通过动态调整量子比特精度，同时提升性能、加速收敛并提高系统吞吐量。
Three Birds with One Stone: Improving Performance, Convergence, and System Throughput with Nest
- 动态调节量子电路中各量子比特的精度分布，优化执行过程。
- 相比固定精度策略，收敛速度更快，最终结果更接近最优值。
- 支持多任务并发运行，显著提升量子计算机整体利用率。
变分量子算法（VQAs）有望在近中期量子计算机上展示量子优势。然而，这些算法通常仅在高保真度量子比特和设备上运行以追求最佳性能，导致系统吞吐量低。近期研究发现，可在初期使用低保真度量子比特运行VQA，后期再切换至高保真度设备，仍可获得良好性能。本文提出Nest技术，通过在运行过程中精心调控VQA的量子比特保真度分布，不仅（1）提升算法性能（接近最优结果），还（2）实现更快收敛。此外，利用Nest可将多个VQA任务共置于同一台设备上并发执行，从而（3）显著提高系统吞吐量，实现性能、收敛速度与系统效率三者的协同优化。
原文摘要 · Abstract (English)
Variational quantum algorithms (VQAs) have the potential to demonstrate quantum utility on near-term quantum computers. However, these algorithms often get executed on the highest-fidelity qubits and computers to achieve the best performance, causing low system throughput. Recent efforts have shown that VQAs can be run on low-fidelity qubits initially and high-fidelity qubits later on to still achieve good performance. We take this effort forward and show that carefully varying the qubit fidelity map of the VQA over its execution using our technique, Nest, does not just (1) improve performance (i.e., help achieve close to optimal results), but also (2) lead to faster convergence. We also use Nest to co-locate multiple VQAs concurrently on the same computer, thus (3) increasing the system throughput, and therefore, balancing and optimizing three conflicting metrics simultaneously.
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