Contact Binaries: A Study of the Proximity Effects and Gravity Darkening Based on Kopal’s Fourier Method

A new method for the determination of the proximity effects and gravity darkening exponents in contact binaries of W UMa type is presented. The method is based on Kopal’s method of Fourier analysis of the light changes of eclipsing variables in the Frequency Domain. The method was applied to 36 W UMa systems for which geometric and photometric elements have been derived by the most powerful techniques. The derived values are very close to those predicted by the existing theory of radiative transfer or convective equilibrium.     

UV Leo: The Binary with the Two Suns

BV light curves of the eclipsing binary UV Leo obtained at the Kryonerion Astronomical Station of the National Observatory of Athens, Greece, are analyzed. The analysis is based on a Roche configuration with two spots on the secondary surface. The elements of the two components of the system are calculated and the spot characteristics are given.     

On the Period Variation of the W UMa-type Contact Binary V502 Ophiuchi

The variation in the orbital period of the W UMa type contact binary V502 Oph is analyzed. The orbital period exhibits a wavelike variation with a periodicity of 23.0 years and an amplitude of △P = 1.24×10~(-6) days superimposed on secular decrease of dP/dt = 1.68×10-7 day per year. The long-term decrease may be accompanied by the contraction of the secondary at a rate of 83 m per year and a mass transfer rate from the primary to the secondary of 4.28×10~8 M per year. The short-term oscillation may be explained by the presence of a third component. Orbital elements of the third body and its possible mass are presented.     

Experimental solidification of anhydrous latitic and trachytic melts at different cooling rates: The role of nucleation kinetics

Two sets of cooling experiments were run at atmospheric conditions for two anhydrous starting latitic and trachytic melts: 1) five cooling rates (25, 12.5, 3, 0.5, and 0.125 °C/min) between 1300° and 800 °C, and 2) a 0.5 °C/min cooling rate from 1300 °C with quench temperatures at 1200°, 1100°, 1000° and 900 °C. Trachytic run-products are invariably glassy. Nucleation is also suppressed in the latitic run-products at the three highest cooling rates. Conversely, in the 0.5 and 0.125 °C/min runs, latites have a crystal content of  90 vol.%. The phases are: plagioclase, clinopyroxene, glass and iron-bearing oxide (in order of abundance). The variable quench temperatures, investigated by coupling experiments with Pt wire and Pt capsule sample containers in set 2, again did not produce crystallization of trachyte, whereas latitic samples are characterized by  10 vol.% of oxides, pyroxenes and plagioclase (in order of appearance), at temperature < 1000 °C. Effects of (preferential) heterogeneous nucleation on sample holders, of superheating degree, and chemical species loss during cooling are absent for both melt compositions. The difference of solidification paths between these two silicate melts can be ascribed only to their small chemical differences. In comparison with calculated equilibrium conditions all the experimental latitic and trachytic run-products revealed strong kinetic effects, interpretable in the light of the nucleation theory. The glass-forming ability (GFA) of trachyte is higher, whereas their critical cooling rate (Rc) is lower (< 0.125 °C/min), in comparison to latitic melts (Rc > 0.5 °C/min). The experimental results carried out in this study can be applied to lava flows and domes; trachytic lavas are able to flow for longer period with respect to latitic ones in a metastable condition. Glass-rich terrestrial lavas, i.e. obsidians, can be the result of sluggish nucleation kinetics due to the relative high polymerisation of evolved silicate melts.     

Inference and uncertainty of snow depth spatial distribution at the kilometre scale in the Colorado Rocky Mountains: the effects of sample size,random sampling,predictor quality,and validation procedures

Historically, observing snow depth over large areas has been difficult. When snow depth observations are sparse, regression models can be used to infer the snow depth over a given area. Data sparsity has also left many important questions about such inference unexamined. Improved inference, or estimation, of snow depth and its spatial distribution from a given set of observations can benefit a wide range of applications from water resource management, to ecological studies, to validation of satellite estimates of snow pack. The development of Light Detection and Ranging (LiDAR) technology has provided non‐sparse snow depth measurements, which we use in this study, to address fundamental questions about snow depth inference using both sparse and non‐sparse observations. For example, when are more data needed and when are data redundant? Results apply to both traditional and manual snow depth measurements and to LiDAR observations. Through sampling experiments on high‐resolution LiDAR snow depth observations at six separate 1.17‐km² sites in the Colorado Rocky Mountains, we provide novel perspectives on a variety of issues affecting the regression estimation of snow depth from sparse observations. We measure the effects of observation count, random selection of observations, quality of predictor variables, and cross‐validation procedures using three skill metrics: percent error in total snow volume, root mean squared error (RMSE), and R². Extremes of predictor quality are used to understand the range of its effect; how do predictors downloaded from internet perform against more accurate predictors measured by LiDAR? Whereas cross validation remains the only option for validating inference from sparse observations, in our experiments, the full set of LiDAR‐measured snow depths can be considered the ‘true’ spatial distribution and used to understand cross‐validation bias at the spatial scale of inference. We model at the 30‐m resolution of readily available predictors, which is a popular spatial resolution in the literature. Three regression models are also compared, and we briefly examine how sampling design affects model skill. Results quantify the primary dependence of each skill metric on observation count that ranges over three orders of magnitude, doubling at each step from 25 up to 3200. Whereas uncertainty (resulting from random selection of observations) in percent error of true total snow volume is typically well constrained by 100–200 observations, there is considerable uncertainty in the inferred spatial distribution (R²) even at medium observation counts (200–800). We show that percent error in total snow volume is not sensitive to predictor quality, although RMSE and R² (measures of spatial distribution) often depend critically on it. Inaccuracies of downloaded predictors (most often the vegetation predictors) can easily require a quadrupling of observation count to match RMSE and R² scores obtained by LiDAR‐measured predictors. Under cross validation, the RMSE and R² skill measures are consistently biased towards poorer results than their true validations. This is primarily a result of greater variance at the spatial scales of point observations used for cross validation than at the 30‐m resolution of the model. The magnitude of this bias depends on individual site characteristics, observation count (for our experimental design), and sampling design. Sampling designs that maximize independent information maximize cross‐validation bias but also maximize true R². The bagging tree model is found to generally outperform the other regression models in the study on several criteria. Finally, we discuss and recommend use of LiDAR in conjunction with regression modelling to advance understanding of snow depth spatial distribution at spatial scales of thousands of square kilometres. Copyright © 2012 John Wiley & Sons, Ltd.     

