Hot flow anomalies(HFAs)are not only a terrestrial phenomenon,but also a solar-system-wide phenomenon,one that can cause significant perturbations in planetary magnetospheres and ionospheres.In this study,based on the...Hot flow anomalies(HFAs)are not only a terrestrial phenomenon,but also a solar-system-wide phenomenon,one that can cause significant perturbations in planetary magnetospheres and ionospheres.In this study,based on the observations of Mars Atmosphere and Volatile EvolutioN(MAVEN)mission in the region upstream of the Martian bow shock from the year 2014 to 2020,we have investigated the statistical properties of HFAs around Mars.Our results show that HFAs can be found in a wide region of Mars,from the dayside to the terminator region.On average,these HFAs last 63 seconds,with a thickness of 28 local proton gyroradii.They are more prevalent when the ambient solar wind is denser and faster,and usually occur when the interplanetary magnetic field magnitude is between 1-4 nT.Martian HFAs can also lead to solar wind dynamics multiplying in pressure by factors of ten within only tens of seconds,which could significantly influence the heights of the Martian ionopause and induced magnetosphere boundary.By comparing HFAs around Earth,we suggest that these phenomena are primarily governed by solar wind dynamics rather than local planetary conditions.展开更多
A new ground-based expenmental device,the Space Plasma Environment Research Facility（SPERF）,is being designed at Harbin Institute of Technology in China,with Asymmetric REconnection eXperiment-3 Dimensional（AREX-3D...A new ground-based expenmental device,the Space Plasma Environment Research Facility（SPERF）,is being designed at Harbin Institute of Technology in China,with Asymmetric REconnection eXperiment-3 Dimensional（AREX-3D） as one of the experimental components to study the asymmetric reconnection dynamics relevant to the interaction between the interplanetary and magnetospheric plasmas.The asymmetry in the designed magnetic reconnection process not only refers to the distinct plasma parameters designed for the two upstream regions across the current sheet,but also refers to the inhomogeneity in the direction along the current sheet resulting from the designed 3D magnetic field geometry.These two asymmetries are fundamental features of the reconnection process at the Earth＇s magnetopause.In experiment,the reconnection process is driven by a set of flux cores through coil-currentramp-up from the ＇magnetosheath-side＇ to interact with a dipole magnetic field generated by the Dipole Research Experiment（DREX） coil on the ＇magnetosphere-side＇.The AREX-3D will be able to investigate a range of important reconnection issues in 3D magnetic field geometry that is relevant to the Earth＇s magnetopause.A wide range of plasma parameters can be achieved through inductive plasma generation with flux cores on the ＇magnetosheath-side＇ and electron cyclotron resonance（ECR） with microwave sources on the ＇magnetosphere-side＇,e.g.high（low）plasma density at experimental magnetosheath（dipole） side.Different reconnection regimes and geometries can be produced by adjusting plasma parameters and coil setups as well as coil current waveforms.The three-dimensional magnetic field configurations in the SPERF relevant to the dayside magnetopause reconnection are discussed in detail.展开更多
Predicting the activity of solar flares is of great significance for studying its physical mechanism and the impact on human production and life.Problems such as class imbalance,high time-series sensitivity,and over-l...Predicting the activity of solar flares is of great significance for studying its physical mechanism and the impact on human production and life.Problems such as class imbalance,high time-series sensitivity,and over-localization of important features exist in the sample data used for flare forecasting.We design a solar flare fusion method based on resampling and the CNN-GRU algorithm to try to solve the above problems.In order to verify the effectiveness of this fusion method,first,we compared the forecast performance of different resampling methods by keeping the forecast model unchanged.Then,we used the resampling algorithm with high performance to combine some single forecast models and fusion forecast models respectively.We use the 2010-2017 sunspot data set to train and test the performance of the flare model in predicting flare events in the next 48 h.Through the conclusion of the above steps,we prove that the resampling method SMOTE and its variant SMOTE-ENN are more advantageous in class imbalance problem of flare samples.In addition,after the fusion of one-dimensional convolution and recurrent network with"forget-gate",combined with the SMOTE-ENN to achieve TSS=61%,HSS=61%,TP_(Rate)=77%and TN_(Rate)=83%.This proves that the fusion model based on resampling and the CNN-GRU algorithm is more suitable for solar flare forecasting.展开更多
The research of flare forecast based on the machine learning algorithm is an important content of space science.In order to improve the reliability of the data-driven model and weaken the impact of imbalanced data set...The research of flare forecast based on the machine learning algorithm is an important content of space science.In order to improve the reliability of the data-driven model and weaken the impact of imbalanced data set on its forecast performance,we proposes a resampling method suitable for flare forecasting and a Particle Swarm Optimization(PSO)-based Support Vector Machine(SVM)regular term optimization method.Considering the problem of intra-class imbalance and inter-class imbalance in flare samples,we adopt the density clustering method combined with the Synthetic Minority Over-sampling Technique(SMOTE)oversampling method,and performs the interpolation operation based on Euclidean distance on the basis of analyzing the clustering space in the minority class.At the same time,for the problem that the objective function used for strong classification in SVM cannot adapt to the sample noise,In this research,on the basis of adding regularization parameters,the PSO algorithm is used to optimize the hyperparameters,which can maximize the performance of the classifier.Finally,through a comprehensive comparison test,it is proved that the method designed can be well applied to the flare forecast problem,and the effectiveness of the method is proved.展开更多
