Model space quantum Monte Carlo (MSQMC) is an extension of full configuration interaction QMC (FCIQMC) that allows us to calculate quasi-degenerate and excited electronic states by sampling the effective Hamiltonian in the model space. We introduce a novel algorithm based on the state-selective partitioning for the effective Hamiltonian using left eigenvectors to calculate several electronic states simultaneously at much less computational cost than the original MSQMC with the energy dependent partitioning. The sampling of walkers in MSQMC is analyzed in the single reference limit using a stochastic algorithm for higher-order perturbation energies by the analogy of the deterministic case utilizing a full configuration interaction program. We further develop size-consistency corrections of the initiator adaptation (i-MSQMC) in three different ways, i.e. the coupled electron pair approximation, a posteriori, and second-order pertrubative corrections. It is clearly demonstrated that most of the initiator error is originating from the deficiency of proper scaling of correlation energy due to its truncated CI nature of the initiator approximation, and that the greater part of the error can be recovered by the size-consistency corrections developed in this work.
翻译:模型空间量蒙特卡洛(MSQMC)是全配置互动QMC(FCIQMC)的延伸,它使我们能够通过对模型空间中有效的汉密尔顿人进行抽样抽样,计算准降解和兴奋的电子状态。我们采用了基于国家选择性分割的新算法,对有效的汉密尔顿人使用左向导体来同时计算数个电子状态,其计算成本远低于原MSQMC和能源依赖分区的计算成本。MSQMC(MICMC)中行走者的抽样在单一参考限度内分析,使用一种用于较高排序的扰动能量的随机算法,比对确定性案例使用全配置互动程序进行类比。我们进一步以三种不同方式对初始适应(i-MSQMC)进行大小一致的校正,即电对对对对接、后传和第二顺序渗透校正。这清楚地表明,大多数导出错误的起源于因对相关能量进行适当缩放的缺陷,因为其驱动力的CI性质是调高调而导致的CI近似性,而更大的误差部分可以通过这一工程恢复。