scholarly journals Aperiodic Non-Isomorphic Lattices with Equivalent Percolation and Random-Cluster Models

10.37236/320 ◽  
2010 ◽  
Vol 17 (1) ◽  
Author(s):  
Klas Markström ◽  
John C. Wierman

We explicitly construct an uncountable class of infinite aperiodic plane graphs which have equal, and explicitly computable, bond percolation thresholds. Furthermore for both bond percolation and the random-cluster model all large scale properties, such as the values of the percolation threshold and the critical exponents, of the graphs are equal. This equivalence holds for all values of $p$ and all $q\in[0,\infty]$ for the random-cluster model. The graphs are constructed by placing a copy of a rotor gadget graph or its reflection in each hyperedge of a connected self-dual 3-uniform plane hypergraph lattice. The exact bond percolation threshold may be explicitly determined as the root of a polynomial by using a generalised star-triangle transformation. Related randomly oriented models share the same bond percolation threshold value.


2006 ◽  
Vol 51 (15) ◽  
pp. 3091-3096 ◽  
Author(s):  
Z.D. Wei ◽  
H.B. Ran ◽  
X.A. Liu ◽  
Y. Liu ◽  
C.X. Sun ◽  
...  


2016 ◽  
Vol 681 ◽  
pp. 012014
Author(s):  
Martin Weigel ◽  
Eren Metin Elci ◽  
Nikolaos G. Fytas


2019 ◽  
Vol 30 (02n03) ◽  
pp. 1950009
Author(s):  
Hai Lin ◽  
Jingcheng Wang

In this paper, we develop an analytical framework and analyze the percolation properties of a random network by introducing statistical physics method. To adequately apply the statistical physics method on the research of a random network, we establish an exact mapping relation between a random network and Ising model. Based on the mapping relation and random cluster model (RCM), we obtain the partition function of the random network and use it to compute the size of the giant component and the critical value of the present probability. We extend this approach to investigate the size of remaining giant component and the critical phenomenon in the random network which is under a certain random attack. Numerical simulations show that our approach is accurate and effective.



2011 ◽  
Vol 852 (1) ◽  
pp. 149-173 ◽  
Author(s):  
Gesualdo Delfino ◽  
Jacopo Viti


2007 ◽  
Vol 75 (2) ◽  
pp. 273-273
Author(s):  
Olle Häggström


2009 ◽  
Vol 80 (3) ◽  
Author(s):  
Youjin Deng ◽  
Xiaofeng Qian ◽  
Henk W. J. Blöte


2016 ◽  
Vol 64 (8) ◽  
pp. 3563-3575 ◽  
Author(s):  
Xuesong Cai ◽  
Xuefeng Yin ◽  
Xiang Cheng ◽  
Antonio Perez Yuste


Physica ◽  
1972 ◽  
Vol 58 (3) ◽  
pp. 393-418 ◽  
Author(s):  
C.M. Fortuin


2017 ◽  
Vol 170 (1) ◽  
pp. 22-61 ◽  
Author(s):  
Andrea Collevecchio ◽  
Eren Metin Elçi ◽  
Timothy M. Garoni ◽  
Martin Weigel


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