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Solar radio images in decimeter wave range consist of many complicated components including a disk component, some bright and weak compact sources, and many diffuse features. Complicated structures combining these various components maybe cause restoration failure when using conventional algorithms. Furthermore, the images at different frequencies band are pretty different. Therefore, restoration method for solar radio image is different from other radio sources. Some image restoration methods were applied and obtained good results on Nancay radioheliograph images and Nobeyama radioheliograph images, and some new methods were introduced into processing these complicated solar radio images in recent years. For a new radioheliograph with ultrawide frequency band, new image restoration method which can maximize function of telescope is demanded. Different images could be obtained from the same visibilities data by using different weighting functions in imaging processing. In this paper, a new restoration method for solar radio image was proposed. Two images with different weighting functions from the same data are combined in this method. This restoration method has applied to data processing of Mingantu spectral radioheliograph.

Overexposure may happen for imaging of solar observation as extremely violet solar bursts occur, which means that signal intensity goes beyond the dynamic range of imaging system of a telescope, resulting in loss of signal. For example, during solar flare, Atmospheric Imaging Assembly (AIA) of Solar Dynamics Observatory (SDO) often records overexposed images/videos, resulting loss of fine structures of solar flare. This paper makes effort to retrieve/recover missing information of overexposure by exploiting deep learning for its powerful nonlinear representation which makes it widely used in image reconstruction/restoration. First, a new model, namely, mask-Pix2Pix network, is proposed for overexposure recovery. It is built on a well-known Pix2Pix network of conditional generative adversarial network (cGAN). In addition, a hybrid loss function, including an adversarial loss, a masked L1 loss and a edge mass loss/smoothness, are integrated together for addressing challenges of overexposure relative to conventional image restoration. Moreover, a new database of overexposure is established for training the proposed model. Extensive experimental results demonstrate that the proposed mask-Pix2Pix network can well recover missing information of overexposure and outperforms the state of the arts originally designed for image reconstruction tasks.

Multiwavelength bright points (BPs) are taken to be cross sections of magnetic flux tubes extending from the surface of the photosphere upward to the higher photosphere. We aim to study the characteristics of isolated multiwavelength BPs using the cotemporal and cospatial TiO band and Hα line wings from the Goode Solar Telescope at Big Bear Solar Observatory. A deep-learning method, based on Track Region-based Convolutional Neural Networks, is proposed to detect, segment, and match the BPs across multiple wavelength observations, including the TiO, Hα + 1 Å, Hα − 1 Å, Hα + 0.8 Å, and Hα − 0.8 Å line wings. Based on the efficient detection and matching result with a precision of 0.98, 1283 groups of BPs matched in all five wavelengths are selected for statistics analysis. The characteristic values of the BPs observed at the same red and blue line wings are averaged. For the BPs of the TiO, averaged Hα ± 1 Å, and averaged Hα ± 0.8 Å line wings, the mean equivalent diameters are 162 ± 32, 254 ± 33, and 284 ± 28 km, respectively. The maximum intensity contrasts are 1.11 ± 0.09, 1.05 ± 0.03, and 1.05 ± 0.02 , respectively. The mean eccentricities are 0.65 ± 0.14, 0.63 ± 0.11, and 0.65 ± 0.11, respectively. Moreover, the characteristic ratios of each Hα ± 1 Å and Hα ± 0.8 Å BP to its corresponding TiO BP are derived. Hα ± 1 Å and Hα ± 0.8 Å line wings BPs show 60% and 80% increases compared to TiO BPs, respectively. With increasing height, most BPs almost keep their shapes. This work is helpful for modeling the three-dimensional structure of flux tubes.

We present an analysis of the formation and eruption of a filament and fast coronal mass ejection associated with a flare that occurred in active region 11429 using observations in the ultraviolet, extreme ultraviolet, X-ray, and radio wavelength bands. Precursor activity began as an interaction between two filaments, F1 and F2, that are identified as having twisted magnetic flux ropes (MFRs). Transient brightenings in all wavelengths are observed as a result of this interaction, likely the result of magnetic reconnection between the two filaments. This interaction results in a reconfiguration of the two filaments into a long overlying filament and a shorter low-lying filament. The upper filament subsequently undergoes a partial confined eruption. Plasma flows originating near the east footpoint of F1 lead to an extension of the upper filament into the filament channel to the west, resulting in a new active region filament (ARF). This new filament begins a slow rise and expansion. During its slowly rising phase, the MFR in which the filament is embedded becomes visible, with both the filament and flux rope rising and expanding simultaneously. The twist of the magnetic rope is determined as four turns. The erupting configuration changes from a twisted arch shape to a reversed γ shape within ∼75 s at the beginning of the fast-rise phase, representing a transformation from twist to writhe. The observations provide a clear example of filament formation via the tether-cutting reconnection of two nearby filaments. A helical kink instability may be the trigger of the ARF eruption.