Eruption of solar flares is a complex nonlinear process,and the rays and high-energy particles generated by such an eruption are detrimental to the reliability of space-based or ground-based systems.So far,there are n...Eruption of solar flares is a complex nonlinear process,and the rays and high-energy particles generated by such an eruption are detrimental to the reliability of space-based or ground-based systems.So far,there are not reliable physical models to accurately account for the flare outburst mechanism,but a lot of data-driven models have been built to study a solar flare and forecast it.In the paper,the status of solar-flare forecasting is reviewed,with emphasis on the machine learning methods and data-processing techniques used in the models.At first,the essential forecast factors strongly relevant to solar flare outbursts,such as classification information of the sunspots and evolution pattern of the magnetic field,are reviewed and analyzed.Subsequently,methods of resampling for data preprocessing are introduced to solve the problems of class imbalance in the solar flare samples.Afterwards,typical model structures adopted for flare forecasting are reviewed from the aspects of the single and fusion models,and the forecast performances of the different models are analyzed.Finally,we herein summarize the current research on solar flare forecasting and outline its development trends.展开更多
A pulsed transverse magnetic field with pulse width of 12 ms and magnitude of 2 T was used to modify the density distribution of a weakly-ionized plasma flow with strong collisions between the charged particles and ne...A pulsed transverse magnetic field with pulse width of 12 ms and magnitude of 2 T was used to modify the density distribution of a weakly-ionized plasma flow with strong collisions between the charged particles and neutrals.The morphology of the plasma is changed substantially,with the density increased upstream and decreased downstream.Meanwhile,the plasma toward the axis contracts laterally and gradually converges to a collimated flow.In addition,a drift wave is observed to be excited in the inhomogeneous plasma by the magnetic field.展开更多
基金supported by NSFC grants 42274219,42330207,42374213 and 42130204Shenzhen Key Laboratory Launching Project(No.ZDSYS20210702140800001)+1 种基金supported by Frontier Science Center of matter behave in space environmentthe support of the National Key Research and Development Program of China(No.2022YFA1604600).
文摘Hot flow anomalies(HFAs)are not only a terrestrial phenomenon,but also a solar-system-wide phenomenon,one that can cause significant perturbations in planetary magnetospheres and ionospheres.In this study,based on the observations of Mars Atmosphere and Volatile EvolutioN(MAVEN)mission in the region upstream of the Martian bow shock from the year 2014 to 2020,we have investigated the statistical properties of HFAs around Mars.Our results show that HFAs can be found in a wide region of Mars,from the dayside to the terminator region.On average,these HFAs last 63 seconds,with a thickness of 28 local proton gyroradii.They are more prevalent when the ambient solar wind is denser and faster,and usually occur when the interplanetary magnetic field magnitude is between 1-4 nT.Martian HFAs can also lead to solar wind dynamics multiplying in pressure by factors of ten within only tens of seconds,which could significantly influence the heights of the Martian ionopause and induced magnetosphere boundary.By comparing HFAs around Earth,we suggest that these phenomena are primarily governed by solar wind dynamics rather than local planetary conditions.
基金supported by the NSFC under Grant Nos.11261140326,11275034,51577043,11505040, 61402138HIT.NSRIF under Grant No.2017009the Natural Science Foundation of Heilongjiang Province(No. E201452)
文摘A new ground-based expenmental device,the Space Plasma Environment Research Facility（SPERF）,is being designed at Harbin Institute of Technology in China,with Asymmetric REconnection eXperiment-3 Dimensional（AREX-3D） as one of the experimental components to study the asymmetric reconnection dynamics relevant to the interaction between the interplanetary and magnetospheric plasmas.The asymmetry in the designed magnetic reconnection process not only refers to the distinct plasma parameters designed for the two upstream regions across the current sheet,but also refers to the inhomogeneity in the direction along the current sheet resulting from the designed 3D magnetic field geometry.These two asymmetries are fundamental features of the reconnection process at the Earth＇s magnetopause.In experiment,the reconnection process is driven by a set of flux cores through coil-currentramp-up from the ＇magnetosheath-side＇ to interact with a dipole magnetic field generated by the Dipole Research Experiment（DREX） coil on the ＇magnetosphere-side＇.The AREX-3D will be able to investigate a range of important reconnection issues in 3D magnetic field geometry that is relevant to the Earth＇s magnetopause.A wide range of plasma parameters can be achieved through inductive plasma generation with flux cores on the ＇magnetosheath-side＇ and electron cyclotron resonance（ECR） with microwave sources on the ＇magnetosphere-side＇,e.g.high（low）plasma density at experimental magnetosheath（dipole） side.Different reconnection regimes and geometries can be produced by adjusting plasma parameters and coil setups as well as coil current waveforms.The three-dimensional magnetic field configurations in the SPERF relevant to the dayside magnetopause reconnection are discussed in detail.