高维遥感图像的快速分类算法

为了实现对高维遥感图像的快速准确分类,提出了一种基于k均值二叉树支持向量机(SVM)的分类方法。该方法通过对选取的训练样本进行k均值聚类,生成支持向量机分类二叉树,作为确定最佳分类顺序的依据,以降低分类过程中的误差累积并提高整体分类精度,而且可缓解由样本数量不均衡导致的分类误差。该方法可在不进行降维处理的情况下,对高维遥感图像进行快速准确分类。测试结果表明,其分类速度和分类精度都优于传统的支持向量机分类结果。     

矿震成核过程的公里尺度研究

成核过程是地震机理研究的重要部分.通过岩石实验、高温高压和数值模拟认为,地震成核的临界尺度为大地震总破裂长度的十分之一,一般为10~20 km左右;地震成核时间从年到秒、甚至毫秒.本文利用山东省宁阳县华丰煤矿立体台网的岩爆观测,进行了公里尺度的破裂成核过程实验研究.通过对华丰煤矿1995年2月~1996年5月期间的地脉动记录和12000次小震记录资料的分析,计算了它们的地脉动、S波和P波振幅比以及S波波峰的到时差,得到ML=2.9矿震的成核时间为50天,成核临界尺度为5 km.     

The additional radiation of Cyg X-1 at primary minimum

New UBV-photoelectric observations of the well-known massive X-ray binary system Cyg X-1/V 1357 Cyg are obtained near the primary minimum. The detailed analysis of these observations confirms the existence of additional blue radiation which appears as a narrow peak with an amplitude of 0.01–0.02 mag near phase 0.00 on the light curve (the superior conjunction of the relativistic component), firstly detected by Lyuty (1985). This emission does not appear at every orbital cycle. The appearance of this narrow peak of additional blue radiation on the light curve of Cyg X-1 can be explained as the radiation of relativistic electrons in the disturbed magnetic field of the optical star in frames of the model proposed by Ikhsanov and Fabrika (1990).     

台风菲特暴雨诊断分析

"菲特"台风暴雨具有阶段性特征,包括台风远距离降水、台风倒槽和内螺旋雨带降水、台风外部螺旋雨带降水、台风残留低压环流与冷空气相互作用降水4个阶段。利用地面观测、气象雷达观测、NCEP分析资料,对"菲特"台风暴雨环流形势进行了分析。引导台风东移的高压东西部具有不同热力属性,东部暖性深厚、西部冷性浅薄。浅薄冷高压阻挡登陆台风继续西移,延长台风倒槽和外围螺旋雨带的降水时间。"丹娜丝"台风的靠近,有利于东南风水汽输送的增强。副热带高压的增强,在黄海上空逼近东移高空槽形成稳定的高空急流。文章提出与传统垂直风切变大、高空急流强的冷空气阻挡型不同的侵入型冷空气和台风相互作用形势。侵入型冷空气从低层入侵,影响台风残留低压的外围环流。在低压外围环流的北部形成较强的东北风,并与海上的东风对峙辐合形成海岸锋。冷空气侵入型的空间不对称特征明显:对流有效位能东高西低,垂直风切变西北高东南低。残留低压的中层受冷空气影响较小,沿海地区的东南风持续的时间更长。中层高位涡区与地面海岸锋的互应,为变性的台风残留低压暴雨提供有利条件。     

慧眼-HXMT观测到的黑洞双星系统中的W-K 关系

通过几十年的观测研究, 黑洞X射线双星(X-Ray Binary, XRB)部分特征被揭示. 然而, 吸积盘结构尚不确定. 黑洞XRB功率密度谱的截断频率与准周期振荡(Quasi Periodic Oscillation, QPO)的相关性质(W-K关系)可以限制吸积盘结构. 利用慧眼-HXMT (Hard X-ray Modulation Telescope)观测到的5个黑洞XRB的数据, 对黑洞XRB的W-K关系进行了研究, 结果表明在慧眼-HXMT观测的3个探测器能段中W-K关系成立. 此外在MAXI J1535-571之中存在截断频率和吸积盘内半径的相关关系, 这和截断的吸积盘结构一致. 如果观测到的功率密度谱来自质量吸积率的扰动传播, 可以推测吸积盘内半径接近最内圆形稳定轨道, 此黑洞可能是高自旋系统.