Quantum state estimation when qubits are lost: A no-data-left-behind approach
arXiv:1610.03714 · doi:10.1088/1367-2630/aa65de
Abstract
We present an approach to Bayesian mean estimation of quantum states using hyperspherical parametrization and an experiment-specific likelihood which allows utilization of all available data, even when qubits are lost. With this method, we report the first closed-form Bayesian mean estimate for the ideal single qubit. Due to computational constraints, we utilize numerical sampling to determine the Bayesian mean estimate for a photonic two-qubit experiment in which our novel analysis reduces burdens associated with experimental asymmetries and inefficiencies. This method can be applied to quantum states of any dimension and experimental complexity.
28 pages. Revision includes, in part, changes to the ideal single-qubit MLE section
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