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arxiv: 1811.03358 · v1 · pith:KRPHLQ6Inew · submitted 2018-11-08 · ❄️ cond-mat.stat-mech

Geometric properties of the Fortuin-Kasteleyn representation of the Ising model

classification ❄️ cond-mat.stat-mech
keywords clusterscriticalexponentsgeometricisingmodelsizetilde
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We present a Monte Carlo study of the Fortuin-Kasteleyn (FK) clusters of the Ising model on the square (2D) and simple-cubic (3D) lattices. The wrapping probability, a dimensionless quantity characterizing the topology of the FK clusters on a torus, is found to suffer from smaller finite-size corrections than the well-known Binder ratio, and yields a high-precision critical coupling as $K_c(3\rm D)=0.221\,654\,631(8)$. We then study geometric properties of the FK clusters at criticality. It is demonstrated that the distribution of the critical largest-cluster size $C_1$ follows a single-variable function as $P(C_1,L){\rm d}C_1=\tilde P(x){\rm d}x$ with $x\equiv C_1/L^{d_{\rm F}}$ ($L$ is the linear size), and that the fractal dimension $d_{\rm F}$ is identical to the magnetic exponent. An interesting bimodal feature is observed in distribution $\tilde P(x)$ in 3D, and attributed to the different approaching behaviors for $K \to K_c+0^\pm$. For a critical FK configuration, the cluster number per site $n(s,L)$ of size $s$ is confirmed to obey the standard scaling form $n(s,L)\sim s^{-\tau}\tilde n(s/L^{d_{\rm F}})$, with hyper-scaling relation $\tau=1+d/d_{\rm F}$ and the spatial dimension $d$. To further characterize the compactness of the FK clusters, we measure their graph distances and determine the shortest-path exponents as $d_{\rm min}(3\rm D)=1.259\,4(2)$ and $d_{\rm min}(2\rm D)=1.094\,0(3)$. Further, by excluding all the bridges from the occupied bonds, we obtain bridge-free configurations and determine the backbone exponents as $d_{\rm B}(3\rm D)=2.167\,3(15)$ and $d_{\rm B}(2\rm D)=1.732\,1(4)$. The estimates of the universal wrapping probabilities for the 3D Ising model and of the geometric critical exponents $d_{\rm min}$ and $d_{\rm B}$ either improve over the existing results or have not been reported yet.

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