A dynamic adaptive readout method for readout electronics of superconducting quantum computing

Real-time control and readout are pivotal in superconducting quantum computing, given the imperative for numerous algorithms to perform quantum operations as much as possible within the qubit coherent time. Here, we specifically address the qubit readout, recognized as the most time-consuming operation within our experimental platform, and propose a dynamic adaptive readout method (DARM) to improve the performance of qubit readout. In contrast to a standard readout method (SRM) employing Gaussian Naïve Bayes as a discriminator, the DARM can demonstrate a 22.76% relative improvement on readout fidelity when the readout duration time of both methods is set to be consistent. Furthermore, the DARM can also terminate measurement pulse ahead with a 9.93% relative reduction of measurement pulse length on statistical average. The DARM is implemented on a field-programmable-gate-array-based system, and the electronic processing latency, from the digital processing unit getting the qubit signal to the valid output information, is 52 ns, which is only 4 ns longer than the SRM. Compared with the feedforward neural network readout method, the DARM can work in a pipeline mode with shorter electronic processing latency and lower electronic utilization.