Phys. Rev. Lett. 104, 063603 (2010) [4 pages]Machine Learning for Precise Quantum MeasurementReceived 6 October 2009; published 11 February 2010 Adaptive feedback schemes are promising for quantum-enhanced measurements yet are complicated to design. Machine learning can autonomously generate algorithms in a classical setting. Here we adapt machine learning for quantum information and use our framework to generate autonomous adaptive feedback schemes for quantum measurement. In particular, our approach replaces guesswork in quantum measurement by a logical, fully automatic, programable routine. We show that our method yields schemes that outperform the best known adaptive scheme for interferometric phase estimation. © 2010 The American Physical Society URL:
http://link.aps.org/doi/10.1103/PhysRevLett.104.063603
DOI:
10.1103/PhysRevLett.104.063603
PACS:
42.50.Dv, 03.67.-a, 07.05.Mh
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