摘要
天文学是一门古老的科学,自有人类文明史以来,天文学就有重要的地位。观测仪器设备及数据收集能力的大幅度提高,使得我们迈入了天文观测数据的“雪崩”时代。天体在光学波段的光谱包含着丰富的物理信息。星系的光谱可以给出它们的距离、构成、分布和运动等信息。恒星的光谱可以确定它们的分布和运动、光度、温度、化学组成等物理状态。从大量天体的光谱观测中还会发现奇异的天体和天文现象,将引起人类对宇宙天体的新认识。
LAMOST巡天正式开始,每晚的观测将要产生数万条光谱。整个巡天计划完成将会产生107数量级的光谱数据,如此庞大数量的光谱显然不能通过传统的人工方式进行的,因此需要研究相关的算法进行光谱的自动处理。
在一维光谱处理中,恒星参数测量部分为银河系恒星光谱巡天提供恒星运动学、化学丰度、有效温度、有效重力加速度等信息,是一维光谱处理中非常重要的部分。从海量巡天数据发现特殊稀少未知天体,能够为天文学各种研究提供样本支持。
本研究的工作主要分为两部分:
(1)设计并实现适用于LAMOST光谱的恒星大气参数测量系统,包括光谱预处理、参数测量等模块,其中参数测量模块支持扩展性,现已集成SSPP、UlySS等软件包,并加入PLS方法,随着研究的不断进行,会有更多的方法集成进来。软件系统采用Python,结合GTK实现图形用户界面,运用多线程编程计算实现对海量光谱的快速批量处理。
(2)研究可用于LAMOST光谱中发现特殊天体的数据挖掘的算法,包括有指导和无指导两类,其中前者主要发现一些已知的特殊天体,而后者主要是发现一些未知的特殊天体。研究的方法主要包括随机森林算法及遗传算法等。
As an ancient science, astronomy played an import part since the beginning of human civilization. With the great improvement of observing equipment and data collection capabilities, astronomical observations come into the avalanche era. The optical spectral of celestial bodies contain a great deal of information. From the spectra of galaxies, we can get their distance, composition, distribution and motion etc. From the stellar spectra,their distribution, motion, luminosity, temperature and its chemical composition etc. can be obtained. Furthermore, we can discover some special, rare and unknown objects or phenomena which will lead to human new understanding of celestial bodies.
With the launch of LAMOST Survey, tens of thousands of spectra of celestial bodies will be collected in each observation night and totally about 10,000,000 spectra will be obtained. It's difficult to deal such massive spectra by hand, hence some algorithms should be developed to process the spectra automatically.
In the LAMOST 1D spectra processing Pipeline, the Stellar Paramater moudle (LAMOST_1DSP) provide physical parameters which are useful in LEGUE.The discovered spectra of special, rare, unknown celestial objects will be large samples for astronomy research.
The work consists of two parts:
(1) The design and implementation of LAMOST automated 1D Stellar atmospheric Parameters measurement system (LAMOST 1DSP), including the spectral preprocessing and parameter measurement modules which support the expansion of parameter measurement. And now Latter module has integrated SSPP, UlySS packages and the PLS method. There will be more methods integrated in the future work. The system is implemented using Python, GTK and multi-threaded programming.
(2) Study some data mining algorithms to discover spectra to find specific objects. The algorithms are divided into two parts:supervised methods and un supervised methods. Research methods include random forest algorithm and genetic algorithm etc.
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