Self-consistent RPA and the time-dependent density matrix approach
Self-consistent RPA and the time-dependent density matrix approach
复制标题
自洽 RPA 和时间相关密度矩阵方法
DOI：
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发表时间：
2016
影响因子：
2.7
通讯作者：
M. Tohyama
中科院分区：
文献类型：
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作者：
P. Schuck;M. Tohyama
含时密度矩阵（TDDM）或BBGKY（Bogoliubov，Born，绿色，柯克伍德，Yvon）方法在三体水平上解耦和闭合，以二次形式的两体相关函数找到后者的自然表示。在小振幅极限中，获得耦合到同样扩展的第二RPA的扩展RPA。由于包含两体相关性意味着基态不能是Hartree-Fock态，因此相应的RPA自然升级为先前独立引入的自洽RPA（SCRPA），并且建立在相关基态上。SCRPA保留了标准RPA的所有属性。在精确可解的Lipkin模型和一维Hubbard模型上的应用表明了SCRPA和TDDM的良好性能。
The time-dependent density matrix (TDDM) or BBGKY (Bogoliubov, Born, Green, Kirkwood, Yvon) approach is decoupled and closed at the three-body level in finding a natural representation of the latter in terms of a quadratic form of two-body correlation functions. In the small amplitude limit an extended RPA coupled to an also extended second RPA is obtained. Since including two-body correlations means that the ground state cannot be a Hartree-Fock state, naturally the corresponding RPA is upgraded to Self-Consistent RPA (SCRPA) which was introduced independently earlier and which is built on a correlated ground state. SCRPA conserves all the properties of standard RPA. Applications to the exactly solvable Lipkin and the 1D Hubbard models show good performances of SCRPA and TDDM.