one of the sources of microturbulence.展开更多
Pulsar candidate identification is an indispensable task in pulsar science.Based on the characteristics of imbalanced and diverse pulsar data sets,and the lack of a unified processing framework,we first used dimension...Pulsar candidate identification is an indispensable task in pulsar science.Based on the characteristics of imbalanced and diverse pulsar data sets,and the lack of a unified processing framework,we first used dimensionality reduction and visualization to analyze potential deficiencies caused by the incompleteness of current data set extraction methods.We found that the limited use of non-pulsar data may lead to bias in the result,which may limit the generalization ability.Based on the dimensionality reduction results,we propose a Grid Group Uniform Sampling(GGUS) method.This data preprocessing method improves the performance of Random Forest,Support Vector Machine,Convolutional Neural Network,and Res Net50 models on Lyon’s features,diagnostic plots,and perioddispersion measure (period-DM) plots in the HTRU1 data set.The average recall increased by approximately0.5%,precision by nearly 2%,and F_(1) score by around 1.2%for all models and in all data sets.In the period-DM plots testing,the high-performance Res Net50 algorithm achieved over 98%F_(1) using random sampling.GGUS demonstrated further improvements in this test,enhancing the average F_(1) score,precision,and recall by approximately 0.07%,0.1%,and 0.03%,respectively.展开更多
This paper addresses the performance degradation issue in a fast radio burst search pipeline based on deep learning.This issue is caused by the class imbalance of the radio frequency interference samples in the traini...This paper addresses the performance degradation issue in a fast radio burst search pipeline based on deep learning.This issue is caused by the class imbalance of the radio frequency interference samples in the training dataset,and one solution is applied to improve the distribution of the training data by augmenting minority class samples using a deep convolutional generative adversarial network.Experi.mental results demonstrate that retraining the deep learning model with the newly generated dataset leads to a new fast radio burst classifier,which effectively reduces false positives caused by periodic wide-band impulsive radio frequency interference,thereby enhancing the performance of the search pipeline.展开更多
To address the issues of low accuracy and high computational complexity in traditional channelization techniques for ultra-wideband signals,this paper proposes a novel rationally oversampled channelization method to e...To address the issues of low accuracy and high computational complexity in traditional channelization techniques for ultra-wideband signals,this paper proposes a novel rationally oversampled channelization method to enhance the accuracy and efficiency of signal processing.The proposed method is evaluated by implementing and comparing critically sampled and integer oversampled channelization algorithms.A detailed analysis of the impact of different oversampling factors and filter orders on performance is provided.The validity of the proposed algorithm is verified using baseband data from pulsar J0437−4715 observed by the Parkes telescope,demonstrating its effectiveness and correctness.展开更多
基金supported by National Key R&D Program of China No.2021YFC2203502the National Natural Science Foundation of China (NSFC)(11803080,12173077,11873082,12003062)+2 种基金the Tianshan Innovation Team Plan of Xinjiang Uygur Autonomous Region (2022D14020)the Youth Innovation Promotion Association CASNational Key R&D Program of China No.2018 YFA0404704。
文摘The Xinjiang Astronomical Observatory Data Center faces issues related to delay-affected services. As a result, these services cannot be implemented in a timely manner due to the overloading of transmission links. In this paper, the software-defined network technology is applied to the Xinjiang Astronomical Observatory Data Center Network(XAODCN). Specifically, a novel reconfiguration method is proposed to realise the software-defined Xinjiang Astronomical Observatory Data Center Network(SDXAO-DCN), and a network model is constructed. To overcome the congestion problem, a traffic load-balancing algorithm is designed for fast transmission of the service traffic by combining three factors: network structure, congestion level and transmission service. The proposed algorithm is compared with current commonly load-balancing algorithms which are used in data center to verify its efficiency. Simulation experiments show that the algorithm improved transmission performance and transmission quality for the SDXAO-DCN.
