scholarly journals Parallelization of the Wolff single-cluster algorithm

2010 ◽  
Vol 81 (2) ◽  
Author(s):  
J. Kaupužs ◽  
J. Rimšāns ◽  
R. V. N. Melnik
1994 ◽  
Vol 05 (01) ◽  
pp. 1-14 ◽  
Author(s):  
N. ITO ◽  
G.A. KOHRING

A comparison between single-cluster and single-spin algorithms is made for the Ising model in 2 and 3 dimensions. We compare the amount of computer time needed to achieve a given level of statistical accuracy, rather than the speed in terms of site updates per second or the dynamical critical exponents. Our main result is that the cluster algorithms become more efficient when the system size, Ld, exceeds, L~70–300 for d=2 and l~80–200 for d=3. The exact value of the crossover is dependent upon the computer being used. The lower end of the crossover range is typical of workstations while the higher end is typical of vector computers. Hence, even for workstations, the system sizes needed for efficient use of the cluster algorithm is relatively large.


1998 ◽  
Vol 09 (06) ◽  
pp. 861-865
Author(s):  
P. R. A. Campos ◽  
R. N. Onody

Here we apply the Wolff single-cluster algorithm to the site-bond-correlated Ising model and study its critical dynamical behavior. We have verified that the autocorrelation time diminishes in the presence of dilution and correlation, showing that the Wolff algorithm performs even better in such situations. The critical dynamical exponents are also estimated.


1997 ◽  
Vol 56 (22) ◽  
pp. 14529-14532 ◽  
Author(s):  
P. R. A. Campos ◽  
R. N. Onody

1995 ◽  
Vol 06 (02) ◽  
pp. 197-210 ◽  
Author(s):  
S. BAE ◽  
S.H. KO ◽  
P.D. CODDINGTON

The Wolff single-cluster algorithm is the most efficient method known for Monte Carlo simulation of many spin models. Due to the irregular size, shape and position of the Wolff clusters, this method does not easily lend itself to efficient parallel implementation, so that simulations using this method have thus far been confined to workstations and vector machines. Here we present two parallel implementations of this algorithm, and show that one gives fairly good performance on a MIMD parallel computer.


2021 ◽  
Vol 103 (5) ◽  
Author(s):  
Hanqing Liu ◽  
Shailesh Chandrasekharan ◽  
Ribhu K. Kaul

Catalysts ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 974
Author(s):  
Bing Han ◽  
Haihong Meng ◽  
Fengyu Li ◽  
Jingxiang Zhao

Under the current double challenge of energy and the environment, an effective nitrogen reduction reaction (NRR) has become a very urgent need. However, the largest production of ammonia gas today is carried out by the Haber–Bosch process, which has many disadvantages, among which energy consumption and air pollution are typical. As the best alternative procedure, electrochemistry has received extensive attention. In this paper, a catalyst loaded with Fe3 clusters on the two-dimensional material C2N (Fe3@C2N) is proposed to achieve effective electrochemical NRR, and our first-principles calculations reveal that the stable Fe3@C2N exhibits excellent catalytic performance for electrochemical nitrogen fixation with a limiting potential of 0.57 eV, while also suppressing the major competing hydrogen evolution reaction. Our findings will open a new door for the development of non-precious single-cluster catalysts for effective nitrogen reduction reactions.


2007 ◽  
Vol 189 (21) ◽  
pp. 7841-7855 ◽  
Author(s):  
Angeliki Mavroidi ◽  
David M. Aanensen ◽  
Daniel Godoy ◽  
Ian C. Skovsted ◽  
Margit S. Kaltoft ◽  
...  

ABSTRACT Streptococcus pneumoniae (the pneumococcus) produces 1 of 91 capsular polysaccharides (CPS) that define the serotype. The cps loci of 88 pneumococcal serotypes whose CPS is synthesized by the Wzy-dependent pathway were compared with each other and with additional streptococcal polysaccharide biosynthetic loci and were clustered according to the proportion of shared homology groups (HGs), weighted for the sequence similarities between the genes encoding the shared HGs. The cps loci of the 88 pneumococcal serotypes were distributed into eight major clusters and 21 subclusters. All serotypes within the same serogroup fell into the same major cluster, but in six cases, serotypes within the same serogroup were in different subclusters and, conversely, nine subclusters included completely different serotypes. The closely related cps loci within a subcluster were compared to the known CPS structures to relate gene content to structure. The Streptococcus oralis and Streptococcus mitis polysaccharide biosynthetic loci clustered within the pneumococcal cps loci and were in a subcluster that also included the cps locus of pneumococcal serotype 21, whereas the Streptococcus agalactiae cps loci formed a single cluster that was not closely related to any of the pneumococcal cps clusters.


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