发表机构
CWI & QuSoft; Quantum Research Center, Technology Innovation Institute; Institute for Theoretical Physics, University of Cologne; Johannes Kepler Universität Linz; Rigetti Computing（荷兰数学与计算机科学研究中心与QuSoft; 技术研究院量子研究中心; 科隆大学理论物理研究所; 林茨约翰内斯·开普勒大学; 里吉蒂计算）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出迹滤波函数的经典后处理技术，可抑制随机电路基准测试的瞬态模式，在短深度下实现一致的保真度估计，扩展了结构化电路的可靠保真度表征范围。
AI 中文摘要
采用结构化电路的随机基准测试（RB）在实验上具有可扩展性，但由于不完全系综混合会引入瞬态模式，因此会产生有偏差的短深度保真度估计。等待这些瞬态在更深的电路中衰减会使信号低于噪声基底，这是一个已确立的障碍，例如在线性交叉熵基准测试（LinXEB）中。本文仅通过经典后处理克服该障碍，引入了一个单参数估计器族，其在标准LinXEB型后处理与一种名为“迹滤波函数”的新型后处理技术之间进行插值。在实际假设下，迹滤波函数可证明能抑制瞬态模式，揭示短深度下可解释的保真度衰减，其理论保证与标准RB相当，代价是方差增大。本文对该方差进行了界定，分析了新估计器的评估复杂度，并开发了实用的后处理算法。在Rigetti超导处理器上开展的实验验证了该方法适用于最多12量子比特的一维电路：当标准估计器需要超过40层实验窗口的深度时，迹滤波函数在10层以下即可得到一致的估计。因此，迹滤波随机基准测试将可靠的保真度表征扩展到了相关的结构化电路系综和传统估计器无法企及的短深度区域。
英文摘要
Randomized benchmarking (RB) with structured circuits is experimentally scalable, but gives biased short-depth fidelity estimates because incomplete ensemble mixing introduces transient modes. Waiting for these transients to decay in deeper circuits can push the signal below the noise floor. This is a well-established obstacle, e.g. in linear cross-entropy benchmarking (LinXEB). Here we overcome this obstacle solely through classical post-processing. We introduce a one-parameter family of estimators that interpolate between the standard LinXEB-type post-processing and a new post-processing technique we call the trace filter function. Under practical assumptions, the trace filter function provably suppresses transient modes, exposing an interpretable fidelity decay at short depth, with theoretical guarantees comparable to standard RB, at the cost of an increased variance. We bound the variance, analyze the evaluation complexity of the new estimators, and develop practical post-processing algorithms. Experiments on a Rigetti superconducting processor validate the method for one-dimensional circuits of up to 12 qubits: where the standard estimator requires depth beyond a 40-layer experimental window, the trace filter function yields consistent estimates below 10 layers. Trace-filtered randomized benchmarking therefore extends reliable fidelity characterization to relevant structured circuit ensembles and short-depth regimes that are inaccessible to conventional estimators.