基金supported by the National Key R&D Program of China (Nos. 2022YFF0711502 and 2021YFC2203502)the National Natural Science Foundation of China (NSFC)(12173077 and 12003062)+6 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 Autonomous Region (2022D01A360)supported by Astronomical Big Data Joint Research Center,co-founded by National Astronomical Observatories,Chinese Academy of Sciences。
文摘Cross-matching is a key technique to achieve fusion of multi-band astronomical catalogs. Due to different equipment such as various astronomical telescopes, the existence of measurement errors, and proper motions of the celestial bodies, the same celestial object will have different positions in different catalogs, making it difficult to integrate multi-band or full-band astronomical data. In this study, we propose an online cross-matching method based on pseudo-spherical indexing techniques and develop a service combining with high performance computing system(Taurus) to improve cross-matching efficiency, which is designed for the Data Center of Xinjiang Astronomical Observatory. Specifically, we use Quad Tree Cube to divide the spherical blocks of the celestial object and map the 2D space composed of R.A. and decl. to 1D space and achieve correspondence between real celestial objects and spherical patches. Finally, we verify the performance of the service using Gaia 3 and PPMXL catalogs. Meanwhile, we send the matching results to VO tools-Topcat and Aladin respectively to get visual results. The experimental results show that the service effectively solves the speed bottleneck problem of crossmatching caused by frequent I/O, and significantly improves the retrieval and matching speed of massive astronomical data.
基金supported by the National Key R&D Program of China(2021YFC2203502 and 2022YFF0711502)the National Natural Science Foundation of China(NSFC)(12173077)+4 种基金the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095 and 2023TSYCCX0112)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(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 SciencesNatural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360).
文摘Astronomical spectroscopy is crucial for exploring the physical properties,chemical composition,and kinematic behavior of celestial objects.With continuous advancements in observational technology,astronomical spectroscopy faces the dual challenges of rapidly expanding data volumes and relatively lagging data processing capabilities.In this context,the rise of artificial intelligence technologies offers an innovative solution to address these challenges.This paper analyzes the latest developments in the application of machine learning for astronomical spectral data mining and discusses future research directions in AI-based spectral studies.However,the application of machine learning technologies presents several challenges.The high complexity of models often comes with insufficient interpretability,complicating scientific understanding.Moreover,the large-scale computational demands place higher requirements on hardware resources,leading to a significant increase in computational costs.AI-based astronomical spectroscopy research should advance in the following key directions.First,develop efficient data augmentation techniques to enhance model generalization capabilities.Second,explore more interpretable model designs to ensure the reliability and transparency of scientific conclusions.Third,optimize computational efficiency and reduce the threshold for deep-learning applications through collaborative innovations in algorithms and hardware.Furthermore,promoting the integration of cross-band data processing is essential to achieve seamless integration and comprehensive analysis of multi-source data,providing richer,multidimensional information to uncover the mysteries of the universe.
文摘We evaluate the performance of the first generation scientific CMOS （sC- MOS） camera used for astronomical observations. The sCMOS camera was attached to a 25 cm telescope at Xinglong Observatory, in order to estimate its photometric capabilities. We further compared the capabilities of the sCMOS camera with that of full-frame and electron multiplying CCD cameras in laboratory tests and observations. The results indicate the sCMOS camera is capable of performing photometry of bright sources, especially when high spatial resolution or temporal resolution is desired.
基金This work is supported by National Key R&D Program of China No.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Artificial Intelligence(AI)is an interdisciplinary research field with widespread applications.It aims at developing theoretical,methodological,technological,and applied systems that simulate,enhance,and assist human intelligence.Recently,notable accomplishments of artificial intelligence technology have been achieved in astronomical data processing,establishing this technology as central to numerous astronomical research areas such as radio astronomy,stellar and galactic(Milky Way)studies,exoplanets surveys,cosmology,and solar physics.This article systematically reviews representative applications of artificial intelligence technology to astronomical data processing,with comprehensive description of specific cases:pulsar candidate identification,fast radio burst detection,gravitational wave detection,spectral classification,and radio frequency interference mitigation.Furthermore,it discusses possible future applications to provide perspectives for astronomical research in the artificial intelligence era.
