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

Author(s):  
Feng Zhang ◽  
Zhuo Ye ◽  
Yong-Xin Yao ◽  
Cai-Zhuang Wang ◽  
Kai-Ming Ho

Abstract 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.

2016 ◽  
Vol 94 (5) ◽  
pp. 501-506 ◽  
Author(s):  
Salah B. Doma ◽  
Fatma N. El-Gammal ◽  
Asmaa A. Amer

The ground state energy of hydrogen molecular ion [Formula: see text] confined by a hard prolate spheroidal cavity is calculated. The case in which the nuclear positions are clamped at the foci is considered. Our calculations are based on using the variational Monte Carlo method with an accurate trial wave function depending on many variational parameters. The results were extended to also include the HeH++ molecular ion. The obtained results are in good agreement with the most recent results.


2018 ◽  
Author(s):  
A. D. Oliveira ◽  
T. P. Filomena

We briefly discuss the differences among several methods to generate a scenario tree for stochastic optimization. First, the Monte Carlo Random sampling is presented, followed by the Fitting of the First Two Moments sampling, and lastly the Michaud sampling. Literature results are reviewed, taking into account distinctive features of each kind of methodology. According to the literature results, it is fundamental to consider the problem’s unique characteristics to make the more appropriate choice on sampling method.  


2019 ◽  
Vol 235 ◽  
pp. 447-462 ◽  
Author(s):  
Takahiro Misawa ◽  
Satoshi Morita ◽  
Kazuyoshi Yoshimi ◽  
Mitsuaki Kawamura ◽  
Yuichi Motoyama ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document