摘要
提出了自优化扩散量子 Monte Carlo差值法 ,这是一个集优化、扩散和相关取样三项技术于一身的 Monte Carlo新算法 .这个算法能够在扩散过程中直接计算两个体系之间的能量差 ,且使计算结果的统计误差达到 10 -5hartree数量级 ,获得相关能达 80 %以上 .应用该方法研究分子势能面 ,使用“刚性移动”模型 ,利用 Jacobi变换使分子两个几何构型的能量计算具有很好的正相关性 ,因而能得到准确的能量差值和分子势能面 .另外 ,我们还首创了“平衡后留样”技术 ,可节省 50 %以上的计算量 .该算法还可应用于分子光谱。
A differential approach for self optimizing diffusion quantum Monte Carlo calculation was proposed in this paper, which is a new algorithm combining with three techniques such as optimizing, diffusion and correlation sampling. This method can directly be used to calculate the energy differential between two systems in the diffusion process, make the statistical error of calculation reduce to the order of 10 -5 hartree, and recover about more than 80% of the correlation energy. We employed this approach to set up a potential energy surface of a molecule, used a 'rigid move' model, and utilized Jacobi transformation to make energy calculation for two configurations of a molecule have a good positive correlation. So, an accurate energy differential could be obtained, and the potential energy surface with a good quality can be depicted. In the calculation, a technique called 'post equilibrium remaining sample' was set up firstly, which can save about 50% of computation expense. This novel algorithm can also be applied to studying other related fields such as molecular spectroscopy and the energy variation in chemical reactions.
出处
《高等学校化学学报》
SCIE
EI
CAS
CSCD
北大核心
1999年第12期1916-1920,共5页
Chemical Journal of Chinese Universities
基金
国家自然科学基金!(批准号:29773036)
湖南省教委科研基金资助课题
关键词
差值论
量子蒙特卡罗法
优化
势能面
能量差值
Differential approach, Quantum Monte Carlo method, Correlation sampling, Potential energy surface
