This paper presents the design,calibration,and survey strategy of the Fast Radio Burst(FRB)digital backend and its real-time data processing pipeline employed in the Tianlai Cylinder Pathfinder Array.The array,consist...This paper presents the design,calibration,and survey strategy of the Fast Radio Burst(FRB)digital backend and its real-time data processing pipeline employed in the Tianlai Cylinder Pathfinder Array.The array,consisting of three parallel cylindrical reflectors and equipped with 96 dual-polarization feeds,is a radio interferometer array designed for conducting drift scans of the northern celestial semi-sphere.The FRB digital backend enables the formation of 96 digital beams,effectively covering an area of approximately 40 square degrees with the 3 dB beam.Our pipeline demonstrates the capability to conduct an automatic search of FRBs,detecting at quasi-realtime and classifying FRB candidates automatically.The current FRB searching pipeline has an overall recall rate of88%.During the commissioning phase,we successfully detected signals emitted by four well-known pulsars:PSR B0329+54,B2021+51,B0823+26,and B2020+28.We report the first discovery of an FRB by our array,designated as FRB 20220414A.We also investigate the optimal arrangement for the digitally formed beams to achieve maximum detection rate by numerical simulation.展开更多
In gamma-ray burst prompt emission,there is still no consistent conclusion if the precursor and main burst share the same origin.In this paper,we try to study this issue based on the relationship between pulse width a...In gamma-ray burst prompt emission,there is still no consistent conclusion if the precursor and main burst share the same origin.In this paper,we try to study this issue based on the relationship between pulse width and energy of the precursor and main burst.We systematically search the light curve data observed by Swift/BAT and Fermi/GBM,and find 13 long bursts with well-structured precursors and main bursts.After fitting the precursor light curve of each different energy channel with the Norris function,we find that there is not only a power-law relationship between precursor width and energy,but also a power-law relationship between the ratio of the rising width to the decaying width and energy.By comparing the relationship between the precursors and the main burst pulses,we find that the distribution of the precursors and the relationship between the power-law indices are roughly the same as those of the main burst.In addition,it is found that the precursor width distribution as well as the upper limit of the pulse width ratio does not exceed 1 and both are asymmetric,which are also consistent with the main burst.These indicate that the precursor and the main burst are indistinguishable,and the precursor and the main burst may have the same physical origin.展开更多
Pulsar detection has become an active research topic in radio astronomy recently.One of the essential procedures for pulsar detection is pulsar candidate sifting(PCS),a procedure for identifying potential pulsar signa...Pulsar detection has become an active research topic in radio astronomy recently.One of the essential procedures for pulsar detection is pulsar candidate sifting(PCS),a procedure for identifying potential pulsar signals in a survey.However,pulsar candidates are always class-imbalanced,as most candidates are non-pulsars such as RFI and only a tiny part of them are from real pulsars.Class imbalance can greatly affect the performance of machine learning(ML)models,resulting in a heavy cost as some real pulsars are misjudged.To deal with the problem,techniques of choosing relevant features to discriminate pulsars from non-pulsars are focused on,which is known as feature selection.Feature selection is a process of selecting a subset of the most relevant features from a feature pool.The distinguishing features between pulsars and non-pulsars can significantly improve the performance of the classifier even if the data are highly imbalanced.In this work,an algorithm for feature selection called the K-fold Relief-Greedy(KFRG)algorithm is designed.KFRG is a two-stage algorithm.In the first stage,it filters out some irrelevant features according to their K-fold Relief scores,while in the second stage,it removes the redundant features and selects the most relevant features by a forward greedy search strategy.Experiments on the data set of the High Time Resolution Universe survey verified that ML models based on KFRG are capable of PCS,correctly separating pulsars from non-pulsars even if the candidates are highly class-imbalanced.展开更多
For high-precision pulsar timing analysis and low-frequency gravitational wave detection,it is essential to accurately determine pulsar pulse times of arrival(ToAs)and associated uncertainties.To measure the ToAs and ...For high-precision pulsar timing analysis and low-frequency gravitational wave detection,it is essential to accurately determine pulsar pulse times of arrival(ToAs)and associated uncertainties.To measure the ToAs and their uncertainties,various cross-correlation-based techniques can be employed.We develop methodologies to investigate the impact of the template-matching method,profile shape,signal-to-noise ratio of both template and observation on ToA uncertainties.These methodologies are then applied to data from the International Pulsar Timing Array.We demonstrate that the Fourier domain Markov chain Monte Carlo method is generally superior to other methods,while the Gaussian interpolation shift method outperforms other methods in certain cases,such as profiles with large duty cycles or smooth profiles without sharp features.However,it is important to note that our study focuses solely on ToA uncertainty,and the optimal method for determining both ToA and ToA uncertainty may differ.展开更多