Recent developments in astronomical radio telescopes opened new opportunities in imaging and spectroscopy of solar radio bursts at sub-second timescales. Imaging in narrow frequency bands has revealed temporal variations in the positions and source sizes that do not fit into the standard picture of type III solar radio bursts, and require a better understanding of radio-wave transport. In this paper, we utilise 3D Monte Carlo ray-tracing simulations that account for the anisotropic density turbulence in the inhomogeneous solar corona to quantitatively explain the image dynamics at the fundamental (near plasma frequency) and harmonic (double) plasma emissions observed at \sim 32~MHz. Comparing the simulations with observations, we find that anisotropic scattering from an instantaneous emission point source can account for the observed time profiles, centroid locations, and source sizes of the fundamental component of type III radio bursts (generated where f_{pe} \approx 32~MHz). The best agreement with observations is achieved when the ratio of the perpendicular to the parallel component of the wave vector of anisotropic density turbulence is around 0.25. Harmonic emission sources observed at the same frequency (\sim 32~MHz, but generated where f_{pe} \approx 16~MHz) have apparent sizes comparable to those produced by the fundamental emission, but demonstrate a much slower temporal evolution. The simulations of radio-wave propagation make it possible to quantitatively explain the variations of apparent source sizes and positions at sub-second time-scales both for the fundamental and harmonic emissions, and can be used as a diagnostic tool for the plasma turbulence in the upper corona., 17 pages, 6 figures, accepted

In this paper, we propose a novel no-reference image quality assessment method for the retargeted image based on the pairwise rank learning approach. Each retargeted image needs to be first represented as a feature vector, which not only captures the image characteristics but also is sensitive to distortions during the retargeting process. As such, we investigate and examine different image representations for their abilities depicting the perceptual quality of retargeted image. Based on the image representations, we resort to the pairwise rank learning approach to discriminate the perceptual quality between the retargeted image pairs. Experimental results demonstrate that the proposed method can effectively depict the perceptual quality of the retargeted image, which can even perform comparably with the full-reference quality assessment methods.

This work reports a peculiar and interesting train of microwave type III pair bursts in the impulsive rising phase of a solar flare on 2011 September 26. The observations include radio spectrometers at frequency of 0.80 - 2.00 GHz, hard X-ray (RHESSI and FERMI), EUV images of SWAP/PROBA-2 and magnetogram of HMI/SDO. By using a recently developed method (Tan et al. 2016a), we diagnosed the plasma density, temperature, plasma beta, magnetic field near the source region, the energy of energetic electrons and the distance between the acceleration region and the emission start sites of type III bursts. From the diagnostics, we find that: (1) The plasma density, temperature, magnetic field, and the distance between the acceleration region and the emission start sites almost have no obvious variations during the period of type III pair trains, while the energy of electrons has an obvious peak value which is consistent to the hard X-ray emission. (2) The plasma beta is much higher than an unity showing a highly dynamic process near the emission start site of type III bursts. (3) Although the reversed-slope type III branches drift slower at one order of magnitude than that of the normal type III branches, the related downgoing and upgoing electrons still could have same order of magnitude of energy. These facts indicate that both of the upgoing and downgoing electrons are possibly accelerated by similar mechanism and in a small source region. This diagnostics can help us to understand the microphysics in the source region of solar bursts., 14 pages, 5 figures, accepted by Solar Physics

To know what kinds of image features are crucial for image quality assessment (IQA) and how these features affect the human visual system (HVS) is still largely beyond human knowledge. Hence, machine learning (ML) is employed to build IQA by simulating the HVS behavior in IQA processes. Support vector machine/regression (SVM/SVR) is a major member of ML. It has been successfully applied to IQA recently. As to image quality rating, the human’s opinion about it is not always reliable. In fact, the subjects cannot precisely rate the small difference of image quality in subjective testing, resulting in unreliable Mean Opinion Scores (MOSs). However, they can easily identify the better/worse one from two given images, even their qualities do not differ much. In this sense, the human’s opinion on pairwise comparison (PC) of image quality is more reliable than image quality rating. Thus, PC has been exploited in developing IQA metrics. In this paper, a rank learning optimization framework is firstly developed to model IQA. Particularly, the PCs of image quality instead of numerical ratings are incorporated into the optimization framework. Then, a novel no-reference (NR)-IQA is proposed to infer image quality in terms of image quality ranks. By importing rank learning theory and PC into IQA, a fundamental and meaningful departure from the existing framework of IQA could be expected. The experimental results confirm that the proposed Pairwise Rank Learning based Image Quality Metric (PRLIQM) can achieve comparable performance over the state-of-the-art NR-IQA approaches.