基金the National Natural Science Foundation of China(Grant No.11975086)project“3D Magnetic Reconnection Reconnection Area Structure Experimental and Numerical Simulation Research”。
文摘Predicting the activity of solar flares is of great significance for studying its physical mechanism and the impact on human production and life.Problems such as class imbalance,high time-series sensitivity,and over-localization of important features exist in the sample data used for flare forecasting.We design a solar flare fusion method based on resampling and the CNN-GRU algorithm to try to solve the above problems.In order to verify the effectiveness of this fusion method,first,we compared the forecast performance of different resampling methods by keeping the forecast model unchanged.Then,we used the resampling algorithm with high performance to combine some single forecast models and fusion forecast models respectively.We use the 2010-2017 sunspot data set to train and test the performance of the flare model in predicting flare events in the next 48 h.Through the conclusion of the above steps,we prove that the resampling method SMOTE and its variant SMOTE-ENN are more advantageous in class imbalance problem of flare samples.In addition,after the fusion of one-dimensional convolution and recurrent network with"forget-gate",combined with the SMOTE-ENN to achieve TSS=61%,HSS=61%,TP_(Rate)=77%and TN_(Rate)=83%.This proves that the fusion model based on resampling and the CNN-GRU algorithm is more suitable for solar flare forecasting.
基金the support of the National Key Research and Development Program of China(No.2022YFF0503601)the National Natural Science Foundation of China(No.11975086)。
文摘The research of flare forecast based on the machine learning algorithm is an important content of space science.In order to improve the reliability of the data-driven model and weaken the impact of imbalanced data set on its forecast performance,we proposes a resampling method suitable for flare forecasting and a Particle Swarm Optimization(PSO)-based Support Vector Machine(SVM)regular term optimization method.Considering the problem of intra-class imbalance and inter-class imbalance in flare samples,we adopt the density clustering method combined with the Synthetic Minority Over-sampling Technique(SMOTE)oversampling method,and performs the interpolation operation based on Euclidean distance on the basis of analyzing the clustering space in the minority class.At the same time,for the problem that the objective function used for strong classification in SVM cannot adapt to the sample noise,In this research,on the basis of adding regularization parameters,the PSO algorithm is used to optimize the hyperparameters,which can maximize the performance of the classifier.Finally,through a comprehensive comparison test,it is proved that the method designed can be well applied to the flare forecast problem,and the effectiveness of the method is proved.
基金the support of the National Key Research and Development Program of China(No.2022YFA1604600)the National Natural Science Foundation of China(NSFC,Grant No.11975086)。
文摘Eruption of solar flares is a complex nonlinear process,and the rays and high-energy particles generated by such an eruption are detrimental to the reliability of space-based or ground-based systems.So far,there are not reliable physical models to accurately account for the flare outburst mechanism,but a lot of data-driven models have been built to study a solar flare and forecast it.In the paper,the status of solar-flare forecasting is reviewed,with emphasis on the machine learning methods and data-processing techniques used in the models.At first,the essential forecast factors strongly relevant to solar flare outbursts,such as classification information of the sunspots and evolution pattern of the magnetic field,are reviewed and analyzed.Subsequently,methods of resampling for data preprocessing are introduced to solve the problems of class imbalance in the solar flare samples.Afterwards,typical model structures adopted for flare forecasting are reviewed from the aspects of the single and fusion models,and the forecast performances of the different models are analyzed.Finally,we herein summarize the current research on solar flare forecasting and outline its development trends.
基金supported by National Natural Science Foundation of China (Nos. 11975086, 51577043)
文摘A pulsed transverse magnetic field with pulse width of 12 ms and magnitude of 2 T was used to modify the density distribution of a weakly-ionized plasma flow with strong collisions between the charged particles and neutrals.The morphology of the plasma is changed substantially,with the density increased upstream and decreased downstream.Meanwhile,the plasma toward the axis contracts laterally and gradually converges to a collimated flow.In addition,a drift wave is observed to be excited in the inhomogeneous plasma by the magnetic field.
