论文标题

通过基于使用的中性原子量子体系结构中的基于使用的迁移来减少运行时开销

Reducing Runtime Overhead via Use-Based Migration in Neutral Atom Quantum Architectures

论文作者

Litteken, Andrew, Baker, Jonathan M., Chong, Frederic T.

论文摘要

中性原子是可扩展量子计算体系结构的有前途的选择。诸如长距离互动和本地多码门之类的功能可降低通信成本和运营数量。但是,在计算过程中可能会丢失用作量子位的被困原子,并且由于不利的环境因素。无法恢复丢失的计算值的值,并且需要重新加载计算的数组和重新编译,从而大大增加了电路的运行次数。存在软件缓解策略,但耗尽了电路的原始映射位置,并在整个体系结构上创建了更多的量子群,从而降低了成功的可能性。我们通过制定找到所有可触及量子的策略,而只是相邻的硬件量子台,从而提高了灵活性。其次,我们将架构分为单独的部分,并在每个部分中运行电路,没有丢失的原子。只要架构足够大,这将重置电路,而无需重新加载整个架构。对于利用30%的架构的电路,这将有效镜头的数量增加了两倍。我们还使用这些部分探索了与电路的执行并行化,从而使30个Qubit电路的总运行时间降低了50%。这些技术有助于一系列动态的新策略,以打击丢失的计算空间的有害影响。

Neutral atoms are a promising choice for scalable quantum computing architectures. Features such as long distance interactions and native multiqubit gates offer reductions in communication costs and operation count. However, the trapped atoms used as qubits can be lost over the course of computation and due to adverse environmental factors. The value of a lost computation qubit cannot be recovered and requires the reloading of the array and rerunning of the computation, greatly increasing the number of runs of a circuit. Software mitigation strategies exist but exhaust the original mapped locations of the circuit slowly and create more spread out clusters of qubits across the architecture decreasing the probability of success. We increase flexibility by developing strategies that find all reachable qubits, rather only adjacent hardware qubits. Second, we divide the architecture into separate sections, and run the circuit in each section, free of lost atoms. Provided the architecture is large enough, this resets the circuit without having to reload the entire architecture. This increases the number of effective shots before reloading by a factor of two for a circuit that utilizes 30% of the architecture. We also explore using these sections to parallelize execution of circuits, reducing the overall runtime by a total 50% for 30 qubit circuit. These techniques contribute to a dynamic new set of strategies to combat the detrimental effects of lost computational space.

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