In this paper, we extend the free-energy principle to video quality assessment (VQA) by incorporating with the recent psychophysical study on human visual speed perception (HVSP). A novel video quality metric, namely the free-energy principle inspired video quality metric (FePVQ), is therefore developed and applied to perceptual video coding optimization. The free-energy principle suggests that the human visual system (HVS) can actively predict “orderly” information and avoid “disorderly” information for image perception. Basically, “orderly” is associated with the skeletons and edges of objects, and “disorderly” mostly concerns textures in images. Based on this principle, an image is separated into orderly and disorderly regions, and processed differently in image quality assessment. For videos, visual attention, or fixation, is associated with the objects with significant motion according to HVSP, resulting in a motion strength factor in the FePVQ so that the free-energy principle is extended into spatio-temporal domain for VQA. In addition, we investigate the application of the FePVQ in perceptual rate distortion optimization (RDO). For this purpose, the FePVQ is realized with low computational cost by using the relative total variation model and the block-wise motion vectors of video coding to simulate the free-energy principle and the HVSP, respectively. The experimental results indicate that the proposed FePVQ is highly consistent with the HVS perception. The linear correlation coefficient and Spearman's rank-order correlation coefficient are up to 0.8324 and 0.8281 on the LIVE video database. Better perceptual quality of encoded video sequences is achieved by FePVQ-motivated RDO in video coding.

In order to realize the requirement of low-noise observations of dark objects in deep-space explorations, the design method for a simple and stable space camera imaging system is proposed in this paper. Based on the back-illuminated frame-transferred surface array CCD (CCD47-20AIMO) produced by the British E2V company, the circuitry design is given for the every part of the system. In which the applications of the correlated double-sampling analog-digital converter (AD) and the synchronous dynamic random access memory (SDRAM) can effectively suppress the correlated noise in the image signal. In addition, a drive control method favorable to the adjustment of exposure time is proposed, in the light-sensing stage it provides the exposure time with an independent and adjustable time delay to make the imaging system satisfy the requirement of long exposure time setting. The imaging system adopts the Cyclone III-series EP3C25Q240C8 field programable gate array produced by the Altera company as the kernel control device, and the drives are programmed in modules according to the function of the every device, in favor of transplantation. The simulative and experimental results indicate that the drive circuitry works normally, and that the system design can satisfy the preset requirement.

With Aperture synthesis (AS) technique, a number of small antennas can assemble to form a large telescope which spatial resolution is determined by the distance of two farthest antennas instead of the diameter of a single-dish antenna. Different from direct imaging system, an AS telescope captures the Fourier coefficients of a spatial object, and then implement inverse Fourier transform to reconstruct the spatial image. Due to the limited number of antennas, the Fourier coefficients are extremely sparse in practice, resulting in a very blurry image. To remove/reduce blur, "CLEAN" deconvolution was widely used in the literature. However, it was initially designed for point source. For extended source, like the sun, its efficiency is unsatisfied. In this study, a deep neural network, referring to Generative Adversarial Network (GAN), is proposed for solar image deconvolution. The experimental results demonstrate that the proposed model is markedly better than traditional CLEAN on solar images., 14 pages, 6 figures, 2 tables

The structural property of the magnetic field in flare-bearing solar active regions (ARs) is one of the key aspects for understanding and forecasting solar flares. In this paper, we make a comparative analysis on the chirality and magnetic configurations associated with two X-class two-ribbon flares happening in AR 10930 and AR 11158. The photospheric magnetic fields of the two ARs were observed by space-based instruments, and the corresponding coronal magnetic fields were calculated based on the nonlinear force-free field model. The analysis shows that the electric current in the two ARs was distributed mostly around the main polarity inversion lines (PILs) where the flares happened, and the magnetic chirality (indicated by the signs of force-free factor $\alpha$) along the main PILs is opposite for the two ARs, i.e., left-handed ($\alpha0$) for AR 11158. It is found that, for both the flare events, a prominent magnetic connectivity (featured by co-localized strong $\alpha$ and strong current density distributions) was formed along the main PIL before flare and was totally broken after flare eruption. The two branches of the broken magnetic connectivity, combined with the prominent magnetic connectivity before flare, compose the opposite magnetic configurations in the two ARs owing to their opposite chirality, i.e., Z-shaped configuration in AR 10930 with left-handed chirality and inverse Z-shaped configuration in AR 11158 with right-handed chirality. It is speculated that two-ribbon flares can be generally classified to these two magnetic configurations by chirality in the flare source regions of ARs., Comment: 24 pages, 9 figures, 2 tables, AdSpR(2020)65:2828, doi:10.1016/j.asr.2020.03.034

