Nishikawa Yoshihiko, Michel Manon, Krauth Werner, Hukushima Koji
Department of Basic Science, University of Tokyo, 3-8-1 Komaba, Meguro, Tokyo 153-8902, Japan.
Laboratoire de Physique Statistique, Ecole Normale Supérieure, PSL Research University, UPMC, Université Paris Diderot, CNRS, 24 Rue Lhomond, 75005 Paris, France.
Phys Rev E Stat Nonlin Soft Matter Phys. 2015 Dec;92(6):063306. doi: 10.1103/PhysRevE.92.063306. Epub 2015 Dec 14.
We apply the event-chain Monte Carlo algorithm to the three-dimensional ferromagnetic Heisenberg model. The algorithm is rejection-free and also realizes an irreversible Markov chain that satisfies global balance. The autocorrelation functions of the magnetic susceptibility and the energy indicate a dynamical critical exponent z≈1 at the critical temperature, while that of the magnetization does not measure the performance of the algorithm. We show that the event-chain Monte Carlo algorithm substantially reduces the dynamical critical exponent from the conventional value of z≃2.
我们将事件链蒙特卡罗算法应用于三维铁磁海森堡模型。该算法无拒绝抽样，并且还实现了一个满足全局平衡的不可逆马尔可夫链。磁化率和能量的自相关函数表明，在临界温度下动态临界指数z≈1，而磁化强度的自相关函数无法衡量该算法的性能。我们表明，事件链蒙特卡罗算法将动态临界指数从传统值z≃2大幅降低。
