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

机译:去除了量子游动的K边缘的完整二部图的降维

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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.
机译:系统降维可优化特定图形上的量子搜索和传输问题。过去,Lanczos算法已用于对包括完全图(CG),对称性破损的CG和完全多部分图(CMPG)(包括完全二部图(CBG))的图矩阵执行系统降维。我们专注于将这些约简的范围扩展到具有对称破损的CBG,以允许对这种类型的图进行量子行走的优化。我们证明,与CG类似,Lanczos算法可以扩展为具有对称破损的CBG ,其中删除了k个随机边,并具有以下限制:每个节点最多只能删除一个边,并且不删除连接到解决方案节点的边。与具有折边的CG不同,在还原之后,它具有3种类型的节点和所得的3×3矩阵,而具有折边的CBG可以简化为具有5种类型的节点的图形,从而从NxN矩阵简化为a 5×5矩阵。从这些结果中,可以进一步探讨是否也可以通过破坏图形的对称性来扩展更通用的CMPG缩减,如果是,则随着分区数量的增加,缩减矩阵的尺寸将受到怎样的影响。

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