We apply a novel pre-flare tracking of sunspot groups towards improving the estimation of flare onset time by focusing on the evolution of the 3D magnetic field construction of AR 11429. The 3D magnetic structure is based on potential field extrapolation encompassing a vertical range from the photosphere through the chromosphere and transition region into the low corona. The basis of our proxy measure of activity prediction is the so-called weighted horizontal gradient of magnetic field (WGM) defined between spots of opposite polarities close to the polarity inversion line of an active region. The temporal variation of the distance of the barycenter of the opposite polarities is also found to possess potentially important diagnostic information about the flare onset time estimation as function of height similar to its counterpart introduced initially in an application at the photosphere only in Korsós et al. (2015). We apply the photospheric pre-flare behavioural patterns of sunspot groups to the evolution of their associated 3D-constructed AR 11429 as function of height. We found that at a certain height in the lower solar atmosphere the onset time may be estimated much earlier than at the photosphere or at any other heights. Therefore, we present a tool and recipe that may potentially identify the optimum height for flare prognostic in the solar atmosphere allowing to improve our flare prediction capability and capacity. ispartof: pages:294-297 ispartof: IAU Symposium 335 vol:13 issue:S335 pages:294-297 ispartof: IAUS 335: Space Weather of the Heliosphere: Processes and Forecasts location:University of Exeter, UK date:17 Jul - 21 Jul 2017 status: published

This paper proposes a reliability analysis method for modular system for MingantU SpEctral Radioheliograph (MUSER) based on Goal Oriented (GO) method. First, the proposed method is expounded in detail from aspects of presenting the frequently-used GO operators for describing the modular system and formulating this paper's reliability analysis process. Then, the LOFAR Analog Receiver and Transmission System (LOFAR ARTS), which is a typical modular system in MUSER, is taken as an example to illustrate the usage and advantages of the proposed method by obtaining its quantitative analysis result and qualitative analysis result. All in all, this study not only widens the application of GO method; but also provides a new reliability analysis approach for complex modular system.

MPID5177279. MUSER-I consists of 40 4.5m dish antennas, observing from 0.4 GHz to 2 GHz. While MUSER-H consists of 60 2.5m dish antennas and works at higher frequencies from 2 GHz to 15 GHz. All 100 antennas of MUSER-I and MUSER-H are arranged along three spiral arms. The max antenna-pair baseline is ∼3km.

Log periodic antenna is a well-known frequency independent antenna, it radiates structures capable of maintaining consistent impedance characteristics over wide bandwidth. This log periodic antenna is used in many broadband applications due to the ability of achieving constant gain. Hence, a folded log periodic antenna array was simulated in 30-400 MHz frequency band for Meridian project. In order to improve its return loss, this antenna is optimized with the width of each pole and the height of the substrate. This optimized process has been implemented in simulated software HFSS. The original results are shown in this paper.

Solar radio type III bursts are believed to be the most sensitive signature of near-relativistic electron beam propagation in the corona. A solar radio type IIIb-III pair burst with fine frequency structures, observed by the Low Frequency Array (LOFAR) with high temporal ($\sim10$ ms) and spectral (12.5 kHz) resolutions at 30 - 80 MHz, is presented. The observations show that the type III burst consists of many striae, which have a frequency scale of about 0.1 MHz in both the fundamental (plasma) and the harmonic (double plasma) emission. We investigate the effects of background density fluctuations based on the observation of striae structure to estimate the density perturbation in solar corona. It is found that the spectral index of the density fluctuation spectrum is about $-1.7$, and the characteristic spatial scale of the density perturbation is around $700$ km. This spectral index is very close to a Kolmogorov turbulence spectral index of $-5/3$, consistent with a turbulent cascade. This fact indicates that the coronal turbulence may play the important role of modulating the time structures of solar radio type III bursts, and the fine structure of radio type III bursts could provide a useful and unique tool to diagnose the turbulence in the solar corona., Comment: 7 pages (text), 5 figures, Submitted to ApJ

The ionosphere is a region over earth's atmosphere which is ionized by solar radiation. It plays an important part in atmospheric electricity and forms the inner edge of the magnetosphere, furthermore, it has practical importance for its effects on radio propagation to earth. Accordingly, its cyclic changes and disturbances could influence communication, navigation, radar seriously. Total Electron Content (TEC) is an important parameter reflecting ionospheric significant characteristic. We can analyse ionospheric disturbance and cyclic change by investigating TEC. Now, the time sequence of TEC and relevant parameters is available for our research. In addition, Bidirectional long short-term memory (Bi-LSTM) is believed to have potential in time sequence processing. Hence, we investigate TEC forecast by referring to Bi-LSTM in this work. Experimental results demonstrate that Bi-LSTM can capture the cyclic change feature of TEC, and perform better than LSTM and multi-LSTM for TEC forecast.

