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Order-N cluster Monte Carlo method for spin systems with long-range interactions

JOURNAL OF COMPUTATIONAL PHYSICS 2009年第7期228卷 2629-2642页

作者： Fukui, Kouki Todo, Synge Univ Tokyo Dept Appl Phys Tokyo 1138656 Japan Japan Sci & Technol Agcy CREST Kawaguchi Saitama 3320012 Japan

An efficient O(N) cluster Monte Carlo method for Ising models with long-range interactions is presented. Our novel algorithm does not introduce any cutoff for interaction range and thus it strictly fulfills the detailed balance. The realized stochastic dynamics is equivalent to that of the conventional Swendsen-Wang algorithm, which requires O(N-2) operations per Monte Carlo sweep if applied to long-range interacting models. In addition, it is shown that the total energy and the specific heat can also be measured in O(N) time. We demonstrate the efficiency of our algorithm over the conventional method and the O(N log N) algorithm by Luijten and Blote. We also apply our algorithm to the classical and quantum Ising chains with inverse-square ferromagnetic interactions, and confirm in a high accuracy that a Kosterlitz-Thouless phase transition, associated with a universal jump in the magnetization, occurs in both cases. (C) 2008 Elsevier Inc. All rights reserved.

关键词： Long-range interaction cluster algorithm O(N) method Ising model Quantum Monte Carlo Kosterlitz-Thouless transition

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Geometric symmetries and cluster simulations

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PHYSICA A 1998年第1-2期254卷 156-163页

作者： Heringa, JR Blote, HWJ Delft Univ Technol Fac Appl Phys NL-2600 GA Delft Netherlands

cluster Monte Carlo methods are especially useful for applications in the vicinity of phase transitions, because they suppress critical slowing down;this may reduce the required simulation times by orders of magnitude. In general, the way in which cluster methods work can be explained in terms of global symmetry properties of the simulated model. In the case of the Swendsen-Wang and related algorithms for the Ising model, this symmetry is the plus-minus spin symmetry;therefore, these methods are not directly applicable in the presence of a magnetic field. More generally, in the case of the Potts model, the Swendsen-Wang algorithm relies on the permutation symmetry of the Potts states. However, other symmetry properties can also be employed for the formulation of cluster algorithms. Besides of the spin symmetries, one can use geometric symmetries of the lattice carrying the spins. Thus, new cluster simulation methods are realized for a number of models. This geometric method enables the investigation of models that have thus far remained outside the reach of cluster algorithms. Here, we present some simulation results for lattice gases, and for an Ising model at constant magnetization. This cluster method is also applicable to the Blume-Capel model, including its tricritical point. (C) 1998 Elsevier Science B.V. All rights reserved.

关键词： lattice gas universality cluster algorithm

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Dynamics of cluster structure in financial correlation matrix

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CHAOS SOLITONS & FRACTALS 2017年 104卷 835-840页

作者： Nie, Chun-Xiao East China Univ Sci & Technol Sch Business Dept Finance Shanghai 200237 Peoples R China

The correlation dimensions in the financial market are calculated and used as a measure to study the cluster structure in the correlation coefficient matrix. First, based on the existing model, we present a toy model. Using the model-generated data, we find that the clearer cluster structure corresponds to a smaller dimension. It implies that the correlation dimension can be used as a measure of the cluster structure in the correlation coefficient matrix. Finally, we use the algorithm to compute the clusters in the real market and verify the previous empirical evidence. The results show that the cluster structure in the financial correlation coefficient matrix may change with time. The correlation dimension is smaller after the financial crisis, indicating that the cluster structure is clearer after the financial crisis. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Correlation dimension cluster algorithm Financial network Financial crisis Correlation coefficient matrix

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Computational cluster validation for microarray data analysis: experimental assessment of Clest, Consensus clustering, Figure of Merit, Gap Statistics and Model Explorer

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BMC BIOINFORMATICS 2008年第1期9卷 1-19页

作者： Giancarlo, Raffaele Scaturro, Davide Utro, Filippo Univ Palermo Dipartimento Matemat & Applicaz I-90123 Palermo Italy

Background: Inferring cluster structure in microarray datasets is a fundamental task for the so-called -omic sciences. It is also a fundamental question in Statistics, Data Analysis and Classification, in particular with regard to the prediction of the number of clusters in a dataset, usually established via internal validation measures. Despite the wealth of internal measures available in the literature, new ones have been recently proposed, some of them specifically for microarray data. Results: We consider five such measures: Clest, Consensus (Consensus clustering), FOM (Figure of Merit), Gap (Gap Statistics) and ME (Model Explorer), in addition to the classic WCSS (Within cluster Sum-of-Squares) and KL (Krzanowski and Lai index). We perform extensive experiments on six benchmark microarray datasets, using both Hierarchical and K-means clustering algorithms, and we provide an analysis assessing both the intrinsic ability of a measure to predict the correct number of clusters in a dataset and its merit relative to the other measures. We pay particular attention both to precision and speed. Moreover, we also provide various fast approximation algorithms for the computation of Gap, FOM and WCSS. The main result is a hierarchy of those measures in terms of precision and speed, highlighting some of their merits and limitations not reported before in the literature. Conclusion: Based on our analysis, we draw several conclusions for the use of those internal measures on microarray data. We report the main ones. Consensus is by far the best performer in terms of predictive power and remarkably algorithm-independent. Unfortunately, on large datasets, it may be of no use because of its nontrivial computer time demand (weeks on a state of the art PC). FOM is the second best performer although, quite surprisingly, it may not be competitive in this scenario: it has essentially the same predictive power of WCSS but it is from 6 to 100 times slower in time, depending on the dat

