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Time Scales and Tidal Effects in Minor Mergers
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作者 Yu Lu and Jian-Yan WeiNational Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012 luyu 《Chinese Journal of Astronomy and Astrophysics》 CSCD 北大核心 2003年第5期395-409,共15页
We use controlled N-body simulation to investigate the dynamical processes(dynamical friction, tidal truncation, etc.) involved in the merging of small satellites into biggerhalos. We confirm the validity of some anal... We use controlled N-body simulation to investigate the dynamical processes(dynamical friction, tidal truncation, etc.) involved in the merging of small satellites into biggerhalos. We confirm the validity of some analytic formulae proposed earlier based on simplearguments. For rigid satellites represented by softened point masses, the merging time scale dependson both the orbital shape and concentration of the satellite. The dependence on orbital ellipticityis roughly a power law, as suggested by Lacey & Cole, and the dependence on satellite concentrationis similar to that proposed by White. When merging satellites are represented by non-rigid objects,Tidal effects must be considered. We found that material beyond the tidal radius are stripped off.The decrease in the satellite mass might mean an increase in the merging time scale, but in fact,the merging time is decreased, because the stripped-off material carries away a proportionatelylarger amount of of orbital energy and angular momentum. 展开更多
关键词 cosmology: dark matter galaxies: kinematics and dynamics galaxies:structure galaxies: interactions numerical methods
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Distance function selection in several clustering algorithms
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作者 luyu 《Journal of Chongqing University》 CAS 2004年第1期47-50,共4页
Most clustering algorithms need to describe the similarity of objects by a predefined distance function. Three distance functions which are widely used in two traditional clustering algorithms k-means and hierarchical... Most clustering algorithms need to describe the similarity of objects by a predefined distance function. Three distance functions which are widely used in two traditional clustering algorithms k-means and hierarchical clustering were investigated. Both theoretical analysis and detailed experimental results were given. It is shown that a distance function greatly affects clustering results and can be used to detect the outlier of a cluster by the comparison of such different results and give the shape information of clusters. In practice situation, it is suggested to use different distance function separately, compare the clustering results and pick out the 搒wing points? And such points may leak out more information for data analysts. 展开更多
关键词 distance function clustering algorithms K-MEANS DENDROGRAM data mining
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