文摘Selecting a good site for ground-based astronomy is very important. Based on the ERA-Interim global reanalysis data, this paper studied the atmospheric conditions of the Qitai Telescope(QTT) site from the aspects of absolute humidity, mixing ratio and precipitable water vapor(PWV). Error estimations of meteorological parameters are also analyzed. These primary results show that the QTT site has obvious advantages in terms of conditions with much less atmospheric water vapor than two well-known existing sites with 100-meter-aperture radio telescopes in the world. In addition, due to the influence of atmospheric water vapor on radio observations, the atmospheric transmittance for each frequency band of the site are simulated, and the atmospheric opacity is also calculated as well as Planck radiation brightness. Based on these results, the effective observational time of different bands is further estimated.
基金supported by the National Key R&D Program of China(Nos.2021YFC2203502 and 2022YFF0711502)the National Natural Science Foundation of China(NSFC,Nos.12173077 and 12003062)+6 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)administrated by the Chinese Academy of Sciences(CAS)Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360)。
文摘Digital channelization decomposes a wideband signal into multiple adjacent sub-bands using Parallel Technology.Channelization can effectively reduce the pressure on the radio astronomy digital backends system and make wideband signal processing possible.Aiming at the problems of signal attenuation at sub-band edge,spectral leakage and aliasing encountered in wideband signal channelization,algorithms to reduce the problems are studied.We design a Critically Sampled Polyphase Filter Bank(CS-PFB)based on the Finite Impulse Response digital filter with a Hamming Window and systematically analyze the frequency response characteristics of the CS-PFB.Based on the channelized structure of the CS-PFB,an Over Sampled Polyphase Filter Bank(OS-PFB)is designed by data reuse,and the filtering frequency response characteristics of CS-PFB and OS-PFB are compared and analyzed.Using the wideband baseband data generated by the CASPSR(Collaboration for Astronomy Signal processing and electronics research Parkes Swinburne Recorder),we implement sub-band division and 16-band output of these data based on the 2×oversampling OS-PFB,and the problem of spectrum inversion in the sub-bands is corrected.After removing 25%of redundant data in the head and tail of each sub-band,we recombine the sub-bands into a wideband.The wideband signal is almost identical to the original observed signal.Therefore,the experimental results show that the OS-PFB can improve the channel response.For the 400 MHz baseband data of J0437-4715,we compare the pulse profile obtained from the original baseband data with the pulse profile obtained after the channelization and recombination.The phase and amplitude information of the pulse profiles are consistent,which verifies the correctness of our channelization algorithm.
基金partly supported by the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administered by the Chinese Academy of Sciences(CAS)supported by the National Natural Science Foundation of China(Grant Nos.11573054,11703065,11603044 and 11873081)+1 种基金support from a CAS PIFIUK STFC grant ST/R006598/1。
文摘A large ground-based optical/infrared telescope is being planned for a world-class astronomical site in China.The cloud-free night percentage is the primary meteorological consideration for evaluating candidate sites.The data from GMS and NOAA satellites and the MODIS instrument were utilized in this research,covering the period from 1996 to 2015.Our data analysis benefits from overlapping results from different independent teams as well as a uniform analysis of selected sites using GMS+NOAA data.Although significant ground-based monitoring is needed to validate these findings,we identify three different geographical regions with a high percentage of cloud-free conditions(~83%on average),which is slightly lower than at Mauna Kea and Cerro Armazones(~85%on average)and were chosen for the large international projects TMT and ELT respectively.Our study finds evidence that cloud distributions and the seasonal changes affected by the prevailing westerly winds and summer monsoons reduce the cloud cover in areas influenced by the westerlies.This is consistent with the expectations from climate change models and is suggestive that most of the identified sites will have reduced cloud cover in the future.
