ITP OpenIR  > 理论物理所2015年知识产出
Fast adaptive flat-histogram ensemble to enhance the sampling in large systems
Xu, S; Zhou, X; Jiang, Y; Wang, YT; Zhou, X (reprint author), Univ Chinese Acad Sci, Sch Phys Sci, Beijing 100049, Peoples R China.
2015
发表期刊SCIENCE CHINA-PHYSICS MECHANICS & ASTRONOMY
卷号58期号:9页码:590501
文章类型Article
摘要An efficient novel algorithm was developed to estimate the Density of States (DOS) for large systems by calculating the ensemble means of an extensive physical variable, such as the potential energy, U, in generalized canonical ensembles to interpolate the interior reverse temperature curve beta S(U) partial derivative S(U)/partial derivative U, where S(U) is the logarithm of the DOS. This curve is computed with different accuracies in different energy regions to capture the dependence of the reverse temperature on U without setting prior grid in the U space. By combining with a U-compression transformation, we decrease the computational complexity from O(N-3/2) in the normal Wang Landau type method to O(N-1/2) in the current algorithm, as the degrees of freedom of system N. The efficiency of the algorithm is demonstrated by applying to Lennard Jones fluids with various N, along with its ability to find different macroscopic states, including metastable states.
关键词Molecular Dynamics Simulations Enhanced Sampling Density Of States Generalized Canonical Ensemble Flat-histogram Ensemble
学科领域Physics
资助者National Natural Science Foundation of China [11175250] ; National Natural Science Foundation of China [11175250] ; Open Project Grant from the State Key Laboratory of Theoretical Physics ; Open Project Grant from the State Key Laboratory of Theoretical Physics ; Hundred of Talents Program in Chinese Academy of Sciences ; Hundred of Talents Program in Chinese Academy of Sciences ; National Natural Science Foundation of China [11175250] ; National Natural Science Foundation of China [11175250] ; Open Project Grant from the State Key Laboratory of Theoretical Physics ; Open Project Grant from the State Key Laboratory of Theoretical Physics ; Hundred of Talents Program in Chinese Academy of Sciences ; Hundred of Talents Program in Chinese Academy of Sciences
DOIhttp://dx.doi.org/10.1007/s11433-015-5690-7
关键词[WOS]DENSITY-OF-STATES ; ALGORITHM
收录类别SCI
语种英语
资助者National Natural Science Foundation of China [11175250] ; National Natural Science Foundation of China [11175250] ; Open Project Grant from the State Key Laboratory of Theoretical Physics ; Open Project Grant from the State Key Laboratory of Theoretical Physics ; Hundred of Talents Program in Chinese Academy of Sciences ; Hundred of Talents Program in Chinese Academy of Sciences ; National Natural Science Foundation of China [11175250] ; National Natural Science Foundation of China [11175250] ; Open Project Grant from the State Key Laboratory of Theoretical Physics ; Open Project Grant from the State Key Laboratory of Theoretical Physics ; Hundred of Talents Program in Chinese Academy of Sciences ; Hundred of Talents Program in Chinese Academy of Sciences
WOS类目Physics, Multidisciplinary
引用统计
文献类型期刊论文
条目标识符http://ir.itp.ac.cn/handle/311006/20884
专题理论物理所2015年知识产出
通讯作者Zhou, X (reprint author), Univ Chinese Acad Sci, Sch Phys Sci, Beijing 100049, Peoples R China.
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GB/T 7714
Xu, S,Zhou, X,Jiang, Y,et al. Fast adaptive flat-histogram ensemble to enhance the sampling in large systems[J]. SCIENCE CHINA-PHYSICS MECHANICS & ASTRONOMY,2015,58(9):590501.
APA Xu, S,Zhou, X,Jiang, Y,Wang, YT,&Zhou, X .(2015).Fast adaptive flat-histogram ensemble to enhance the sampling in large systems.SCIENCE CHINA-PHYSICS MECHANICS & ASTRONOMY,58(9),590501.
MLA Xu, S,et al."Fast adaptive flat-histogram ensemble to enhance the sampling in large systems".SCIENCE CHINA-PHYSICS MECHANICS & ASTRONOMY 58.9(2015):590501.
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