Institute for Solid State Physics, University of Tokyo, Chiba, Japan 277-8581.
Graduate School of Engineering, University of Hyogo, Himeji, Japan 671-2280.
Phys Rev Lett. 2014 Apr 11;112(14):140603. doi: 10.1103/PhysRevLett.112.140603. Epub 2014 Apr 10.
Based on the worm algorithm in the path-integral representation, we propose a general quantum Monte Carlo algorithm suitable for parallelizing on a distributed-memory computer by domain decomposition. Of particular importance is its application to large lattice systems of bosons and spins. A large number of worms are introduced and its population is controlled by a fictitious transverse field. For a benchmark, we study the size dependence of the Bose-condensation order parameter of the hard-core Bose-Hubbard model with L×L×βt=10240×10240×16, using 3200 computing cores, which shows good parallelization efficiency.
基于路径积分表示中的蠕虫算法,我们提出了一种通用的量子蒙特卡罗算法,通过域分解适合在分布式内存计算机上并行化。特别重要的是它在玻色子和自旋的大晶格系统中的应用。引入了大量的蠕虫,并通过虚构的横向场来控制其种群。作为基准,我们使用 3200 个计算核心研究了 L×L×βt=10240×10240×16 的硬芯玻色-哈伯德模型的玻色凝聚阶参数的大小依赖性,显示出良好的并行化效率。