基金supported by the National Key Research and Development Program of China (2022YFF0711502)the National Natural Science Foundation of China (NSFC) (12273025 and 12133010)supported by China National Astronomical Data Center (NADC), CAS Astronomical Data Center and Chinese Virtual Observatory (China-VO)。
文摘Location-based cross-matching is a preprocessing step in astronomy that aims to identify records belonging to the same celestial body based on the angular distance formula. The traditional approach involves comparing each record in one catalog with every record in the other catalog, resulting in a one-to-one comparison with high computational complexity. To reduce the computational time, index partitioning methods are used to divide the sky into regions and perform local cross-matching. In addition, cross-matching algorithms have been adopted on highperformance architectures to improve their efficiency. But the index partitioning methods and computation architectures only increase the degree of parallelism, and cannot decrease the complexity of pairwise-based crossmatching algorithm itself. A better algorithm is needed to further improve the performance of cross-matching algorithm. In this paper, we propose a 3d-tree-based cross-matching algorithm that converts the angular distance formula into an equivalent 3dEuclidean distance and uses 3d-tree method to reduce the overall computational complexity and to avoid boundary issues. Furthermore, we demonstrate the superiority of the 3d-tree approach over the 2d-tree method and implement it using a multi-threading technique during both the construction and querying phases. We have experimentally evaluated the proposed 3d-tree cross-matching algorithm using publicly available catalog data. The results show that our algorithm applied on two 32-core CPUs achieves equivalent performance than previous experiments conducted on a six-node CPU-GPU cluster.
基金supported by the National Key R&D Program of China(Nos.2021YFC2203502,2022YFF0711502)the National Natural Science Foundation of China(NSFC,Grant Nos.12173077,12003062)+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Aiming at the subband division of ultra-wide bandwidth low-frequency(UWL)signal(frequency coverage range:704–4032 MHz)of the Xinjiang 110 m QiTai radio Telescope(QTT),a scheme of ultra-wide bandwidth signal is designed.First,we analyze the effect of different window functions such as the Hanning window,Hamming window,and Kaiser window on the performance of finite impulse response(FIR)digital filters,and implement a critical sampling polyphase filter bank(CS-PFB)based on the Hamming window FIR digital filter.Second,we generate 3328 MHz simulation data of ultra-wideband pulsar baseband in the frequency range of 704–4032 MHz using the ultra-wide bandwidth pulsar baseband data generation algorithm based on the 400 MHz bandwidth pulsar baseband data obtained from Parkes CASPSR observations.Third,we obtain 26 subbands of 128 MHz based on CS-PFB and the simulation data,and the pulse profile of each subband by coherent dispersion,integration,and folding.Finally,the phase of each subband pulse profile is aligned by non-coherent dedispersion,and to generate a broadband pulse profile,which is basically the same as the pulse profile obtained from the original data using DSPSR.The experimental results show that the scheme for the QTT UWL receiving system is feasible,and the proposed channel algorithm in this paper is effective.
基金supported by the National Key R&D Program of China(Nos.2021YFC2203502 and 2022YFF0711502)Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360)+6 种基金the National Natural Science Foundation of China(NSFC)(12173077 and 12003062)the Tianshan Innovation Team Plan of Xinjiang Uygur Autonomous Region(2022D14020)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(Grant No.PTYQ2022YZZD01)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)supported by Astronomical Big Data Joint Research Centerco-founded by National Astronomical Observatories,Chinese Academy of Sciences。
文摘A telecommunication network used for the transmission of astronomical observation data,telescope remote control and other astronomical research purposes is a critical infrastructure.The monitoring and analysis of network traffic,which help improve the network performance and the utilization of network resources,are a challenging task.The accurate identification of the astronomical data traffic will effectively improve transmission efficiency.In this paper,a classification method applied to types of traffic containing astronomical data using deep learning is proposed.The advantages of a convolutional neural network model in image classification are exploited to classify types of traffic containing astronomical data.The objective is to identify the mixed traffic in the network and accurately identify types of traffic containing astronomical data.The effectiveness of the model in improving classification accuracy is also discussed.Actual traffic data captured by Tcpdump and Wireshark are tested,and the experimental results indicate that the proposed method can accurately classify types of traffic containing astronomical data.