Mingantu Ultrawide Spectral Radioheliograph (MUSER) is an aperture synthesis telescope consisting of a group of small antennas to image the Sun. Each two antennas form a baseline contributing a Fourier sampling point for each time of imaging. Both amplitude and phase of a baseline form a time sequence in a time interval. Normally, amplitude/phase should vary linearly in a short time interval. However, many reasons would result in errors of baselines, damaging image quality. This work makes the first attempt to auto-flag baselines so as to delete bad baselines and improve image quality. Inspired by the big success of long short-term memory (LSTM) for time series analysis, we believe that LSTM could accomplish auto-flagging (a binary classification task) of baselines even better by treating them as time sequences. Thus, LSTM is employed to learn the representation of the phase of each baseline for classification, where the interaction and connection within a phase sequence are explored, benefiting classification. The experimental results demonstrate that LSTM can well capture the characteristics of the phase of a baseline, and thus achieves better classification.

MingantU SpEctral Radioheliograph (MUSER) is a radio synthesis imaging array dedicated to observe the sun, operating on multiple frequencies from decimeter to centimeter range. In the experimental observations MUSER produces about 2.55 Tera Bytes data daily, which will be processed offline to get the solar radio images. In this paper the current data processing and imaging procedure for MUSER will be discussed in details. Some algorithms are presented to solve the problems in the imaging with MUSER.

The Chinese Spectral Radioheliograph (CSRH) with two arrays in 400MHz-2GHz/2-15GHz ranges with 64/520 frequency channels have been established in Mingantu Observing Station, Inner Mongolia of China, since 2013 and is in test observations now. CSRH is renamed as Mingantu Ultrawide SpEctral Radioheliograph (MUSER) after its accomplishment. We introduce the progress and current status of MUSER. The first burst imaging results of MUSER is presented.

In this paper, the authors make the first attempt to employ the deep learning method for the representation learning of the solar radio spectrums. The original solar radio spectrums are pre-processed, including normalization, enhancement and etc., to generate new images for the next processing. With the expertise of solar radio astronomy for identifying solar radio activity, we build a solar radio activity database, which contains solar radio spectrums as well as their labels indicating the types of solar radio bursts. The employed deep learning network is firstly pre-trained based on the available massive of unlabeled radio solar images. Afterwards, the weights of the network are further fined-tuned based on the labeled data. Experimental results have demonstrated that the employed network can effectively classify the solar radio image into the labeled categories. Moreover, the pre-training process can help improve the classification accuracy.

MingantU SpEctral Radioheliograph (MUSER) is a new aperture synthesis radio heliograph, which aims to image the Sun in snapshot mode at multiple frequencies (0.40–15.00GHz) with high time resolution, high spatial resolution and high frequency resolution. In general, the observed data in the UV plane is incomplete, so the deconvolution algorithm is needed. The traditional CLEAN is ineffective in solar radiation observation with large scale, hierarchical complex structure and diffuse features. Furthermore, excessive computational time happens in case the signal-to-noise ratio is very low. This paper makes the first attempt to employ the wavelet CLEAN in Matlab to alleviate the difficulties occurring in the traditional CLEAN. The parameters of wavelet CLEAN are optimized and the results between traditional CLEAN and wavelet CLEAN are compared and discussed. It is proved that the wavelet CLEAN is superior to the traditional CLEAN algorithm in less number of iterations and the improved image quality.

As a dedicated solar radio interferometer, the MingantU SpEctral RadioHeliograph (MUSER) generates massive observational data in the frequency range from 400 MHz to 15 GHz. The image quality depends strongly on the phase calibration and imaging algorithms. And, clean, which are really extraordinarily time consumption deconvolution operations, is an essential step to get high-quality images. In this paper, we proposed an approach to estimate the probably brightness of the solar disk and sky, which can give the parameters for phase calibration. Meanwhile, the number of iterations for clean algorithms can be determined by the estimated sky brightness, which can effectively improve the efficiency of clean performance. The preliminary experimental result of the MUSER imaging proves the availability of this approach.

We propose a flexible multi-frequency channel correlator upgrade for MUSER-I array. The upgrade correlator has a more flexible architecture to be extensible for signal receiving elements. It can process 1024 frequency channels in IF band and the correlation sensibility is improved by utilizing 4-bit quantization in pre-correlation as well. The enhanced multi-frequency channel processing capability also helps to implement RFI excision in the upgrade correlator.

MUSER (MingantU SpEctral Radioheliograph) is a solar-dedicated interferometric array that is located in Mingantu town, Inner Mongolia of China and carries out imaging spectroscopy of the Sun with high spatial resolution, high time resolution and high frequency resolution at a wide frequency range from 0.4–2GHz. It was renamed from CSRH (Chinese Spectral Radioheliograph) after its accomplishment. Some observations and current status of MUSER are introduced in this paper.

