ITP OpenIR  > 理论物理所2017年知识产出
Irreversible Markov chain Monte Carlo algorithm for self-avoiding walk
Hu, H; Chen, XS; Deng, YJ; Deng, YJ (reprint author), Univ Sci & Technol China, Natl Lab Phys Sci Microscale, Hefei 230026, Peoples R China.; Deng, YJ (reprint author), Univ Sci & Technol China, Dept Modern Phys, Hefei 230026, Peoples R China.; Deng, YJ (reprint author), Chinese Acad Sci, Inst Theoret Phys, State Key Lab Theoret Phys, Beijing 100190, Peoples R China.
2017
发表期刊FRONTIERS OF PHYSICS
卷号12期号:1页码:120503
文章类型Article
摘要We formulate an irreversible Markov chain Monte Carlo algorithm for the self-avoiding walk (SAW), which violates the detailed balance condition and satisfies the balance condition. Its performance improves significantly compared to that of the Berretti-Sokal algorithm, which is a variant of the Metropolis-Hastings method. The gained efficiency increases with spatial dimension (D), from approximately 1 0 times in 2D to approximately 4 0 times in 5D. We simulate the SAW on a 5D hyper-cubic lattice with periodic boundary conditions, for a linear system with a size up to L = 128, and confirm that as for the 5D Ising model, the finite-size scaling of the SAW is governed by renormalized exponents, nu* = 2/d and gamma/nu* = d/2. The critical point is determined, which is approximately 8 times more precise than the best available estimate.
关键词Monte Carlo Algorithms Self-avoiding Walk Irreversible Balance Condition
学科领域Physics
资助者National Natural Science Foundation of China [11275185, 11625522] ; National Natural Science Foundation of China [11275185, 11625522] ; Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China [Y5KF191CJ1] ; Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China [Y5KF191CJ1] ; Ministry of Education (of China) for the Fundamental Research Funds for the Central Universities [2340000034] ; Ministry of Education (of China) for the Fundamental Research Funds for the Central Universities [2340000034] ; National Natural Science Foundation of China [11275185, 11625522] ; National Natural Science Foundation of China [11275185, 11625522] ; Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China [Y5KF191CJ1] ; Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China [Y5KF191CJ1] ; Ministry of Education (of China) for the Fundamental Research Funds for the Central Universities [2340000034] ; Ministry of Education (of China) for the Fundamental Research Funds for the Central Universities [2340000034]
DOIhttp://dx.doi.org/10.1007/s11467-016-0646-6
关键词[WOS]SIMULATIONS ; POLYMERS
语种英语
资助者National Natural Science Foundation of China [11275185, 11625522] ; National Natural Science Foundation of China [11275185, 11625522] ; Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China [Y5KF191CJ1] ; Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China [Y5KF191CJ1] ; Ministry of Education (of China) for the Fundamental Research Funds for the Central Universities [2340000034] ; Ministry of Education (of China) for the Fundamental Research Funds for the Central Universities [2340000034] ; National Natural Science Foundation of China [11275185, 11625522] ; National Natural Science Foundation of China [11275185, 11625522] ; Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China [Y5KF191CJ1] ; Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China [Y5KF191CJ1] ; Ministry of Education (of China) for the Fundamental Research Funds for the Central Universities [2340000034] ; Ministry of Education (of China) for the Fundamental Research Funds for the Central Universities [2340000034]
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/311006/22138
专题理论物理所2017年知识产出
通讯作者Deng, YJ (reprint author), Univ Sci & Technol China, Natl Lab Phys Sci Microscale, Hefei 230026, Peoples R China.; Deng, YJ (reprint author), Univ Sci & Technol China, Dept Modern Phys, Hefei 230026, Peoples R China.; Deng, YJ (reprint author), Chinese Acad Sci, Inst Theoret Phys, State Key Lab Theoret Phys, Beijing 100190, Peoples R China.
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GB/T 7714
Hu, H,Chen, XS,Deng, YJ,et al. Irreversible Markov chain Monte Carlo algorithm for self-avoiding walk[J]. FRONTIERS OF PHYSICS,2017,12(1):120503.
APA Hu, H,Chen, XS,Deng, YJ,Deng, YJ ,Deng, YJ ,&Deng, YJ .(2017).Irreversible Markov chain Monte Carlo algorithm for self-avoiding walk.FRONTIERS OF PHYSICS,12(1),120503.
MLA Hu, H,et al."Irreversible Markov chain Monte Carlo algorithm for self-avoiding walk".FRONTIERS OF PHYSICS 12.1(2017):120503.
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