SAMOP 2023 – scientific programme

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QI: Fachverband Quanteninformation

QI 35: Quantum Computers: Algorithms and Benchmarking

QI 35.8: Talk

Friday, March 10, 2023, 12:45–13:00, B305

Noise mitigating adaptive quantum tomography — •Adrian Aasen and Martin Gärttner — Kirchhoff-Institut für Physik, Universität Heidelberg, Heidelberg, Germany

Quantum tomography is the process of reconstructing density matrices, or quantum states, and is the golden standard for state discrimination. It is quite an active field partially due to the recent development and benchmarking requirements of quantum computers and hardware. Common for all near term quantum devices is that they are noisy. Knowing how readout errors affect the tomographic estimate and how to mitigate the effect of noise is of significant interest. We leverage two strategies to reduce the overall experimental cost and improve control over noise in experimental setups. Firstly, we limit the use of noisy measurements to fit within a "noise budget". Subsequently we give a theoretical prescription for how to derive an optimal set of measurements within these restrictions, given some noise model. Secondly, we use adaptive strategies, suitable for both maximal likelihood estimation and Bayesian inference, to maximize information extraction per measurement. Combining these two strategies provide an optimal protocol to reach a desired reconstruction accuracy in a noisy environment.