以型態辨識法來確認合併星系;Identification of Merging Galaxies Using Pattern Recognition Methods

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/62374

Title:	以型態辨識法來確認合併星系;Identification of Merging Galaxies Using Pattern Recognition Methods
Authors:	黃崇源
Contributors:	國立中央大學天文研究所
Keywords:	物理
Date:	2012-12-01
Issue Date:	2014-03-17 11:31:21 (UTC+8)
Publisher:	行政院國家科學委員會
Abstract:	研究期間：10108~10207;Galaxy merging is the most important process in galaxy evolution. However, people do not have enough uniform samples of distant faint merging galaxies to investigate how galaxies were evolving. For the past few years, we have been developing new algorithms in order to search for distant faint merging galaxies and galaxy clusters. We had an important breakthrough in searching merging galaxies last year. We developed a new pattern recognition algorithm to identify merging galaxies. We discovered ~ 15,000 new pairs of merging galaxies within 422 degree square of Red Sequence Cluster Survey 2 (RCS2) of CFHT observations. Furthermore, we also found nine new candidates of galaxy clusters by searching for regions with significant density enhancements of merging galaxies. This catalog has the largest number of morphologically identified interacting and merging galaxies based on consistent searching criteria. These sources provide a uniform sample of merging galaxies for further photometric and spectroscopic studies of galaxy evolution. Although the pattern-recognition algorithms are currently the best algorithms for searching merging galaxies, it is still not efficient enough. Furthermore, we cannot perform photometric measurements in the current algorithms. In this project, we plan to improve the algorithms to make it more efficient by adding some more shape parameters and to develop new photometric algorithms suitable for merging galaxies. In some preliminary testing, we found that we would be able to improve the efficiency by a factor of ten with proper shape parameters and moment analyses. We thus expect to discover more than 100,000 merging galaxies even just with our current available RSC2 data sets. In the photometric measurements of merging galaxies, tradition apertures are not very suitable because the shapes of the merging galaxies are usually very complicated. We will also develop an adaptive algorithm of aperture selections for photometric measurements based on our pattern recognition methods. The aperture algorithm will be useful for merging galaxies of irregular patterns and for sources in a crowded region. We will study galaxy evolution and search for new galaxy clusters using the results obtained from our searching and photometric algorithms. The huge amounts of data and information we can extract from our new techniques are expected to have big impacts on the researches of galaxy evolution and large-scale structures of the universe.
Relation:	財團法人國家實驗研究院科技政策研究與資訊中心
Appears in Collections:	[Graduate Institute of Astronomy] Research Project

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