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Embedding Algorithms for Quantum Annealers with Chimera and Pegasus Connection Topologies

机译:具有Chimera和Pegasus连接拓扑的量子退火器的嵌入算法

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We propose two new algorithms - Spring-Based MinorMiner (SPMM) and Clique-Based MinorMiner (CLMM) - which take as input the connectivity graph of a Quadratic Unconstrained Binary Optimization (QUBO) problem and produce as output an embedding of the input graph on a host graph that models the topology of a quantum computing device. As host graphs, we take the Chimera graph and the Pegasus graph, which are the topology graphs of D-Wave's 2000 qubit (first introduced in 2017) and 5000 qubit (expected 2020) quantum annealer devices, respectively. We evaluate our algorithms on a large set of random graph QUBO inputs (Erdos-Renyi G_(n,p,)Barabasi-Albert and d-regular graphs) on both host topologies against other embedding algorithms. For the Pegasus topology, we find that CLMM outperforms all other algorithms at edge densities larger than 0.08, while SPMM wins at edge densities smaller than 0.08 for Erdos-Renyi graphs, with very similar transition densities for the other graph classes. Surprisingly, the standard D-Wave MinorMiner embedding algorithm-while also getting slightly outperformed by SPMM for sparse and very dense graphs on Chimera - does not manage to extend its overall good performance on Chimera to Pegasus as it fails to embed even medium-density graphs on 175-180 nodes which are known to have clique embeddings on Pegasus.
机译:我们提出了两种新算法-基于Spring的MinorMiner(SPMM)和基于Clique的MinorMiner(CLMM)-将二次无约束二进制优化(QUBO)问题的连通图作为输入,并在输出上生成嵌入的输入图一个对量子计算设备的拓扑进行建模的主机图。作为主体图,我们采用Chimera图和Pegasus图,它们分别是D-Wave的2000量子位(2017年首次推出)和5000量子位(预计2020年)量子退火设备的拓扑图。我们在两种主机拓扑上都针对其他嵌入算法,在大量随机图QUBO输入集(Erdos-Renyi G_(n,p,)Barabasi-Albert和d-正则图)上评估了我们的算法。对于Pegasus拓扑,我们发现对于Erdos-Renyi图,CLMM在边缘密度大于0.08时胜过所有其他算法,而SPMM在Erdos-Renyi图的边缘密度小于0.08时胜出,而其他图类的过渡密度非常相似。令人惊讶的是,标准的D-Wave MinorMiner嵌入算法虽然在Chimera上的稀疏和非常密集的图形上也表现稍逊于SPMM,却无法将其在Chimera上的总体良好性能扩展到Pegasus,因为它甚至无法嵌入中等密度的图形在175-180个节点上,这些节点在Pegasus上有集团嵌入。

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