Data underlying the publication: Improved error correction with leakage reduction units built into qubit measurement in a superconducting quantum processor

This research is to demonstrate a zero-time overhead leakage reduction unit in superconducting qubit and investigate its benefit in quantum error correction in experiment. The dataset is to support findings in the paper. The experiments were done on a 17-qubit superconducting quantum processor. Data are collected by standard readout of superconducting qubits using RF signals. Experiments include characterization of the leakage reduction unit, and its application in memory experiments of a distance-3 repetition code and 7-qubit stability experiments. The characterization sweeps the control parameters and plots the key performance, defined in the paper. The error correction experiments repeatedly measure qubits using the circuits defined in the paper, and use a neural-network decoder to interpret the measurement outcomes. The processing, training and testing of measurement outcomes with neural-network can be found in https://github.com/MarcSerraPeralta/data-lru-integrated-with-measurement-for-qec/

本研究旨在展示一款应用于超导量子比特（superconducting qubit）的零时间开销泄露抑制单元，并通过实验探究其在量子纠错中的应用价值。本数据集用于支撑该论文的研究结论。实验基于一台17量子比特超导量子处理器开展，数据通过射频（RF）信号对超导量子比特进行标准读出流程采集得到。实验内容涵盖泄露抑制单元的性能表征，以及其在距离3重复码（distance-3 repetition code）存储实验与7量子比特稳定性实验中的应用。性能表征环节通过扫描控制参数，绘制论文中定义的关键性能指标曲线。量子纠错实验采用论文中定义的电路对量子比特进行重复测量，并借助神经网络解码器（neural-network decoder）解读测量结果。有关神经网络对测量结果的处理、训练与测试流程，可参见链接：https://github.com/MarcSerraPeralta/data-lru-integrated-with-measurement-for-qec/