The increasing radio frequency interference(RFI)is a well-recognized problem in radio astronomy research.Pulsars and Fast Radio Bursts(FRBs)are high-priority science targets of the ongoing Commercial Radio Astronomy F...The increasing radio frequency interference(RFI)is a well-recognized problem in radio astronomy research.Pulsars and Fast Radio Bursts(FRBs)are high-priority science targets of the ongoing Commercial Radio Astronomy FAST Survey(CRAFTS).To improve the quality of RFI removal in searches of pulsars and FRBs based on CRAFTS multi-beam data,we here propose an intuitive but powerful RFI mitigation pipeline(CCF-ST).The“CCF-ST”is a spatial filter constructed by signal cross-correlation function(CCF)and Sum-Threshold(ST)algorithm.The RFI marking result is saved in a“mask”file,a binary format for RFI masks in PRESTO.Three known pulsars,PSR B0525-21,PSR B0621-04,and PSR J0943+2252 from CRAFTS L-band 19 beams data are used for evaluation of the performance of CCF-ST in comparison with other methods,such as PRESTO’s“rfifind”,ArPLS-ST and ArPLS-SF.The result shows that CCF-ST can reduce effective data loss rate and improves the detected signal-to-noise ratio of the pulsations by~26%and~18%respectively compared with PRESTO’s“rfifind”and ArPLS-ST.The CCF-ST also has the advantage of low computational cost,e.g.,reducing the time consumption by~40%and memory consumption by~90%compared with ArPLS-SF.We expect that the new RFI mitigation and analysis toolkit(CCF-ST)demonstrated in this paper can be applied to CRAFTS and other multi-beam telescope observations to improve the data quality and efficiency of pulsar and FRB searches.展开更多
We present a method by using the phase characteristics of radio observation data for pulsar search and candidate identification.The phase characteristics are relations between the pulsar signal and the phase correctio...We present a method by using the phase characteristics of radio observation data for pulsar search and candidate identification.The phase characteristics are relations between the pulsar signal and the phase correction in the frequency-domain,and we regard it as a new search diagnostic characteristic.Based on the phase characteristics,a search method is presented:calculating dispersion measure(DM)—frequency data to select candidate frequencies,and then confirming of candidates by using the broadband characteristics of pulsar signals.Based on this method,we performed a search test on short observation data of M15 and M71,which were observed by Five-hundredmeter Aperture Spherical radio Telescope,and some of the Galactic Plane Pulsar Snapshot survey data.Results show that it can get similar search results to PRESTO(Pulsa R Exploration and Search TOolkit)while having a faster processing speed.展开更多
基金support of the National SKA program of China(Nos.2022SKA0110100 and 2022SKA0110101)the National Natural Science Foundation of China(NSFC,Grant Nos.1236114814,12203061,12273070,and 12303004)。
文摘This paper presents the design,calibration,and survey strategy of the Fast Radio Burst(FRB)digital backend and its real-time data processing pipeline employed in the Tianlai Cylinder Pathfinder Array.The array,consisting of three parallel cylindrical reflectors and equipped with 96 dual-polarization feeds,is a radio interferometer array designed for conducting drift scans of the northern celestial semi-sphere.The FRB digital backend enables the formation of 96 digital beams,effectively covering an area of approximately 40 square degrees with the 3 dB beam.Our pipeline demonstrates the capability to conduct an automatic search of FRBs,detecting at quasi-realtime and classifying FRB candidates automatically.The current FRB searching pipeline has an overall recall rate of88%.During the commissioning phase,we successfully detected signals emitted by four well-known pulsars:PSR B0329+54,B2021+51,B0823+26,and B2020+28.We report the first discovery of an FRB by our array,designated as FRB 20220414A.We also investigate the optimal arrangement for the digitally formed beams to achieve maximum detection rate by numerical simulation.
基金supported by the National Natural Science Foundation of China(NSFC,Grant Nos.12163007,11763009)。
文摘In gamma-ray burst prompt emission,there is still no consistent conclusion if the precursor and main burst share the same origin.In this paper,we try to study this issue based on the relationship between pulse width and energy of the precursor and main burst.We systematically search the light curve data observed by Swift/BAT and Fermi/GBM,and find 13 long bursts with well-structured precursors and main bursts.After fitting the precursor light curve of each different energy channel with the Norris function,we find that there is not only a power-law relationship between precursor width and energy,but also a power-law relationship between the ratio of the rising width to the decaying width and energy.By comparing the relationship between the precursors and the main burst pulses,we find that the distribution of the precursors and the relationship between the power-law indices are roughly the same as those of the main burst.In addition,it is found that the precursor width distribution as well as the upper limit of the pulse width ratio does not exceed 1 and both are asymmetric,which are also consistent with the main burst.These indicate that the precursor and the main burst are indistinguishable,and the precursor and the main burst may have the same physical origin.
