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We introduce an efficient self-learning swarm-intelligence algorithm for devising feedback-based quantum metrological procedures to replace what is otherwise an difficult and inefficient problem. Our algorithm can be trained with simulated or real-world trials and accommodates experimental imperfections, losses, and decoherence.
© 2011 AOS
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