Improved Fast Randomized Iteration Approach to Full Configuration Interaction
Improved Fast Randomized Iteration Approach to Full Configuration Interaction
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DOI：
10.1021/acs.jctc.0c00437
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发表时间：
2020-09-08
影响因子：
5.5
通讯作者：
Berkelbach, Timothy C.
中科院分区：
文献类型：
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作者：
Greene, Samuel M.;Webber, Robert J.;Berkelbach, Timothy C.
我们对最近引入的全配置交互快速随机迭代方法 (FCI-FRI) 进行了三项修改，并研究了它们对该方法对 Ne、H2O 和 N-2 性能的影响。引发剂近似最初是为全构型相互作用量子蒙特卡罗开发的，当压缩操作中使用少量样本时，显着减少了 FCI-FRI 中的统计误差，使其能够应用于更大的化学系统。半随机扩展涉及在每次压缩中精确保留固定的元素子集，在某些情况下提高了统计效率，但在其他情况下却降低了统计效率。我们还开发了一种新的激励采样方法，可以持续提高统计效率并降低计算成本。我们根据我们的发现讨论了更普遍地提高随机量子化学方法性能的可能策略。
We present three modifications to our recently introduced fast randomized iteration method for full configuration interaction (FCI-FRI) and investigate their effects on the method's performance for Ne, H2O, and N-2. The initiator approximation, originally developed for full configuration interaction quantum Monte Carlo, significantly reduces statistical error in FCI-FRI when few samples are used in compression operations, enabling its application to larger chemical systems. The semistochastic extension, which involves exactly preserving a fixed subset of elements in each compression, improves statistical efficiency in some cases but reduces it in others. We also developed a new approach to sampling excitations that yields consistent improvements in statistical efficiency and reductions in computational cost. We discuss possible strategies based on our findings for improving the performance of stochastic quantum chemistry methods more generally.