(IWQC20) Filip Maciejewski: Effects & mitigation of realistic readout noise ...
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Full talk title: Effects and mitigation of realistic readout noise in Quantum Approximate Optimization Algorithm
Author: Filip Maciejewski
Abstract: We introduce a correlated measurement noise model that can be efficiently described and characterized, and which admits noise-mitigation on the level of marginal probability distributions. Noise mitigation can be performed up to some error for which we give upper bounds. Characterization of the model is done efficiently using Quantum Overlapping Tomography. We perform experiments on up to 11 qubits on IBM's quantum device and conclude a good agreement with our noise model. Furthermore, we study the effects of the readout noise on the performance of the Quantum Approximate Optimization Algorithm (QAOA). We observe numerically that for numerous objective Hamiltonians, including random MAX 2SAT instances, the noise-mitigation improves the quality of optimization and final estimation in QAOA. Finally, we show that in the task of simultaneous estimation of few-body operators that typically appear in QAOA, the covariances between them vanish for a broad class of states, significantly lowering the sampling complexity.