Interplanetary Scintillation (IPS) of compact radio sources at meter to centimeter wavelengths is a useful ground-based method to investigate solar wind. There are 3 technical solutions for IPS observation. At present, each running IPS dedicated telescope represents a solution accordingly. In recent future, a new IPS telescope is proposed to build in China. Therefore, we combined advantages of single station and multi-station, and proposed a new IPS telescope concept. Furthermore, some specification were described as well in this paper.

The Mingantu Observing Staion of National Astronomcial Observatories, Chinese Academy of Sciences was officially established in 2008 in Zhengxiang Baiqi, Inner Mongolia of China, about 260 km distance northwest of Beijing. It was reformed by combining Solar Radio Research Group together in 2016. The Mingantu Spectral Radioheliograph (MUSER) is constructed and located there. The MUSER is divided into MUSER-I covering 0.4–2GHz band and MUSER-II covering 2–15GHz band. The MUSER-I contains 40 antennas of 4.5m diameter, and the MUSER-II contains 60 antennas of 2m diameter. The whole systems with 100 antennas of both MUSER arrays were constructed over 3 log-spiral arms, and the maximum baseline length is 3km. Additionally two 20 m antennas for interferometry experimental in 400–1000 MHz were established in 2011 in the station, which may be incorporated into MUSER-I calibrations. The permanent buidings for Mingantu Observing Station has been under construction since 2015. The MUSER system officially passed National Assisement evaluation in 2016. MUSER Initial observations are promising. MUSER will be extended to metric & decametric band and an IPS telescope will be built at Mingantu Station, both under Meridian-II project during the 13th National 5-year plan (2016–2020).

In recent years, the high resolution, high precision and high sensitivity telescopes have been widely developed for astronomical observation in the world, such as SKA, Arecibo, ALMA and MingantU SpEctral Radioheliograpy (Muser). Along with these newly developed modern telescopes, a “big data” challenge was raised for data storage and processing. For example, Muser produces about 4.3TB raw data for daily solar radio observation, which presents a great challenge for archiving, analysing, transmitting and storage of data. In this paper, for the first time, we investigate data compression of Muser. We seek a lossless compressor, meanwhile, with good compression efficiency and affordable computational complexity.

Ionosphere is an important space environment near the earth. Its disturbance would result in severe propagation effects to radio information system, thus causing bad influences on communication, navigation, radar and so on. The total electron content (TEC) is an important parameter to present the disturbance of ionosphere, so TEC forecast is very meaningful in scientific research field. In this paper, we propose a long short-term memory (LSTM) based model to predict ionospheric vertical TEC of Beijing. The input of our model is a time sequence consisting of the vector of daily TECs and other closely related parameters. The output is TECs of future 24 hours. The result shows the root of mean square (RMS) error of test data can reach 3.50 and RMS error is less than this number during the period of low solar activity. Compared to multilayer perceptron network, LSTM is more promising and reliable to forecast ionospheric TEC.

This paper makes the first attempt to utilize long short-term memory (LSTM) for classification of solar radio spectrum. A solar radio spectrum is a gray-scale image representing solar radio radiation over multiple frequency channels and in a short time period. The vertical and horizontal dimensions of a spectrum correspond to frequency channel and time, respectively. Intrinsically, time dependence exists between columns of a spectrum, which indicates the slowly varying process of solar radio radiation. Thus, a spectrum can be treated as a time sequence instead of a general image losing its time information. Inspired by the big success of LSTM for time sequence processing, e.g., natural language recognition, it is reasonably believed that treating a spectrum as a time sequence would benefit its classification via LSTM. Thus, LSTM is employed to explore the sequential relations and interactions within a spectrum being treated as a time sequence. As such, LSTM learns the sequential properties and generates the representation of solar radio spectrum for classification. The experimental results demonstrate that LSTM can well capture the characteristics of solar radio spectrum, and thus achieves better classification accuracy.

This paper makes the first attempt to utilize convolutional neural network (CNN) for classification of solar radio spectrums. The solar radio spectrum is a two-dimensional gray-scale image with one dimension of frequency and the other of time. Taking the advantages of CNN, we can efficiently learn the distinct characteristic of different types of spectrum, and further classify them even more accurate. The proposed CNN-based network consists of four convolution layers, four pooling layers and one fully connected layer. Its input is spectrums of the size 120×120. The output gives the type of each spectrum among “burst”, “non-burst” and “calibration”. Experimental results demonstrate that the proposed CNN can achieve more accuracy of classification of solar radio spectrum beyond our previous efforts by employing deep belief network (DBN) and autoencoder (AE).

