ATOM: An Efficient Topology Adaptive Algorithm for Minor Embedding in Quantum Computing

• URL: http://arxiv.org/abs/2307.01843v1
• Date: Tue, 4 Jul 2023 17:45:07 GMT
• Title: ATOM: An Efficient Topology Adaptive Algorithm for Minor Embedding in Quantum Computing
• Authors: Hoang M. Ngo, Tamer Kahveci, My T. Thai
• Abstract summary: We introduce a novel notion of adaptive topology which is an expandable subgraph of the hardware graph. ATOM iteratively selects a node from the logical graph, and embeds it to the adaptive topology of the hardware graph. Our experimental results show that ATOM is able to provide a feasible embedding in much smaller running time than that of the state-of-the-art.
• Score: 18.594343052664335
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum annealing (QA) has emerged as a powerful technique to solve optimization problems by taking advantages of quantum physics. In QA process, a bottleneck that may prevent QA to scale up is minor embedding step in which we embed optimization problems represented by a graph, called logical graph, to Quantum Processing Unit (QPU) topology of quantum computers, represented by another graph, call hardware graph. Existing methods for minor embedding require a significant amount of running time in a large-scale graph embedding. To overcome this problem, in this paper, we introduce a novel notion of adaptive topology which is an expandable subgraph of the hardware graph. From that, we develop a minor embedding algorithm, namely Adaptive TOpology eMbedding (ATOM). ATOM iteratively selects a node from the logical graph, and embeds it to the adaptive topology of the hardware graph. Our experimental results show that ATOM is able to provide a feasible embedding in much smaller running time than that of the state-of-the-art without compromising the quality of resulting embedding.

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