量子过程非线性性质的鲁棒估计
Robust Estimation of Nonlinear Properties of Quantum Processes
AI总结：
针对量子过程非线性性质估计对状态制备与测量误差的鲁棒性需求，提出两种基于随机门序列但后处理不同的协议，分别实现非时序关联的鲁棒估计（伊辛模型数值验证）和幺正性估计以表征量子信道非相干性，助力量子多体物理研究与量子过程表征。
摘要：
量子过程性质的准确且鲁棒估计对量子信息处理和量子多体物理至关重要。Helsen等人结合经典阴影层析和随机基准测试，提出了一种估计量子过程线性性质的方法。本工作聚焦于对状态制备和测量误差具有鲁棒性的非线性过程性质估计协议。我们引入两种协议，均利用随机门序列但采用不同的后处理方法，使其适用于测量不同非线性性质。第一种协议提供了鲁棒且可靠的方法来估计非时序关联，如伊辛模型中的数值演示所示；第二种协议估计幺正性，有效表征量子信道的非相干性。我们期望这两种协议成为探索量子多体物理和表征量子过程的有用工具。
英文摘要：
Accurate and robust estimation of quantum process properties is crucial for quantum information processing and quantum many-body physics. Combining classical shadow tomography and randomized benchmarking, Helsen et al. introduced a method to estimate the linear properties of quantum processes. In this work, we focus on the estimation protocols of nonlinear process properties that are robust to state preparation and measurement errors. We introduce two protocols, both utilizing random gate sequences but employing different post-processing methods, which make them suitable for measuring different nonlinear properties. The first protocol offers a robust and sound method to estimate the out-of-time-ordered correlation, as demonstrated numerically in an Ising model. The second protocol estimates unitarity, effectively characterizing the incoherence of quantum channels. We expect the two protocols to be useful tools for exploring quantum many-body physics and characterizing quantum processes.
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