Tubman Norm M, Lee Joonho, Takeshita Tyler Y, Head-Gordon Martin, Whaley K Birgitta
University of California, Berkeley, Berkeley, California 94720, USA.
J Chem Phys. 2016 Jul 28;145(4):044112. doi: 10.1063/1.4955109.
Development of exponentially scaling methods has seen great progress in tackling larger systems than previously thought possible. One such technique, full configuration interaction quantum Monte Carlo, is a useful algorithm that allows exact diagonalization through stochastically sampling determinants. The method derives its utility from the information in the matrix elements of the Hamiltonian, along with a stochastic projected wave function, to find the important parts of Hilbert space. However, the stochastic representation of the wave function is not required to search Hilbert space efficiently, and here we describe a highly efficient deterministic method that can achieve chemical accuracy for a wide range of systems, including the difficult Cr2 molecule. We demonstrate for systems like Cr2 that such calculations can be performed in just a few cpu hours which makes it one of the most efficient and accurate methods that can attain chemical accuracy for strongly correlated systems. In addition our method also allows efficient calculation of excited state energies, which we illustrate with benchmark results for the excited states of C2.
指数缩放方法的发展在处理比以前认为可能的更大系统方面取得了巨大进展。一种这样的技术，即全组态相互作用量子蒙特卡罗方法，是一种有用的算法，它允许通过对行列式进行随机采样来实现精确对角化。该方法的效用源于哈密顿量矩阵元中的信息，以及一个随机投影波函数，以找到希尔伯特空间的重要部分。然而，有效地搜索希尔伯特空间并不需要波函数的随机表示，在这里我们描述了一种高效的确定性方法，该方法可以为包括具有挑战性的Cr2分子在内的广泛系统实现化学精度。我们证明，对于像Cr2这样的系统，这样的计算可以在短短几个CPU小时内完成，这使其成为能够为强关联系统实现化学精度的最有效和准确的方法之一。此外，我们的方法还允许对激发态能量进行高效计算，我们用C2激发态的基准结果对此进行了说明。
