Jung Yousung, Shao Yihan, Head-Gordon Martin
Department of Chemistry, University of California, Berkeley, California 94720, USA.
J Comput Chem. 2007 Sep;28(12):1953-64. doi: 10.1002/jcc.20590.
The scaled opposite spin Møller-Plesset method (SOS-MP2) is an economical way of obtaining correlation energies that are computationally cheaper, and yet, in a statistical sense, of higher quality than standard MP2 theory, by introducing one empirical parameter. But SOS-MP2 still has a fourth-order scaling step that makes the method inapplicable to very large molecular systems. We reduce the scaling of SOS-MP2 by exploiting the sparsity of expansion coefficients and local integral matrices, by performing local auxiliary basis expansions for the occupied-virtual product distributions. To exploit sparsity of 3-index local quantities, we use a blocking scheme in which entire zero-rows and columns, for a given third global index, are deleted by comparison against a numerical threshold. This approach minimizes sparse matrix book-keeping overhead, and also provides sufficiently large submatrices after blocking, to allow efficient matrix-matrix multiplies. The resulting algorithm is formally cubic scaling, and requires only moderate computational resources (quadratic memory and disk space) and, in favorable cases, is shown to yield effective quadratic scaling behavior in the size regime we can apply it to. Errors associated with local fitting using the attenuated Coulomb metric and numerical thresholds in the blocking procedure are found to be insignificant in terms of the predicted relative energies. A diverse set of test calculations shows that the size of system where significant computational savings can be achieved depends strongly on the dimensionality of the system, and the extent of localizability of the molecular orbitals.
缩放反对称自旋莫勒-普莱塞特方法(SOS-MP2)是一种获取相关能的经济方法,通过引入一个经验参数,它在计算上比标准MP2理论更便宜,并且在统计意义上质量更高。但是SOS-MP2仍然有一个四阶缩放步骤,这使得该方法不适用于非常大的分子系统。我们通过利用展开系数和局部积分矩阵的稀疏性,对占据-虚拟乘积分布进行局部辅助基展开,来降低SOS-MP2的缩放比例。为了利用三指标局部量的稀疏性,我们使用一种分块方案,通过与数值阈值比较,删除给定第三个全局指标的整个零行和零列。这种方法最小化了稀疏矩阵簿记开销,并且在分块后还提供了足够大的子矩阵,以允许高效的矩阵-矩阵乘法。所得算法在形式上是立方缩放的,只需要适度的计算资源(二次内存和磁盘空间),并且在有利的情况下,在我们可以应用它的尺寸范围内显示出有效的二次缩放行为。发现在分块过程中使用衰减库仑度量和数值阈值进行局部拟合相关的误差,就预测的相对能量而言是微不足道的。一系列不同的测试计算表明,可以实现显著计算节省的系统大小强烈依赖于系统的维度以及分子轨道的可定域程度。