Abstract
We describe strategies for quantum-state estimation based on self-learning algorithms. In contrast to the optimal estimation procedures proposed earlier, our schemes rely on measurements performed separately on each quantum system in a finite ensemble. We numerically simulate our strategies in the case of finite ensembles of qubits and compare the resulting average fidelities to the fidelity of optimal quantum-state estimation.
- Received 28 September 1999
DOI:https://doi.org/10.1103/PhysRevA.61.032306
©2000 American Physical Society