论文标题
有效的量子读数缓解措施，用于稀疏测量结果的近期量子设备
Efficient quantum readout-error mitigation for sparse measurement outcomes of near-term quantum devices
论文作者
论文摘要
近期量子设备上的读数误差是主要的噪声因子之一，可以通过称为量子读数误差（QREM）的经典后处理来减轻。标准QREM将噪声校准矩阵的倒数应用于使用指数计算资源的结果概率分布，以对测得的量子数的数量。对于具有数十吨或更多的当前量子设备而言，这是不可行的。在这里，我们提出了两种有效的QREM方法，以$ O（NS^2）$ $ N $ QUBITS和$ S $ shots的概率分配为$ O（ns^2）$时间，这主要旨在减轻稀疏概率分布，使得只有少数州占主导地位。在以下三种情况下，我们将提出的方法与最近的几种QREM方法进行了比较：GHz状态的期望值，其保真度和最大似然振幅估计（MLAE）算法的估计误差，并具有修改的Grover Etererator。 GHz状态的两种情况处于真实的IBM量子设备上，而第三个则使用数值模拟。使用所提出的方法，65 Qubit GHz状态的缓解仅需几秒钟，我们目睹了超过0.5的29 Qubit GHz状态的保真度。所提出的方法还成功地减少了MLAE算法中的估计误差，从而超过了其他QREM方法的结果。
The readout error on near-term quantum devices is one of the dominant noise factors, which can be mitigated by classical postprocessing called quantum readout error mitigation (QREM). The standard QREM applies the inverse of noise calibration matrix to the outcome probability distribution using exponential computational resources to the number of measured qubits. This becomes infeasible for the current quantum devices with tens of qubits or more. Here we propose two efficient QREM methods finishing in $O(ns^2)$ time for probability distributions of $n$ qubits and $s$ shots, which mainly aim at mitigating sparse probability distributions such that only a few states are dominant. We compare the proposed methods with several recent QREM methods in the following three cases: expectation values of the GHZ state, its fidelities, and the estimation error of maximum likelihood amplitude estimation (MLAE) algorithm with a modified Grover iterator. The two cases of the GHZ state are on real IBM quantum devices, while the third is with numerical simulation. Using the proposed method, the mitigation of the 65-qubit GHZ state takes only a few seconds, and we witness the fidelity of the 29-qubit GHZ state exceeding 0.5. The proposed methods also succeed in reducing the estimation error in the MLAE algorithm, outperforming the results by other QREM methods in general.
