SKLOF: A New Algorithm to Reduce the Range of Supernova Candidates
TU Liang-ping1, 2, WEI Hui-ming1, WEI Peng2, PAN Jing-chang3, LUO A-li2, ZHAO Yong-heng2
1. School of Science, University of Science and Technology Liaoning, Anshan 114051, China 2. Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China 3. School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai, Weihai 264209, China
Abstract：Supernova (SN) is called the “standard candles” in the cosmology, the probability of outbreak in the galaxy is very low and is a kind of special, rare astronomical objects. Only in a large number of galaxies, we have a chance to find the supernova. The supernova which is in the midst of explosion will illuminate the entire galaxy, so the spectra of galaxies we obtained have obvious features of supernova. But the number of supernova have been found is very small relative to the large number of astronomical objects. The time computation that search the supernova be the key to weather the follow-up observations, therefore it needs to look for an efficient method. The time complexity of the density-based outlier detecting algorithm (LOF) is not ideal, which effects its application in large datasets. Through the improvement of LOF algorithm, a new algorithm that reduces the searching range of supernova candidates in a flood of spectra of galaxies is introduced and named SKLOF. Firstly, the spectra datasets are pruned and we can get rid of most objects are impossible to be the outliers. Secondly, we use the improved LOF algorithm to calculate the local outlier factors (LOF) of the spectra datasets remained and all LOFs are arranged in descending order. Finally, we can get the smaller searching range of the supernova candidates for the subsequent identification. The experimental results show that the algorithm is very effective, not only improved in accuracy, but also reduce the operation time compared with LOF algorithm with the guarantee of the accuracy of detection.
屠良平1, 2，魏会明1，韦 鹏2，潘景昌3，罗阿理2，赵永恒2 . SKLOF：一种新的超新星候选范围约减算法 [J]. 光谱学与光谱分析, 2015, 35(01): 258-262.
TU Liang-ping1, 2, WEI Hui-ming1, WEI Peng2, PAN Jing-chang3, LUO A-li2, ZHAO Yong-heng2 . SKLOF: A New Algorithm to Reduce the Range of Supernova Candidates . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 35(01): 258-262.
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