基金supported by“SKA(No.2020SKA0110300)”“Yunnan Key Laboratory of the Solar Physics and Space Science(No.YNSPCC202220),”+3 种基金“The open project of the Key Laboratory in Xinjiang Uygur Autonomous Region of China(No.2023D04058)”the“National Natural Science Foundation of China(No.11941003)”“The Chinese Academy of Sciences Foundation of the young scholars of western(No.2020-XBQNXZ-019)”“The 2018 Project of Xinjiang Uygur Autonomous Region of China for Heaven Lake Hundred-Talent Program”。
文摘The extremely low frequency(f<40 MHz)is a very important frequency band for modern radio astronomy observations.It is also a key frequency band for solar radio bursts,planetary radio bursts,fast radio bursts detected in the lunar space electromagnetic environment,and the Earth’s middle and upper atmosphere with low dispersion values.In this frequency band,the solar stellar activity,the early state of the universe,and the radiation characteristics of the planetary magnetosphere and plasma layer can be explored.Since there are few observations with effective spatial resolution in the extremely low frequency,it is highly possible to discover unknown astronomical phenomena on such a band in the future.In conjunction with low frequency radio observation on the far side of the Moon,we initially set up a novel low-frequency radio array in the Qitai station of Xinjiang Astronomical Observatory deep in Tianshan Mountains,Xinjiang,China on 2021 August 23.The array covers an operating frequency range of 1~90 MHz with a sensitivity of-78 dBm/125kHz,a dynamic range of 72 dB,and a typical gain value of 6 dBi,which can realize unattended all-weather observations.The two antennas due south of the Qitai Low-Frequency Radio Array were put into trial observations on 2021 May 28,and the very quiet electromagnetic environment of the station has been confirmed.So far,many solar radio bursts and other foreign signals have been detected.The results show that this novel low frequency radio array has the advantages of good performance,strong direction,and high antenna efficiency.It can play a unique role in Solar Cycle 25,and has a potential value in prospective collaborative observation between the Earth and space for extremely low frequency radio astronomy.
文摘Using the new soft X-ray data from the Macao Science Satellite-1,we studied a solar flare that occurred on 22 June 2023.We found that the centroids of the Ca(around 3.9 keV)and Fe(around 6.7 keV)line features exhibit a rapid shift toward higher energy channels during the flare's rising phase,followed by a gradual decrease during the decay phase.Through precise energy calibration,the centroids are determined with high accuracy.Temperature and velocity are then self-consistently derived by comparing the centroids with those calculated from the synthesized line features using the latest CHIANTI atomic database(ver.10.1).The calculated maximum velocity reaches up to 710±60 km s-1,which significantly exceeds the previously reported values.Our results suggest that the entire shift of soft X-ray lines may occur during the process of chromospheric evaporation.
基金supported by the National Key R&D Program of China(2021YFC2203502 and 2022YFF0711502)the National Natural Science Foundation of China(NSFC)(12173077)+4 种基金the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095 and 2023TSYCCX0112)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(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 Autonomous Region(2022D01A360)。
文摘As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and it has been widely applied across various fields.In the field of astronomy,AI techniques have demonstrated unique advantages,particularly in the identification of pulsars and their candidates.AI is able to address the challenges of pulsar celestial body identification and classification because of its accuracy and efficiency.This paper systematically surveys commonly used AI models for pulsar candidate identification,analyzing and discussing the typical applications of machine learning,artificial neural networks,convolutional neural networks,and generative adversarial networks in candidate identification.Furthermore,it explores how th.e introduction of AI techniques not only enhances the efficiency and accuracy of pulsar identification but also provides new perspectives and tools for pulsar survey data processing,thus playing a significant role in advancing pulsar research and the field of astronomy.
