An efficient algorithm for optimizing adaptive quantum metrology processes
Barry Cyril Sanders, Alexander Hentschel · 2011
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.