Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Efficient Algorithm for Optimizing Adaptive Quantum Metrology

Not Accessible

Your library or personal account may give you access

Abstract

We introduce an efficient self-learning swarm-intelligence algorithm for devising feedback-based quantum metrological procedures to replace what is otherwise an inefficient problem. Our algorithm can be trained with simulated or real-world trials.

© 2011 Optical Society of America

PDF Article
More Like This
An Efficient Algorithm for Optimizing Adaptive Quantum Metrology Processes

Barry C. Sanders and Alexander Hentschel
I184 International Quantum Electronics Conference (IQEC) 2011

Adaptive Quantum Measurement via Swarm-Intelligence Machine Learning

Barry C. Sanders and Alexander Hentschel
QW1B.1 Quantum Information and Measurement (QIM) 2012

Reinforcement Learning for Adaptive Optical Quantum-Enhanced Metrology

Barry C. Sanders, Pantita Palittapongarnpim, and Seyed Shakib Vedaie
STu5H.4 Applications of Lasers for Sensing and Free Space Communications (LS&C) 2018

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.