Persistence in q-state Potts model:: A mean-field approach -: art. no. 026115

被引:4
|
作者
Manoj, G [1 ]
机构
[1] Virginia Polytech Inst & State Univ, Dept Phys, Blacksburg, VA 24061 USA
[2] Virginia Polytech Inst & State Univ, Ctr Stochast Proc Sci & Engn, Blacksburg, VA 24061 USA
来源
PHYSICAL REVIEW E | 2003年 / 67卷 / 02期
关键词
D O I
10.1103/PhysRevE.67.026115
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
We study the persistence properties of the T=0 coarsening dynamics of one-dimensional q-state Potts model using a modified mean-field approximation (MMFA). In this approximation, the spatial correlations between the interfaces separating spins with different Potts states is ignored, but the correct time dependence of the mean density P(t) of persistent spins is imposed. For this model, it is known that P(t) follows a power-law decay with time, P(t)similar tot(-theta(q)), where theta(q) is the q-dependent persistence exponent. We study the spatial structure of the persistent region within the MMFA. We show that the persistent site pair correlation function P-2(r,t) has the scaling form P-2(r,t)=P(t)(2)f(r/t(1/2)) for all values of the persistence exponent theta(q). The scaling function has the limiting behavior f(x)similar tox(-2theta) (x<1) and f(x)-->1 (x>1). We then show within the independent interval approximation (IIA) that the distribution n(k,t) of separation k between two consecutive persistent spins at time t has the asymptotic scaling form n(k,t)=t(-2phi)g(t,k/t(phi)), where the dynamical exponent has the form phi=max(1/2,theta). The behavior of the scaling function for large and small values of the arguments is found analytically. We find that for small separations k<t(phi),n(k,t)similar toP(t)k(-tau), where tau=max[2(1-theta),2theta], while for large separations k>t(phi), g(t,x) decays exponentially with x. The unusual dynamical scaling form and the behavior of the scaling function is supported by numerical simulations.
引用
收藏
页数:9
相关论文
共 50 条
  • [41] Glauber Dynamics for the Mean-Field Potts Model
    Cuff, P.
    Ding, J.
    Louidor, O.
    Lubetzky, E.
    Peres, Y.
    Sly, A.
    JOURNAL OF STATISTICAL PHYSICS, 2012, 149 (03) : 432 - 477
  • [42] Spanning forests and the q-state Potts model in the limit q→0
    Jacobsen, JL
    Salas, J
    Sokal, AD
    JOURNAL OF STATISTICAL PHYSICS, 2005, 119 (5-6) : 1153 - 1281
  • [43] Quasistationary trajectories of the mean-field XY Hamiltonian model:: A topological perspective -: art. no. 036148
    Tamarit, FA
    Maglione, G
    Stariolo, DA
    Anteneodo, C
    PHYSICAL REVIEW E, 2005, 71 (03):
  • [44] Glauber Dynamics for the Mean-Field Potts Model
    P. Cuff
    J. Ding
    O. Louidor
    E. Lubetzky
    Y. Peres
    A. Sly
    Journal of Statistical Physics, 2012, 149 : 432 - 477
  • [45] Antiferromagnetic φ4 model.: I.: The mean-field solution -: art. no. 045006
    Branchina, V
    Mohrbach, H
    Polonyi, J
    PHYSICAL REVIEW D, 1999, 60 (04)
  • [46] Spanning Forests and the q-State Potts Model in the Limit q →0
    Jesper Lykke Jacobsen
    Jesús Salas
    Alan D. Sokal
    Journal of Statistical Physics, 2005, 119 : 1153 - 1281
  • [47] The mean-field φ4 model:: Entropy, analyticity, and configuration space topology -: art. no. 056134
    Hahn, I
    Kastner, M
    PHYSICAL REVIEW E, 2005, 72 (05):
  • [48] Thermal operators and cluster topology in the q-state Potts model
    Caselle, M
    Gliozzi, F
    Necco, S
    JOURNAL OF PHYSICS A-MATHEMATICAL AND GENERAL, 2001, 34 (03): : 351 - 355
  • [49] On the phase diagram of the random bond q-state Potts model
    Gesualdo Delfino
    Noel Lamsen
    The European Physical Journal B, 2019, 92
  • [50] Modified q-state Potts model with binarized synaptic coefficients
    Kryzhanovsky, Vladimir
    ARTIFICIAL NEURAL NETWORKS - ICANN 2008, PT II, 2008, 5164 : 72 - 80