Title :
An efficient algorithm for optimizing adaptive quantum metrology processes
Author :
Sanders, Barry C. ; Hentschel, Alexander
Author_Institution :
Inst. for Quantum Informatiom Sci., Univ. of Calgary, Calgary, AB, Canada
fDate :
Aug. 28 2011-Sept. 1 2011
Abstract :
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.
Keywords :
optical losses; quantum optics; quantum theory; unsupervised learning; decoherence; experimental imperfections; feedback-based quantum metrological procedures; optical losses; optimized adaptive quantum metrology processes; real-world trials; self-learning swarm-intelligence algorithm; Algorithm design and analysis; Atmospheric measurements; Metrology; Noise; Noise measurement; Phase shifting interferometry; Training;
Conference_Titel :
Quantum Electronics Conference & Lasers and Electro-Optics (CLEO/IQEC/PACIFIC RIM), 2011
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4577-1939-4
DOI :
10.1109/IQEC-CLEO.2011.6193672
