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An intertwined method for making low-rank sum-of-product basis functions that makes it possible to compute vibrational spectra of molecules with more than 10 atoms

机译:一种用于生成低秩乘积和基函数的方法可以计算具有10个以上原子的分子的振动光谱

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摘要

We propose a method for solving the vibrational Schrödinger equation with which one can compute spectra for molecules with more than ten atoms. It uses sum-of-product (SOP) basis functions stored in a canonical polyadic tensor format and generated by evaluating matrix-vector products. By doing a sequence of partial optimizations, in each of which the factors in a SOP basis function for a single coordinate are optimized, the rank of the basis functions is reduced as matrix-vector products are computed. This is better than using an alternating least squares method to reduce the rank, as is done in the reduced-rank block power method. Partial optimization is better because it speeds up the calculation by about an order of magnitude and allows one to significantly reduce the memory cost. We demonstrate the effectiveness of the new method by computing vibrational spectra of two molecules, ethylene oxide (C2H4O) and cyclopentadiene (C5H6), with 7 and 11 atoms, respectively.
机译:我们提出了一种解决振动Schrödinger方程的方法,利用该方法可以计算具有十个以上原子的分子的光谱。它使用以标准多态张量格式存储并通过评估矩阵向量乘积生成的乘积和(SOP)基函数。通过执行一系列局部优化,在每个优化中,针对单个坐标的SOP基函数中的因子都得到了优化,随着计算矩阵向量乘积,基函数的秩降低了。这好于使用降级最小二乘方法来降低等级(如降低等级的块功率方法中所做的那样)。局部优化更好,因为它可以将计算速度提高一个数量级,并可以显着降低内存成本。我们通过计算两个分子(分别具有7和11个原子)的环氧乙烷(C2H4O)和环戊二烯(C5H6)的振动光谱来证明该新方法的有效性。

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