ML for Quantum Error Correction
RNN-based protocol for ancilla-free QEC on transmons
We were invited to talk about our paper Machine Learning for Continuous Quantum Error Correction on Superconducting Qubits at the biweekly colloquium of Quantum Systems Accelerator in January 2022. Also check us out at the 2022 American Physical Society (APS) March Meeting.
Welcome to learn about how we leverage Bayesian inference and machine learning for continuous-in-time, ancilla-free quantum error corrections below.
Below is our poster presentation for the Quantum Techniques in Machine Learning (QTML) 2021 conference.
Source code for this project can be found at this Google Colab notebook