发表机构
University of Wisconsin–Madison（威斯康星大学麦迪逊分校）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出腔量子退火，将退火错误交换为光子，缩短退火时间至平方根量级，并通过光子计数验证高保真结果。
AI 中文摘要
量子退火是一种有前景的量子计算形式，但在退火过程中，由于小能隙 $\Delta$ 的存在，其速度会减慢，且在此过程中产生的错误未被检测到。我们引入了腔量子退火，其中频率为 $O(1)\gg\Delta$ 的腔模，在调度中期耦合，将这些错误交换为光子。在 $p$-自旋模型中，这使退火时间缩短至无腔时所需时间的平方根左右。此外，光子计数可验证结果：高光子运行，产率为 $O(1)$，达到基态保真度高于 $99.99\\%$ 的速度快数个数量级，且这一增益随系统规模呈指数增长。预先加载的光子则反向运行交换，制备激发态。更广泛地，我们的工作表明，腔可以增强使用量子比特进行的计算，为通过量子退火实现高保真量子态制备铺平了道路。
英文摘要
Quantum annealing is a promising form of quantum computation, but it slows down at a small energy gap $Δ$ during the anneal, and the errors it makes there remain undetected. We introduce cavity quantum annealing, in which a cavity mode of frequency $O(1)\ggΔ$, coupled mid-schedule, swaps these errors into photons. In the $p$-spin model, this reduces the annealing time to nearly the square root of that required without the cavity. Moreover, counting the photons certifies the result: high-photon runs, with an $O(1)$ yield, reach a ground-state fidelity above $99.99\%$ orders of magnitude sooner, a gain that grows exponentially with system size. A pre-loaded photon instead runs the swap in reverse, preparing an excited state. More broadly, our work shows that cavities can enhance computations performed with qubits, paving the way toward high-fidelity quantum state preparation by quantum annealing.
Comments10 pages, 6 figures
