HAIL is a heuristic qubit-mapping algorithm that combines layer-weighted subgraph isomorphism, two-stage SWAP sequence search, and iterative forward-backward refinement to cut inserted SWAP gates by about 20% versus TWP on the B23 benchmark.
Mapping quantum algorithms to multi-core quantum computing architectures
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abstract
Current monolithic quantum computer architectures have limited scalability. One promising approach for scaling them up is to use a modular or multi-core architecture, in which different quantum processors (cores) are connected via quantum and classical links. This new architectural design poses new challenges such as the expensive inter-core communication. To reduce these movements when executing a quantum algorithm, an efficient mapping technique is required. In this paper, a detailed critical discussion of the quantum circuit mapping problem for multi-core quantum computing architectures is provided. In addition, we further explore the performance of a mapping method, which is formulated as a partitioning over time graph problem, by performing an architectural scalability analysis.
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An Efficient Iterative Algorithm for Qubit Mapping via Layer-Weight Assignment and Search Space Reduction
HAIL is a heuristic qubit-mapping algorithm that combines layer-weighted subgraph isomorphism, two-stage SWAP sequence search, and iterative forward-backward refinement to cut inserted SWAP gates by about 20% versus TWP on the B23 benchmark.