ArsoNISQ: 分析近邻架构上的量子算法
ArsoNISQ: Analyzing Quantum Algorithms on Near-Term Architectures
AI总结：
提出ArsoNISQ框架以分析NISQ架构上量子算法的可容忍错误率与成功概率，评估发现无内在鲁棒性算法，电路规模决定错误率上限，为算法开发和平台选择提供支持。
摘要：
尽管可扩展的全纠错量子计算还需要数年甚至数十年时间，但人们对含噪声中等规模量子计算（NISQ）抱有相当大的兴趣。本文提出了ArsoNISQ框架，该框架可确定给定量子算法计算（即量子电路）的可容忍错误率，以及在给定成功准则和NISQ计算机的情况下计算的成功概率。ArsoNISQ基于受泡利错误模型影响的量子电路模拟。我们在一组可实现量子加速或与NISQ计算相关的量子算法上评估了ArsoNISQ。尽管近期文献中存在乐观预期，但在本次评估中我们未观察到具有内在鲁棒性的量子算法，即平均能容忍一个错误的算法。不过，评估表明量子电路规模为其可容忍错误率设定了上限，并量化了相似规模量子电路在可容忍错误率上的差异。因此，该框架可帮助量子算法开发者改进其实现并选择合适的NISQ计算平台。将结果外推到量子优势区域表明，对于大多数被评估的算法，更大规模量子计算机的错误率必须大幅降低，或者需要部署主动量子纠错。
英文摘要：
While scalable, fully error corrected quantum computing is years or even decades away, there is considerable interest in noisy intermediate-scale quantum computing (NISQ). In this paper, we introduce the ArsoNISQ framework that determines the tolerable error rate of a given quantum algorithm computation, i.e. quantum circuits, and the success probability of the computation given a success criterion and a NISQ computer. ArsoNISQ is based on simulations of quantum circuits subject to errors according to the Pauli error model. ArsoNISQ was evaluated on a set of quantum algorithms that can incur a quantum speedup or are otherwise relevant to NISQ computing. Despite optimistic expectations in recent literature, we did not observe quantum algorithms with intrinsic robustness, i.e. algorithms that tolerate one error on average, in this evaluation. The evaluation demonstrated, however, that the quantum circuit size sets an upper bound for its tolerable error rate and quantified the difference in tolerate error rates for quantum circuits of similar sizes. Thus, the framework can assist quantum algorithm developers in improving their implementation and selecting a suitable NISQ computing platform. Extrapolating the results into the quantum advantage regime suggests that the error rate of larger quantum computers must decrease substantially or active quantum error correction will need to be deployed for most of the evaluated algorithms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
