GREEN FUNCTION MONTE CARLO WITH STOCHASTIC RECONFIGURATION
GREEN FUNCTION MONTE CARLO WITH STOCHASTIC RECONFIGURATION
复制标题
DOI：
10.1103/physrevlett.80.4558
复制
发表时间：
1998-03
影响因子：
8.6
通讯作者：
S. Sorella
中科院分区：
文献类型：
--
作者：
S. Sorella
提出了一种新的方法来稳定格林函数蒙特卡罗技术中的符号问题。该方法是为实格哈密顿量设计的，基于迭代“随机重构”方案，该方案引入了一些偏差，但允许具有恒定符号的稳定模拟。系统地减少这种偏差原则上是可能的。该方法应用于受挫 J1-J2 海森堡模型，并针对精确对角化数据进行测试。在热力学极限中发现了 J2/J1 >~ 0.4 有限自旋间隙的证据。
A new method for the stabilization of the sign problem in the Green Function Monte Carlo technique is proposed. The method is devised for real lattice Hamiltonians and is based on an iterative ''stochastic reconfiguration'' scheme which introduces some bias but allows a stable simulation with constant sign. The systematic reduction of this bias is in principle possible. The method is applied to the frustrated J1-J2 Heisenberg model, and tested against exact diagonalization data. Evidence of a finite spin gap for J2/J1 >~ 0.4 is found in the thermodynamic limit.