An Automatic Method for Detecting Transients and Variable Sources in AST3 Survey Based on Image Subtraction and Random Forest

AST3-2 (the second Antarctic Survey Telescope) is located in Antarctic Dome A, the loftiest ice dome on the Antarctic Plateau. It produces a huge amount of observational data which require a more efficient data reduction program to be developed. Also the data transmission in Antarctica is much difficult, thus it is necessary to perform data reduction and detect variable and transient sources remotely and automatically in Antarctica, but this attempt is restricted by the unsatisfactory performance of the low power consumption computer in Antarctica. For realizing this purpose, to develop a new method based on the existing image subtraction method and random forest algorithm, taking the AST3-2 2016 dataset as the test sample, becomes an alternative choice. This method performs image subtraction on the dataset, then applies the principle component analysis to extract the features of residual images. Random forest is used as a machine learning classifier, and in the test a recall rate of 97% is resulted for the positive sample. Our work has verified the feasibility and accuracy of this method, and finally found out a batch of candidates for variable stars in the AST3-2 2016 dataset.     

An optimal extraction algorithm for imaging photometry

This paper is primarily an investigation of whether the 'optimal extraction' techniques used in CCD spectroscopy can be applied to imaging photometry. It is found that using such techniques provides a gain of around 10 per cent in signal-to-noise ratio over normal aperture photometry. Formally, it is shown to be equivalent to profile fitting, but offers advantages of robust error estimation, freedom from bias introduced by mis-estimating the point spread function, and convenience. In addition some other techniques are presented, which can be applied to profile fitting, aperture photometry and the 'optimal' photometry. Code implementing these algorithms is available at http://www.astro.keele.ac.uk/~timn/.     

Fast compression and reconstruction of astronomical images based on compressed sensing

With the fast increase in the resolution of astronomical images, the question of how to process and transfer such large images has become a key issue in astronomy. We propose a new real-time compression and fast reconstruction algorithm for astronomical images based on compressive sensing techniques. We first reconstruct the original signal with fewer measurements, according to its compressibility. Then,based on the characteristics of astronomical images, we apply Daubechies orthogonal wavelets to obtain a sparse representation. A matrix representing a random Fourier ensemble is used to obtain a sparse representation in a lower dimensional space. For reconstructing the image, we propose a novel minimum total variation with block adaptive sensing to balance the accuracy and computation time. Our experimental results show that the proposed algorithm can efficiently reconstruct colorful astronomical images with high resolution and improve the applicability of compressed sensing.     

Integer‐ambiguity resolution in astronomy and geodesy

Recent theoretical developments in astronomical aperture synthesis have revealed the existence of integer‐ambiguity prob‐lems. Those problems, which appear in the self‐calibration procedures of radio imaging, have been shown to be similar to the nearest‐lattice point (NLP) problems encountered in high‐precision geodetic positioning and in global navigation satellite systems. In this paper we analyse the theoretical aspects of the matter and propose new methods for solving those NLP problems. The related optimization aspects concern both the preconditioning stage, and the discrete‐search stage in which the integer ambiguities are finally fixed. Our algorithms, which are described in an explicit manner, can easily be implemented. They lead to substantial gains in the processing time of both stages. Their efficiency was shown via intensive numerical tests. (© 2014 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Adaptive Optics Image Restoration Based on Frame Selection and Multi-frame Blind Deconvolution

Restricted by the observational condition and the hardware, adaptive optics can only make a partial correction of the optical images blurred by atmospheric turbulence. A postprocessing method based on frame selection and multi-frame blind deconvolution is proposed for the restoration of high-resolution adaptive optics images. By frame selection we mean we first make a selection of the degraded (blurred) images for participation in the iterative blind deconvolution calculation, with no need of any a priori knowledge, and with only a positivity constraint. This method has been applied to the restoration of some stellar images observed by the 61-element adaptive optics system installed on the Yunnan Observatory 1.2m telescope. The experimental results indicate that this method can effectively compensate for the residual errors of the adaptive optics system on the image, and the restored image can reach the diffraction-limited quality.     

Wavelet domain Bayesian denoising of string signal in the cosmic microwave background

An algorithm is proposed for denoising the signal induced by cosmic strings in the cosmic microwave background. A Bayesian approach is taken, based on modelling the string signal in the wavelet domain with generalized Gaussian distributions. Good performance of the algorithm is demonstrated by simulated experiments at arcminute resolution under noise conditions including primary and secondary cosmic microwave background anisotropies, as well as instrumental noise.     

The sodium tail of the Moon

During the few days centered about new Moon, the lunar surface is optically hidden from Earth-based observers. However, the Moon still offers an observable: an extended sodium tail. The lunar sodium tail is the escaping “hot” component of a coma-like exosphere of sodium generated by photon-stimulated desorption, solar wind sputtering and meteoroid impact. Neutral sodium atoms escaping lunar gravity experience solar radiation pressure that drives them into the anti-solar direction forming a comet-like tail. During new Moon time, the geometry of the Sun, Moon and Earth is such that the anti-sunward sodium flux is perturbed by the terrestrial gravitational field resulting in its focusing into a dense core that extends beyond the Earth. An all-sky camera situated at the El Leoncito Observatory (CASLEO) in Argentina has been successfully imaging this tail through a sodium filter at each lunation since April 2006. This paper reports on the results of the brightness of the lunar sodium tail spanning 31 lunations between April 2006 and September 2008. Brightness variability trends are compared with both sporadic and shower meteor activity, solar wind proton energy flux and solar near ultra violet (NUV) patterns for possible correlations. Results suggest minimal variability in the brightness of the observed lunar sodium tail, generally uncorrelated with any single source, yet consistent with a multi-year period of minimal solar activity and non-intense meteoric fluxes.     

Digitization of sunspot drawings by Spörer made in 1861–1894

Most of our knowledge about the Sun's activity cycle arises from sunspot observations over the last centuries since telescopes have been used for astronomy. The German astronomer Gustav Spörer observed almost daily the Sun from 1861 until the beginning of 1894 and assembled a 33‐year collection of sunspot data covering a total of 445 solar rotation periods. These sunspot drawings were carefully placed on an equidistant grid of heliographic longitude and latitude for each rotation period, which were then copied to copper plates for a lithographic reproduction of the drawings in astronomical journals. In this article, we describe in detail the process of capturing these data as digital images, correcting for various effects of the aging print materials, and preparing the data for contemporary scientific analysis based on advanced image processing techniques. With the processed data we create a butterfly diagram aggregating sunspot areas, and we present methods to measure the size of sunspots (umbra and penumbra) and to determine tilt angles of active regions. A probability density function of the sunspot area is computed, which conforms to contemporary data after rescaling. (© 2015 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

AIPS对综合孔径展源的图象处理

本文介绍了用美国国立射电天文台图象处理软件系统—AIPS对综合孔径VLA观测数据的处理方法,特别是对展源,要得到高质量的图象,在编辑及成图中要注意的事项。作者根据自己的实际工作,总结了用AIPS进行图象处理的经验。     

1997年3月9日漠河日全食外日冕结构及相对强度分布

利用简单的视频图像采集系统 ,对 1 997年 3月 9日用PanasonicNV -S880EN型摄像机拍摄的黑龙江漠河日全食黄光 (加GG1 1滤光片 )和白光日冕观测资料进行计算处理 ,得到大于 1 .5R⊙ 的太阳活动低年外日冕结构及其相对强度分布。