论文标题

对单位球的有效二级优化优化的更严格的结合估计

Tighter Bound Estimation for Efficient Biquadratic Optimization Over Unit Spheres

论文作者

Li, Shigui, Lu, Linzhang, Qiu, Xing, Chen, Zhen, Zeng, Delu

论文摘要

对单位球体的双季度编程是爱因斯坦,Schrödinger和其他人提出的量子力学中的一个基本问题。它已被证明是NP-HARD;因此,必须通过有效的启发式算法(例如块改进方法(BIM))来解决。本文重点介绍了双季度形式的最大化,这导致了一个排名的近似问题,相当于计算M光谱半径及其相应的特征向量。具体而言,我们为非负四阶部分对称(PS)张量提供了M光谱半径的紧密上限,可以将其视为M光谱半径的近似值。此外,我们表明,如果非负四阶PS张量是某些MONOID半群的成员,则可以更有效地获得所提出的上限。此外,作为所提出的上限的扩展,我们为某些四阶PS tensors的M频谱半径及其相应的M-EigenVector提供了精确的溶液。最后,作为拟议结合的应用,我们为具有强椭圆形条件的非发挥弹性M量提供了可实际测试的足够条件。 我们进行了几个数值实验,以证明提出的结果的实用性。结果表明:(a)我们提出的方法可以在几乎没有计算负担的情况下达到M频谱半径的紧密上限,并且(b)如此紧密有效的上限极大地提高了BIM丙二醇的收敛速度,从而使其适用于应用程序中的大型问题。

Bi-quadratic programming over unit spheres is a fundamental problem in quantum mechanics introduced by pioneer work of Einstein, Schrödinger, and others. It has been shown to be NP-hard; so it must be solve by efficient heuristic algorithms such as the block improvement method (BIM). This paper focuses on the maximization of bi-quadratic forms, which leads to a rank-one approximation problem that is equivalent to computing the M-spectral radius and its corresponding eigenvectors. Specifically, we provide a tight upper bound of the M-spectral radius for nonnegative fourth-order partially symmetric (PS) tensors, which can be considered as an approximation of the M-spectral radius. Furthermore, we showed that the proposed upper bound can be obtained more efficiently, if the nonnegative fourth-order PS-tensors is a member of certain monoid semigroups. Furthermore, as an extension of the proposed upper bound, we derive the exact solutions of the M-spectral radius and its corresponding M-eigenvectors for certain classes of fourth-order PS-tensors. Lastly, as an application of the proposed bound, we obtain a practically testable sufficient condition for nonsingular elasticity M-tensors with strong ellipticity condition. We conduct several numerical experiments to demonstrate the utility of the proposed results. The results show that: (a) our proposed method can attain a tight upper bound of the M-spectral radius with little computational burden, and (b) such tight and efficient upper bounds greatly enhance the convergence speed of the BIM-algorithm, allowing it to be applicable for large-scale problems in applications.

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