Cluster identification and characterization of physical fields  

作　　者：ZHANG GuangCai,XU AiGuo,LU Guo & MO ZeYao National Key Laboratory of Computational Physics,Institute of Applied Physics and Computational Mathematics,Beijing 100088,China 

出　　处：《Science China(Physics,Mechanics & Astronomy)》2010年第9期1610-1618,共9页中国科学：物理学、力学、天文学（英文版）

基　　金：supported by the National Natural Science Foundation of China (Grant Nos 10702010 and 10775018);the Science Foundations of the Laboratory of Computational Physics and China Academy of Engineering Physics (Grant Nos.2009A0102005 and 2009B0101012)

摘　　要：The description of complex configuration is a difficult issue.We present a powerful technique for cluster identification and characterization.The scheme is designed to treat and analyze the experimental and/or simulation data from various methods.The main steps are as follows.We first divide the space using face or volume elements from discrete points.Then,we combine the elements with the same and/or similar properties to construct clusters with special physical characterizations.In the algorithm,we adopt an administrative structure of a hierarchy-tree for spatial bodies such as points,lines,faces,blocks,and clusters.Two fast search algorithms with the complexity lnN are generated.The establishment of the hierarchy-tree and the fast searching of spatial bodies are general,which are independent of spatial dimensions.Therefore,it is easy to extend the method to other fields.As a verification and validation,we applied this method and analyzed some two-dimensional and three-dimensional random data.The description of complex configuration is a difficult issue.We present a powerful technique for cluster identification and characterization.The scheme is designed to treat and analyze the experimental and/or simulation data from various methods.The main steps are as follows.We first divide the space using face or volume elements from discrete points.Then,we combine the elements with the same and/or similar properties to construct clusters with special physical characterizations.In the algorithm,we adopt an administrative structure of a hierarchy-tree for spatial bodies such as points,lines,faces,blocks,and clusters.Two fast search algorithms with the complexity lnN are generated.The establishment of the hierarchy-tree and the fast searching of spatial bodies are general,which are independent of spatial dimensions.Therefore,it is easy to extend the method to other fields.As a verification and validation,we applied this method and analyzed some two-dimensional and three-dimensional random data.

关 键 词：spatial hierarchical TREE fast SEARCH complex CONFIGURATION dynamic physical FIELDS CLUSTER IDENTIFICATION 

分 类 号：O411[理学—理论物理]