TL;DR
This paper introduces a quantum model averaging approach to address model uncertainty in quantum state tomography and randomized benchmarking, improving parameter estimation reliability.
Contribution
It applies model averaging techniques to quantum analysis, specifically for rank selection in tomography and model choice in fidelity decay curves, enhancing estimation robustness.
Findings
Improved accuracy in quantum state rank estimation.
More reliable model selection in fidelity decay analysis.
Mitigation of overconfidence in quantum parameter estimates.
Abstract
Standard tomographic analyses ignore model uncertainty. It is assumed that a given model generated the data and the task is to estimate the quantum state, or a subset of parameters within that model. Here we apply a model averaging technique to mitigate the risk of overconfident estimates of model parameters in two examples: (1) selecting the rank of the state in tomography and (2) selecting the model for the fidelity decay curve in randomized benchmarking.
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