论文标题
快速估计稀疏量子噪声
Fast Estimation of Sparse Quantum Noise
论文作者
论文摘要
随着量子计算机接近容错阈值，诊断和表征大规模量子设备上的噪声变得越来越重要。最重要的噪声通道类别之一是Pauli通道的类别，原因是理论障碍性和实验性相关性。在这里，我们提出了一种实用算法，用于估计$ s $零的保利错误率在$ s $ -sparse，$ n $ qubit的Pauli噪声频道，或更一般而言是$ S $最大的Pauli错误率。该算法具有严格的恢复保证金，仅使用$ O（n^2）$测量，$ O（s n^2）$经典处理时间和Clifford Quantum电路。我们通过实验验证了该算法的启发式版本，该算法使用简化的Clifford电路对来自IBM 14 Quition的超导设备的数据和我们的开源实现。这些数据表明，即使信号是测量噪声底层以下两个数量级的信号，对任意权重误差的可能性的准确和精确估计也是可能的。
As quantum computers approach the fault tolerance threshold, diagnosing and characterizing the noise on large scale quantum devices is increasingly important. One of the most important classes of noise channels is the class of Pauli channels, for reasons of both theoretical tractability and experimental relevance. Here we present a practical algorithm for estimating the $s$ nonzero Pauli error rates in an $s$-sparse, $n$-qubit Pauli noise channel, or more generally the $s$ largest Pauli error rates. The algorithm comes with rigorous recovery guarantees and uses only $O(n^2)$ measurements, $O(s n^2)$ classical processing time, and Clifford quantum circuits. We experimentally validate a heuristic version of the algorithm that uses simplified Clifford circuits on data from an IBM 14-qubit superconducting device and our open source implementation. These data show that accurate and precise estimation of the probability of arbitrary-weight Pauli errors is possible even when the signal is two orders of magnitude below the measurement noise floor.