Various solar features can be seen on maps of the Sun in the mm and sub-mm wavelength range. The recently installed Atacama Large Millimeter/submillimeter Array (ALMA) is capable of observing the Sun in that wavelength range with an unprecedented spatial, temporal and spectral resolution. To interpret solar observations with ALMA the first important step is to compare ALMA maps with simultaneous images of the Sun recorded in other spectral ranges. First we identify different structures in the solar atmosphere seen in the optical, IR and EUV parts of the spectrum (quiet Sun (QS), active regions (AR), prominences on the disc, magnetic inversion lines (IL), coronal holes (CH) and coronal bright points (CBPs)) in a full disc solar ALMA image. The second aim is to measure the intensities (brightness temperatures) of those structures and compare them with the corresponding QS level. A full disc solar image at 1.21 mm obtained on December 18, 2015 during a CSV-EOC campaign with ALMA is calibrated and compared with full disc solar images from the same day in H\alpha, in He I 1083 nm core, and with SDO images (AIA at 170 nm, 30.4 nm, 21.1 nm, 19.3 nm, and 17.1 nm and HMI magnetogram). The brightness temperatures of various structures are determined by averaging over corresponding regions of interest in the ALMA image. Positions of the QS, ARs, prominences on the disc, ILs, CHs and CBPs are identified in the ALMA image. At 1.21 mm ARs appear as bright areas (but sunspots are dark), while prominences on the disc and CHs are not discernible from the QS background, although having slightly less intensity than surrounding QS regions. ILs appear as large, elongated dark structures and CBPs correspond to ALMA bright points. These results are in general agreement with sparse earlier measurements at similar wavelengths. The identification of CBPs represents the most important new result., Comment: 9 pages, 3 figures

The Atacama Large Millimeter-submillimeter Array (ALMA) radio telescope has commenced science observations of the Sun starting in late 2016. Since the Sun is much larger than the field of view of individual ALMA dishes, the ALMA interferometer is unable to measure the background level of solar emission when observing the solar disk. The absolute temperature scale is a critical measurement for much of ALMA solar science, including the understanding of energy transfer through the solar atmosphere, the properties of prominences, and the study of shock heating in the chromosphere. In order to provide an absolute temperature scale, ALMA solar observing will take advantage of the remarkable fast-scanning capabilities of the ALMA 12m dishes to make single-dish maps of the full Sun. This article reports on the results of an extensive commissioning effort to optimize the mapping procedure, and it describes the nature of the resulting data. Amplitude calibration is discussed in detail: a path that utilizes the two loads in the ALMA calibration system as well as sky measurements is described and applied to commissioning data. Inspection of a large number of single-dish datasets shows significant variation in the resulting temperatures, and based on the temperature distributions we derive quiet-Sun values at disk center of 7300 K at lambda=3 mm and 5900 K at lambda=1.3 mm. These values have statistical uncertainties of order 100 K, but systematic uncertainties in the temperature scale that may be significantly larger. Example images are presented from two periods with very different levels of solar activity. At a resolution of order 25 arcsec, the 1.3 mm wavelength images show temperatures on the disk that vary over about a 2000 K range., Comment: Solar Physics, accepted: 24 pages, 13 figures

The measurement of positions and sizes of radio sources in the observations of the fine structure of solar radio bursts is a determining factor for the selection of the radio emission mechanism. The identical parameters describing the radio sources for zebra structures (ZSs) and fiber bursts confirm there is a common mechanism for both structures. It is very important to measure the size of the source in the corona to determine if it is distributed along the height or if it is point-like. In both models of ZSs (the double plasma resonance (DPR) and the whistler model) the source must be distributed along the height, but by contrast to the stationary source in the DPR model, in the whistler model the source should be moving. Moreover, the direction of the space drift of the radio source must correlate with the frequency drift of stripes in the dynamic spectrum. Some models of ZSs require a local source, for example, the models based on the Bernstein modes, or on explosive instability. The selection of the radio emission mechanism for fast broadband pulsations with millisecond duration also depends on the parameters of their radio sources.

The Advanced Space-based Solar Observatory (ASO-S) is a mission proposed for the 25th solar maximum by the Chinese solar community. The scientific objectives are to study the relationships between the solar magnetic field, solar flares and coronal mass ejections (CMEs). Three payloads are deployed: the Full-disk vector MagnetoGraph (FMG), the Lyman-α Solar Telescope (LST) and the Hard X-ray Imager (HXI). ASO-S will perform the first simultaneous observations of the photospheric vector magnetic field, non-thermal imaging of solar flares, and the initiation and early propagation of CMEs on a single platform. ASO-S is scheduled to be launched into a 720 km Sun-synchronous orbit in 2022. This paper presents an overview of the mission till the end of Phase-B and the beginning of Phase-C.

