The integration of machine learning techniques has opened new avenues for real-time quantum state tomography (QST). In this work, we demonstrate the deployment of machine learning-based QST onto edge devices, specifically utilizing Field-Programmable Gate Arrays (FPGAs). This implementation was realized using the ”Vitis AI” development environment provided by AMD Inc. The FPGA-based QST offers a highly efficient and precise tool for diagnosing quantum states, marking a significant advancement in the practical application of quantum state tomography.
Wu et al. (Wed,) studied this question.