基金funded by NSFC under grants 12250014, 42250101 and 12403068supported by youth funding of Jiangsu province BK20241707+1 种基金supported by the Macao FoundationXinjiang Uygur Autonomous Region for the support through “Tianchi Talent” special expert project。
文摘Strong flares and/or coronal mass ejections(CMEs) could bring us disastrous space weather,destroy crucial technology in space,and cause a large-scale blackout during some extreme cases.They frequently cause geomagnetic storms,which is a sudden disturbance of the Earth's magnetosphere.It is well accepted that CMEs play a dominant role in causing geomagnetic storms by a direct impact,but it is still not very clear regarding their association with solar flares.The association would be helpful for forecasting geomagnetic storms directly from flares,which are much easier to observe.The Macao Science Satellite-1(MSS-1) mission,with the scientific aim of studying the origin and evolution of the geomagnetic field,is able to accurately measure the vector geomagnetic field.Besides,it measures rapid spectral evolution of the solar X-ray irradiance of solar flares.In this study,we analyzed measurements by MSS-1 during a series of X-class flares in October of 2024,and saw the relationship between the flares and the associated geomagnetic storms.The observations support that the major geomagnetic storms tend to be associated with flares' duration in addition to flare class.We also find that long duration ones have radiated more energy in the extreme ultraviolet waveband.Being equally important,our results show that the magnetic fields measured by MSS-1,especially its external(e_(1)^(0)) coefficient,can well be used for monitoring the geomagnetic disturbance.
基金supported by the National Natural Science Foundation of China(12273008,12025303,12403046)the National SKA Program of China(2022SKA0130104)+3 种基金the Natural Science and Technology Foundation of Guizhou Province(QiankehejichuMS[2025]266,[2023]024,ZK[2022]304)the Foundation of Guizhou Provincial Education Department(KY(2020)003)the Academic New Seedling Fund Project of Guizhou Normal University([2022]B18)the Major Science and Technology Program of Xinjiang Uygur Autonomous Region(2022A03013-4).
文摘The emission of anomalous X-ray pulsars(AXPs)and soft gamma-ray repeaters(SGRs)is believed to be powered by the dissipation of their strong magnetic fields,which coined the name“magnetar”.By combining timing and energy observational results,the magnetar model can be easily appreciated.From a timing perspective,the magnetic field strengths of AXPs and SGRs,which are calculated under the assumption of dipole radiation,are extremely strong.From an energy perspective,the X-ray/soft gamma-ray luminosities of AXPs and SGRs are larger than their rotational energy loss rates(i.e.,L_(x>E_(rot)).It is thus reasonable to assume that the high-energy radiation comes from magnetic energy decay,and the magnetar model has been extensively discussed(or accepted).However,we argue that:(ⅰ)Calculating magnetic fields by assuming that rotational energy loss is dominated by dipole radiation(i.e.,E_(rot)■E_(μ))may be controversial,and we suggest that the energies carried by outflowing particles should also be considered.(ⅱ)The fact that X-ray luminosity is greater than the rotational energy loss rate does not necessarily mean that the emission energy comes from the magnetic field decaying,which requires further observational testing.Furthermore,some observational facts conflict with the“magnetar”model,such as observations of anti-magnetars,high magnetic field pulsars,and radio and X-ray observations of AXPs/SGRs.Therefore,we propose a crusted strange star model as an alternative,which can explain many more observational facts of AXPs/SGRs.
基金the National Natural Science Foundation of China under grant Nos.U2031204,12163005,12373038,12288102,and 12263006the science research grant from the China Manned Space Project with No.CMSCSST-2021-A10+1 种基金the Natural Science Foundation of Xinjiang Nos.2022D01D85 and 2022TSYCLJ0006the Major Science and Technology Program of Xinjiang Uygur Autonomous Region under grant No.2022A03013-3.