A solar radio spectrometer records solar radio radiation in the radio waveband. Such solar radio radiation spanning multiple frequency channels and over a short time period could provide a solar radio spectrum which is a two dimensional image. The vertical axis of a spectrum represents frequency channel and the horizontal axis signifies time. Intrinsically, time dependence exists between neighboring columns of a spectrum since solar radio radiation varies continuously over time. Thus, a spectrum can be treated as a time series consisting of all columns of a spectrum, while treating it as a general image would lose its time series property. A recurrent neural network (RNN) is designed for time series analysis. It can explore the correlation and interaction between neighboring inputs of a time series by augmenting a loop in a network. This papermakes the first attempt to utilize an RNN, specifically long short-termmemory (LSTM), for solar radio spectrum classification. LSTM can mine well the context of a time series to acquire more information beyond a non-time series model. As such, as demonstrated by our experimental results, LSTM can learn a better representation of a spectrum, and thus contribute better classification.

Quasi-periodic pulsations (QPPs) are frequently observed in solar flares, which may reveal some essential characteristics of both thermal and nonthermal energy releases. This work presents multi-wavelength imaging observations of an M8.7 flare in active region AR 12242 on 2014 December 17. We found that there were three different QPPs: UV QPPs with a period of about 4 minutes at 1600 Å images near the center of the active region lasting from the preflare phase to the impulsive phase; EUV QPPs with a period of about 3 minutes along the circular ribbon during the preflare phase; and radio QPPs with a period of about 2 minutes at frequencies of 1.2–2.0 GHz around the flaring source region during the impulsive phase. The observations include the radio images observed by the Mingantu Spectral Radioheliograph in China at frequencies of 1.2–2.0 GHz for the first time, microwave images by the Nobeyama Radioheliograph, UV and EUV images by AIA/SDO, and a magnetogram by HMI/SDO. We suggest that the 4 minute UV QPPs should be modulated by the sunspot oscillations, and the 3 minute EUV QPPs are closely related to the 2 minute radio QPPs for their source regions connected by a group of coronal loops. We propose that the intermittent magnetic reconnecting downward and upward plasmoids may be the possible trigger of both the preflare 3 minute EUV QPPs and the impulsive 2 minute radio QPPs. The other possible mechanism is LRC oscillation, which is associated with the current-carrying coronal loops. The latter mechanism implies that the existence of preflare QPPs may be a possible precursor to solar flares.

Studying the origin of solar activities, revealing the basic laws of solar activities and forecasting the violent solar eruptions are not only important problems in astronomy, but also the basis of protecting the near-Earth space environment and the many high-technology systems. In order to achieve this target, the radio telescope is required to have the capability to detect the solar element bursts and cover the huge source regions including magnetic energy release, propagations and evolutions. Based on these scientific objectives and the development of radio telescopes, in this paper, we proposed a new solar radio telescope array. It can be expanded step by step on the basis of the present MUSER and the forthcoming meter-decimeter wavelength radioheliograph of Meridian II project. The maximum baseline of the proposed array will be extended to 30 km, and the spatial resolution will be improved to 0.2. This array is able to detect the element burst procedure of different radio bursts in solar atmosphere plasma. The system schematic and the specifications of this array have been studies and designed preliminarily.

Although it is believed that Alfven waves can be present in the form of torsional modes in interplanetary magnetic flux ropes, convincing observational evidence remains elusive. In this Letter, we report the detection of Alfven waves embedded within an interplanetary magnetic cloud (MC) on 2003 March 20, which exhibited features quite different from those upstream and downstream. The magnetic field inside the MC underwent alternate rotations along an arc through a relatively small angle in the plane perpendicular to the minimum variance direction, which seems consistent with the appearance of torsional modes. A significant poloidal motion of plasma existed in the MC, thus it is possible that the field-aligned helical plasma flow was mixed with Alfven waves exhibiting high correlation between plasma velocity and the magnetic field.

As the Sun rotates, a fast stream can overtake a preceding slow stream, leading to the formation of a stream interaction region (SIR). Two neighboring SIRs may eventually coalesce to produce a merged interaction region (MIR) en route to the outer heliosphere. However, instances of significant interaction and merging of two neighboring SIRs within 1 au are thought to be extremely rare. In this Letter, we present a case report of two interacting and merging SIRs observed near 1 au, which was associated with two adjacent low-latitude coronal holes. The two SIRs were filled with outward propagating Alfvenic fluctuations associated with magnetohydrodynamic turbulence. A reconnection exhaust associated with a current sheet was identified. We suggest that magnetic reconnection represented a potentially important mechanism for the merging of two neighboring SIRs. This observation may shed light on the understanding of the structure and formation of a MIR within 1 au.