解决NISQ时代量子器件的量子比特映射问题
Tackling the Qubit Mapping Problem for NISQ-Era Quantum Devices
摘要：
由于很少考虑硬件约束，例如，由于物理量子位之间的连接有限，以启用两个量子位门，因此大多数量子算法不能直接在噪声中间尺度量子（NISQ）设备上执行。需要在编译器中动态地将逻辑量子位重新映射到物理量子位以启用算法中的双量子位门，这引入了额外的操作并且不可避免地降低了算法的保真度。以前的解决方案在寻找这样的重映射遭受高复杂性，初始映射质量差，有限的灵活性和可控性。针对上述缺陷，提出了一种基于SWAP的双向启发式搜索算法SABRE，该算法适用于量子位之间具有任意连接的NISQ器件。通过优化每次搜索尝试，全局优化的初始映射使用一种新的反向遍历技术，引入衰减效应，使整个算法的深度和门的数量之间的权衡，SABRE优于最知名的算法与指数加速和可比或更好的结果在各种基准测试。
英文摘要：
Due to little consideration in the hardware constraints, e.g., limited connections between physical qubits to enable two-qubit gates, most quantum algorithms cannot be directly executed on the Noisy Intermediate-Scale Quantum (NISQ) devices. Dynamically remapping logical qubits to physical qubits in the compiler is needed to enable the two-qubit gates in the algorithm, which introduces additional operations and inevitably reduces the fidelity of the algorithm. Previous solutions in finding such remapping suffer from high complexity, poor initial mapping quality, and limited flexibility and controllability. To address these drawbacks mentioned above, this paper proposes a SWAP-based BidiREctional heuristic search algorithm SABRE, which is applicable to NISQ devices with arbitrary connections between qubits. By optimizing every search attempt,globally optimizing the initial mapping using a novel reverse traversal technique, introducing the decay effect to enable the trade-off between the depth and the number of gates of the entire algorithm, SABRE outperforms the best known algorithm with exponential speedup and comparable or better results on various benchmarks.
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