关键词： cluster algorithm Null Model cluster Solution Good Performer Gold Solution

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cluster methods for Ising systems with fields

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INTERNATIONAL JOURNAL OF MODERN PHYSICS C 1999年第8期10卷 1427-1432页

作者： Machta, J Univ Massachusetts Dept Phys & Astron Amherst MA 01002 USA

Efficient cluster algorithms for Ising systems with fields are described. cluster are grown between two replicas of the system in the same field. As is the case for other successful cluster approaches, the critical po... 详细信息

关键词： Ising model cluster algorithm replica exchange model

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cluster-based content caching driven by popularity prediction

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CCF TRANSACTIONS ON HIGH PERFORMANCE COMPUTING 2022年第3期4卷 357-366页

作者： Jia, Bosen Li, Ruibin Wang, Chenyang Qiu, Chao Wang, Xiaofei Tianjin Univ Tianjin Int Engn Inst 92 Weijin Rd Tianjin 300072 Peoples R China Tianjin Univ Coll Intelligence & Comp 92 Weijin Rd Tianjin 300072 Peoples R China

This paper introduces a novel cache replacement strategy, named cluster-Based Content Caching (CBCC). CBCC extracts the content feature and uses it to predict popularity for cache replacement. The prediction of expected popularity of new content is based on the clustering algorithm dynamically. If the content is not in the cache list and the list is full, CBCC can help the Cache Node (CN) to make smarter decisions about whether cache new content or not and which content will be replaced based on a popularity prior queue, intending to increase the number of cache hitting in the near future. This strategy can reduce the pressure on the backbone and further improve user satisfaction. We evaluate the performance of our algorithm based on an open Douban Movie Comment Dataset. This dataset can be used to simulate users' requests. Simulation results show the feasibility and effectiveness of the proposed algorithm.

关键词： Content caching cluster algorithm Popularity prediction K-means

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STUDY OF THE 3-DIMENSIONAL ISING-MODEL ON FILM GEOMETRY WITH THE cluster MONTE-CARLO METHOD

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JOURNAL OF STATISTICAL PHYSICS 1993年第1-2期73卷 293-317页

作者： RUGE, C DUNKELMANN, S WAGNER, F WULF, J 1. Institut für Theoretische Physik und Sternwarte Universit?t Kiel D-2300 Kiel Germany

Topological properties of clusters are used to extract critical parameters. This method is tested for the bulk properties of d = 2 percolation and the d = 2, 3 Ising model. For the latter we obtain an accurate value of the critical temperature J/k(B) T(c) = 0.221617(18). In the case of the d = 3 Ising model with film geometry the critical value of the surface coupling at the special transitions is determined as J(1c)/J = 1.5004(20) together with the critical exponents beta1m=0.237(5) and phi=0.461(15).

关键词： D = 3 ISING MODEL cluster algorithm CRITICAL TEMPERATURE FINITE-SIZE SCALING SURFACE-RELATED CRITICAL EXPONENTS

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cluster Based Dynamic Routing On Powerline Carrier Network

Cluster Based Dynamic Routing On Powerline Carrier Network

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5th International Conference on Wireless Communications, Networking and Mobile Computing

作者： Hong Li Wang Kensheng Li Shurong Zou Weixia Zhou Zheng China Univ Petr Coll Comp & Commun Engn Dongying 257061 Shandong Peoples R China Beijing Univ Posts & Telecommun Coll Telecommun Engn Beijing 100876 Peoples R China

ISBN: (纸本)9781424436927

Topology of power line carrier network (PLCN) is complex, fast changeable and its channel is time-variant. To enhance the availability and effectiveness of network communication, a cluster based dynamic routing algorithm (CBDR) is proposed in the paper. The algorithm adopts clustering based on root tree and local traversal in order to construct and maintain the dynamic routes according to trees topology, uncertain nodes and the characteristics of power line carrier network, it also adjusts effective communication distance to simplify route. The simulation shows that CBDR using in PLCN is available, it reduces network construction time and maintains the routes effectively. It makes routes of PLCN stabile and flexible. At last the conclusion is made for the further study.

关键词： Powerline carrier network cluster algorithm dynamic route tree-topology

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A Novel Application Layer DDoS Detecting Method Based on cluster Method 9

A Novel Application Layer DDoS Detecting Method Based on Clu...

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9th IEEE International Conference on Software Engineering and Service Science (ICSESS)

作者： Wang, Jin Li, Zhongwen Zhou, Xiaoxue Yang, Jianyu Shi, Feng Miao, Fang Chengdu Univ Sch Informat Sci & Technol Chengdu 610106 Sichuan Peoples R China Chengdu Univ Inst Big Data Chengdu 610106 Sichuan Peoples R China

ISBN: (纸本)9781538665657

Application layer DDoS attack challenges web applications seriously. It launches attack by sending a large number of HTTP Get requests to a web server. The anomaly based method is a promising method, which detects the DDoS attack by comparing the individual surfing behavior with a reference surfing-behavior profile. Yet due to the exist of noisy web logs caused by web-crawling, it is difficult to build robust reference profile for detection. This paper proposes a novel anomaly-based application DDoS detection scheme base on clustering method Our method could tolerate the web crawling traces in building reference surfing profile, and can detect different Application layer DDoS attack (e.g., repetitively getting several webpages, randomly getting webpages following hyper-lmks etc.). The simulation results show that our method can detect application layer DDoS attacks accurately.

关键词： IP network DDoS Relative Entropy cluster algorithm Virtual Assets

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cluster MONTE-CARLO algorithmS IN STATISTICAL-MECHANICS

CLUSTER MONTE-CARLO ALGORITHMS IN STATISTICAL-MECHANICS

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WORKSHOP ON FERMION algorithmS

作者： WANG, JS

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