Generalized Markovian Noise as a Resource for Suppressing Markovian Errors in Superconducting Qubits: Part I (Simulations)

Non-Markovian noise environments, i.e. environments with temporal correlation, are well known to have detrimental effects on quantum
computational tasks with superconducting qubits. In recent years, there has been intense interest in characterizing non-Markovian environments, on active control protocols to eliminate their effects, and on ways to harness them to reduce errors. In this talk, we present computational results showing that non-Markovian noise can in fact be used to improve the coherence of a qubit embedded in a purely Markovian noisy background. We show further that our quantum trajectory simulations enable us to find the memory kernel function that offers the best improvement in qubit coherence. We compare these computational results with theoretical predictions of the corresponding master equation and show that this stochastic error correction scheme yields even better performance than predicted by theory. We finally discuss how this method compares with conventional error suppression schemes and how our results provide a powerful tool in controlling and engineering qubit dissipation processes.