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Quantum State Estimation from Partial Tomography Data Using a Stack of Machine Learning Models and Imputation

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Abstract

Reconstruction of two-qubit systems typically performed using 36 coincidence measurements. We trained an ensemble of CNN & XGBoost ML models, employed imputation to demonstrate high-fidelity state estimation when multiple measurements are missing.

© 2020 The Author(s)

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