文摘The subsurface convective zones (CZs) of massive stars significantly influence many of their key characteristics.Previous studies have paid little attention to the impact of rotation on the subsurface CZ,so we aim to investigate the evolution of this zone in rapidly rotating massive stars.We use the Modules for Experiments in Stellar Astrophysics to simulate the subsurface CZs of massive stars during the main sequence phase.We establish stellar models with initial masses ranging from 5 M⊙to 120 M⊙,incorporating four metallicities (Z=0.02,0.006,0.002,and 0.0001) and three rotational velocities (ω/ωcrit=0,ω/ωcrit=0.50,andω/ωcrit=0.75).We find that rapid rotation leads to an expansion of the subsurface CZ,increases convective velocities,and promotes the development of this zone.Additionally,subsurface CZs can also emerge in stars with lower metallicities.Comparing our models with observations of massive stars in the Galaxy,the Large Magellanic Cloud,and the Small Magellanic Cloud,we find that rotating models better encompass the observed samples.Rotation significantly influences the evolution of the subsurface CZ in massive stars.By comparing with the observed microturbulence on the surfaces of OB stars,we propose that the subsurface CZs may be one of the sources of microturbulence.
基金supported by the National Key Research and Development Program of China under grant No.2018YFA0404603supported by the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China (MOF) and administered by the Chinese Academy of Sciences (CAS)。
文摘Pulsar candidate identification is an indispensable task in pulsar science.Based on the characteristics of imbalanced and diverse pulsar data sets,and the lack of a unified processing framework,we first used dimensionality reduction and visualization to analyze potential deficiencies caused by the incompleteness of current data set extraction methods.We found that the limited use of non-pulsar data may lead to bias in the result,which may limit the generalization ability.Based on the dimensionality reduction results,we propose a Grid Group Uniform Sampling(GGUS) method.This data preprocessing method improves the performance of Random Forest,Support Vector Machine,Convolutional Neural Network,and Res Net50 models on Lyon’s features,diagnostic plots,and perioddispersion measure (period-DM) plots in the HTRU1 data set.The average recall increased by approximately0.5%,precision by nearly 2%,and F_(1) score by around 1.2%for all models and in all data sets.In the period-DM plots testing,the high-performance Res Net50 algorithm achieved over 98%F_(1) using random sampling.GGUS demonstrated further improvements in this test,enhancing the average F_(1) score,precision,and recall by approximately 0.07%,0.1%,and 0.03%,respectively.
基金supported by the Chinese Academy of Science"Light of West China"Program(2022-XBQNXZ-015)the National Natural Science Foundation of China(11903071)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China and administered by the Chinese Academy of Sciences。
文摘This paper addresses the performance degradation issue in a fast radio burst search pipeline based on deep learning.This issue is caused by the class imbalance of the radio frequency interference samples in the training dataset,and one solution is applied to improve the distribution of the training data by augmenting minority class samples using a deep convolutional generative adversarial network.Experi.mental results demonstrate that retraining the deep learning model with the newly generated dataset leads to a new fast radio burst classifier,which effectively reduces false positives caused by periodic wide-band impulsive radio frequency interference,thereby enhancing the performance of the search pipeline.
基金supported by the National Key R&D Program of China Nos.2021YFC2203502 and 2022YFF0711502the National Natural Science Foundation of China(NSFC)(12173077)+5 种基金the Chinese Academy of Sciences(CAS)“Light of West China”Program(No.xbzg-zdsys-202410)the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095 and 2023TSYCCX0112)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 issues of low accuracy and high computational complexity in traditional channelization techniques for ultra-wideband signals,this paper proposes a novel rationally oversampled channelization method to enhance the accuracy and efficiency of signal processing.The proposed method is evaluated by implementing and comparing critically sampled and integer oversampled channelization algorithms.A detailed analysis of the impact of different oversampling factors and filter orders on performance is provided.The validity of the proposed algorithm is verified using baseband data from pulsar J0437−4715 observed by the Parkes telescope,demonstrating its effectiveness and correctness.
