Dimensionality Reduction of the Complete Bipartite Graph with K Edges Removed for Quantum Walks

Viktoria Koscinski, Chen-Fu Chiang
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引用次数: 1

Abstract

Systematic dimensionality reduction allows for the optimization of quantum search and transport problems on particular graphs. In the past, the Lanczos Algorithm has been used to perform systematic dimensionality reduction on matrices of graphs including the Complete Graph (CG), the CG with symmetry broken, and Complete Multipartite Graphs (CMPGs), including the Complete Bipartite Graph (CBG). We focus on expanding the scope of these reductions to the CBG with symmetry broken in order to allow the optimization of Quantum Walks on this type of graph.We show that similarly to the CG, the Lanczos Algorithm can be expanded to the CBG with broken symmetry, which has k random edges removed with the constraints that no more than one edge per node is removed and that no edges that connect to the solution node are removed. Unlike the CG with broken edges, which, after reduction, has 3 types of nodes and a resulting 3×3 matrix, the CBG with broken edges reduces to a graph with 5 types of nodes, resulting in a reduction from an NxN matrix to a 5×5 matrix. From these results, it may be further explored whether or not the more general CMPG reduction may also be expanded by breaking the graph’s symmetry, and if so, how the dimensions of the reduced matrices will be affected as the number of partitions grows.
量子行走中去K边完全二部图的降维
系统的降维允许在特定图上优化量子搜索和传输问题。在过去,Lanczos算法已经被用于对图的矩阵进行系统的降维,包括完全图(CG)、对称破缺的CG和完全多部图(cmpg),包括完全二部图(CBG)。我们专注于将这些约简的范围扩展到对称破缺的CBG,以便在这种类型的图上优化量子行走。我们表明,与CG类似,Lanczos算法可以扩展到具有破对称的CBG,其中有k个随机边被删除,每个节点不超过一条边被删除,并且没有连接到解节点的边被删除。与边缘破碎的CG不同,边缘破碎的CG经过约简后有3种类型的节点和一个3×3矩阵,而边缘破碎的CBG则约简为一个有5种类型节点的图,从而从NxN矩阵约简为5×5矩阵。从这些结果中,可以进一步探索是否更一般的CMPG约简也可以通过打破图的对称性来扩展,如果是这样,那么随着分区数量的增加,约简矩阵的维数将如何受到影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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