A Novel Exact Fixed-node Quantum Monte Carlo Algorithm

被引:0
|
作者
Hong Xin HUANG Department of Chemistry
机构
关键词
Self-optimizing; quantum Monte Carlo method; cusp conditions;
D O I
暂无
中图分类号
O641 [结构化学];
学科分类号
070304 ; 081704 ;
摘要
In this paper we proposed a novel exact fixed-node quantum Monte Carlo (EFNQMC) algorithm, which is a self-optimizing and self-improving procedure. In contrast to the previous EFNQMC method, the trial function is optimized synchronistically in the diffusion procedure, but not before the beginning of EFNQMC computation. In order to optimize the trial function, the improved steepest descent technique is used, in which the step size is automatically adjustable. The procedure is quasi-Newton and converges super linearly. We also use a novel trial function, which has correct electron-electron and electron-nucleus cusp conditions. The novel EFNQMC algorithm and the novel trial function are employed to calculate the energies of 11 A1 state of CH2, 1Ag state of C8 and the ground-states of H2, LiH, Li2, H2O, respectively. The test results show that both the novel algorithm and the trial function proposed in the present paper are very excellent.
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页码:501 / 504
页数:4
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