基金support from the National Natural Science Foundation of China(NSFC,grant Nos.11973022 and 12373108)the Natural Science Foundation of Guangdong Province(No.2020A1515010710)Hanshan Normal University Startup Foundation for Doctor Scientific Research(No.QD202129)。
文摘Pulsar detection has become an active research topic in radio astronomy recently.One of the essential procedures for pulsar detection is pulsar candidate sifting(PCS),a procedure for identifying potential pulsar signals in a survey.However,pulsar candidates are always class-imbalanced,as most candidates are non-pulsars such as RFI and only a tiny part of them are from real pulsars.Class imbalance can greatly affect the performance of machine learning(ML)models,resulting in a heavy cost as some real pulsars are misjudged.To deal with the problem,techniques of choosing relevant features to discriminate pulsars from non-pulsars are focused on,which is known as feature selection.Feature selection is a process of selecting a subset of the most relevant features from a feature pool.The distinguishing features between pulsars and non-pulsars can significantly improve the performance of the classifier even if the data are highly imbalanced.In this work,an algorithm for feature selection called the K-fold Relief-Greedy(KFRG)algorithm is designed.KFRG is a two-stage algorithm.In the first stage,it filters out some irrelevant features according to their K-fold Relief scores,while in the second stage,it removes the redundant features and selects the most relevant features by a forward greedy search strategy.Experiments on the data set of the High Time Resolution Universe survey verified that ML models based on KFRG are capable of PCS,correctly separating pulsars from non-pulsars even if the candidates are highly class-imbalanced.
基金support by the Deutsche Forschungsgemeinschaft(DFG)through the Heisenberg program(Project No.433075039)。
文摘For high-precision pulsar timing analysis and low-frequency gravitational wave detection,it is essential to accurately determine pulsar pulse times of arrival(ToAs)and associated uncertainties.To measure the ToAs and their uncertainties,various cross-correlation-based techniques can be employed.We develop methodologies to investigate the impact of the template-matching method,profile shape,signal-to-noise ratio of both template and observation on ToA uncertainties.These methodologies are then applied to data from the International Pulsar Timing Array.We demonstrate that the Fourier domain Markov chain Monte Carlo method is generally superior to other methods,while the Gaussian interpolation shift method outperforms other methods in certain cases,such as profiles with large duty cycles or smooth profiles without sharp features.However,it is important to note that our study focuses solely on ToA uncertainty,and the optimal method for determining both ToA and ToA uncertainty may differ.
基金supported by National Natural Science Foundation of China(NSFC)under Nos.11988101,U183110134,11703047,11773041,and U1831131support by the Youth Innovation Promotion Association CAS(id.2021055)cultivation project for FAST scientific payoff and research achievement of CAMS-CAS。
文摘The increasing radio frequency interference(RFI)is a well-recognized problem in radio astronomy research.Pulsars and Fast Radio Bursts(FRBs)are high-priority science targets of the ongoing Commercial Radio Astronomy FAST Survey(CRAFTS).To improve the quality of RFI removal in searches of pulsars and FRBs based on CRAFTS multi-beam data,we here propose an intuitive but powerful RFI mitigation pipeline(CCF-ST).The“CCF-ST”is a spatial filter constructed by signal cross-correlation function(CCF)and Sum-Threshold(ST)algorithm.The RFI marking result is saved in a“mask”file,a binary format for RFI masks in PRESTO.Three known pulsars,PSR B0525-21,PSR B0621-04,and PSR J0943+2252 from CRAFTS L-band 19 beams data are used for evaluation of the performance of CCF-ST in comparison with other methods,such as PRESTO’s“rfifind”,ArPLS-ST and ArPLS-SF.The result shows that CCF-ST can reduce effective data loss rate and improves the detected signal-to-noise ratio of the pulsations by~26%and~18%respectively compared with PRESTO’s“rfifind”and ArPLS-ST.The CCF-ST also has the advantage of low computational cost,e.g.,reducing the time consumption by~40%and memory consumption by~90%compared with ArPLS-SF.We expect that the new RFI mitigation and analysis toolkit(CCF-ST)demonstrated in this paper can be applied to CRAFTS and other multi-beam telescope observations to improve the data quality and efficiency of pulsar and FRB searches.
基金supported by the National Natural Science Foundation of China(Nos.12203039 and 11873083)the National Natural Science Foundation of China(Nos.12173053 and 12041303)+4 种基金supported by the National SKA Program of China(No.2020SKA0120100)the Youth Innovation Promotion Association of CAS(id.2018075)the CAS“Light of West China”Programthe Specialized Research Fund for State Key Laboratoriesthe Science and Technology Program of Guizhou Province([2021]4001)。
文摘We present a method by using the phase characteristics of radio observation data for pulsar search and candidate identification.The phase characteristics are relations between the pulsar signal and the phase correction in the frequency-domain,and we regard it as a new search diagnostic characteristic.Based on the phase characteristics,a search method is presented:calculating dispersion measure(DM)—frequency data to select candidate frequencies,and then confirming of candidates by using the broadband characteristics of pulsar signals.Based on this method,we performed a search test on short observation data of M15 and M71,which were observed by Five-hundredmeter Aperture Spherical radio Telescope,and some of the Galactic Plane Pulsar Snapshot survey data.Results show that it can get similar search results to PRESTO(Pulsa R Exploration and Search TOolkit)while having a faster processing speed.
