A random-sampling method as an efficient alternative to variational Monte Carlo for solving Gutzwiller wavefunctions

被引:1
作者
Zhang, Feng [1 ]
Ye, Zhuo
Yao, Yong-Xin
Wang, Cai-Zhuang
Ho, Kai-Ming
机构
[1] Iowa State Univ, Ames Lab, US DOE, Ames, IA 50011 USA
来源
JOURNAL OF PHYSICS COMMUNICATIONS | 2021年 / 5卷 / 12期
关键词
strongly correlated system; Hubbard model; Gutzwille wavefunction; Variational Monte Carlo; Random sampling; GROUND-STATE PROPERTIES; CORRELATED FERMIONS; HUBBARD-MODEL; TRANSITION; SCHEME;
D O I
10.1088/2399-6528/ac3c32
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
We present a random-sampling (RS) method for evaluating expectation values of physical quantities using the variational approach. We demonstrate that the RS method is computationally more efficient than the variational Monte Carlo method using the Gutzwiller wavefunctions applied on single-band Hubbard models as an example. Non-local constraints can also been easily implemented in the current scheme that capture the essential physics in the limit of strong on-site repulsion. In addition, we extend the RS method to study the antiferromagnetic states with multiple variational parameters for 1D and 2D Hubbard models.
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页数:11
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