The activities of Chinese space solar physics in 2014—2016 were mainly undertaken within the framework of Strategic Priority Program on Space Science,sponsored by CAS,which include:to accomplish the last version for the mid and long-term(2016—2030) plan of Chinese space solar physics;to subsidy a few of pre-study projects of space solar physics;to implement two intensive study projects,ASO-S and SPORT.This paper summarizes these activities briefly.
From the Reuven Ramaty High Energy Solar Spectroscopic Imager （RHESS1） catalog we select events which have approximately the same GOES class （high C - low M or 500-1200 counts s-1 within the RHESSI 6-12 keV energy band）, but with different maximal energies of detected hard X-rays. The selected events are subdivided into two groups： （1） flares with X-ray emissions observed by RHESSI up to only 50 keV and （2） flares with hard X-ray emission observed also above 50 keV. The main task is to understand observational peculiarities of these two flare groups. We use RHESSIX-ray data to obtain spectral and spa- tial information in order to find differences between selected groups. Spectra and images are analyzed in detail for six events （case study）. For a larger number of samples （85 and 28 flares in the low-energy and high-energy groups respectively） we only make some generalizations. In spectral analysis we use the thick- target model for hard X-ray emission and one temperature assumption for thermal soft X-ray emission. RHESSI X-ray images are used for determination of flare region sizes. Although thermal and spatial prop- erties of these two groups of flares are not easily distinguishable, power law indices of hard X-rays show significant differences. Events from the high-energy group generally have a harder spectrum. Therefore, the efficiency of chromospheric evaporation is not sensitive to the hardness of nonthermal electron spectra but rather depends on the total energy flux of nonthermal electrons.
Ivan N.SharykinAlexei B.StruminskyIvan V.ZimovetsWei-Qun Gan
定标是射电天文观测中基础而重要的工作.定标工作可以得到太阳观测中的一个重要物理量:太阳射电辐射流量,可以扣除射电频谱仪的通道不均匀性,清晰显示射电频谱特征.结合紫金山天文台射电频谱仪的观测数据,详细介绍了定标的基本方法,分析了定标常数的变化情况,最后给出了定标结果,并与野边山射电偏振计以及RHESSI(The Reuven Ramaty High Energy Solar Spectroscopic Imager)卫星硬X射线波段的几个太阳耀斑的观测结果进行了比较,结果符合耀斑的光变特征.其中对一个耀斑脉冲相硬X射线流量和微波光变的相关性的分析表明这些观测可以用来研究有关的辐射机制以及相应的能量释放和粒子加速过程.
Properties of fractional Brownian motions （fBms） have been investigated by researchers in different fields, e.g. statistics, hydrology, biology, finance, and public transportation, which has helped us better understand many complex time series observed in nature [1-4]. The Hurst exponent H （0 〈 H 〈 1） is the most important parameter characterizing any given time series F（t）, where t represents the time steps, and the fractal dimension D is determined via the relation D = 2 - H.
BingQiang QiaoSiMing LiuHouDun ZengXiang LiBenZhong Dai
The power-law frequency distributions of the peak flux of solar flare X-ray emission have been studied extensively and attributed to a system having self-organized criticality （SOC）. In this paper, we first show that, so long as the shape of the normalized light curve is not correlated with the peak flux, the flux histogram of solar flares also follows a power-law distribution with the same spectral index as the power- law frequency distribution of the peak flux, which may partially explain why power-law distributions are ubiquitous in the Universe. We then show that the spectral indexes of the histograms of soft X-ray fluxes observed by GOES satellites in two different energy channels are different： the higher energy channel has a harder distribution than the lower energy channel, which challenges the universal power-law distribution predicted by SOC models and implies a very soft distribution of thermal energy content of plasmas probed by the GOES satellites. The temperature （T） distribution, on the other hand, approaches a power-law dis- tribution with an index of 2 for high values of T. Hence the application of SOC models to the statistical properties of solar flares needs to be revisited.
You-Ping LiLi FengPing ZhangSi-Ming LiuWei-Qun Gan
