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dc.contributor.authorHuang, HX
dc.contributor.authorCao, ZX
dc.contributor.author曹泽星
dc.date.accessioned2012-08-23T00:46:10Z
dc.date.available2012-08-23T00:46:10Z
dc.date.issued1997
dc.identifier.citationSCIENCE IN CHINA SERIES B-CHEMISTRY,1997,40(2):199-204zh_CN
dc.identifier.issn1001-652X
dc.identifier.urihttp://dx.doi.org/doi: 10.1007/BF02876412
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/13555
dc.description.abstractA novel algorithm is proposed for the fixed-node quantum Monte Carlo (FNQMC) method. In contrast to previous procedures, its ''guiding function'' is not optimized prior to diffusion quantum Monte Carlo (DMC) computation but synchronistically in the diffusion process. The new algorithm can not only save CPU time, but also make both of the optimization and diffusion carried out according to the same sampling fashion, reaching the goal to improve each other. This new optimizing procedure converges super-linearly, and thus can accelerate the particle diffusion. During the diffusion process, the node of the ''guiding function'' changes incessantly, which is conducible to reducing the ''fixed-node error''. The new algorithm has been used to calculate the total energies of states X(3)B(1) and a(1)A(1) of CH2 as well as pi-X(2)B(1) and sigma-(2)A(1) of NH2. The singlet-triplet energy splitting (Delta E(S . T)) in CH2 and sigma-pi energy splitring Delta E(sigma .pi) in NH2 obtained with this present method are (45.542+/-1.840) and (141.644+/-1.589) kJ/mol, respectively. The calculated results show that the novel algorthm is much superior to the conventional fixed-node quantum Monte Carlo in accuracy, statistical error and computational cost.zh_CN
dc.language.isoenzh_CN
dc.publisherSCIENCE CHINA PRESSzh_CN
dc.subjectfixed-node quantum Monte Carlozh_CN
dc.subjectdiffusion processzh_CN
dc.subjectguiding functionzh_CN
dc.subjectsuper-linear convergencezh_CN
dc.titleA new algorithm for the fixed-node quantum Monte Carlo methodzh_CN
dc.typeArticlezh_CN


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