Quantum Information Processing

, Volume 14, Issue 10, pp 3933–3947 | Cite as

Protocol for secure quantum machine learning at a distant place



The application of machine learning to quantum information processing has recently attracted keen interest, particularly for the optimization of control parameters in quantum tasks without any pre-programmed knowledge. By adapting the machine learning technique, we present a novel protocol in which an arbitrarily initialized device at a learner’s location is taught by a provider located at a distant place. The protocol is designed such that any external learner who attempts to participate in or disrupt the learning process can be prohibited or noticed. We numerically demonstrate that our protocol works faithfully for single-qubit operation devices. A trade-off between the inaccuracy and the learning time is also analyzed.


Quantum computation Quantum machine learning Secure machine learning 



We thank Professor Jinhyoung Lee for helpful discussion. J.B. thanks Chang-Woo Lee for comments. We acknowledge the financial support of the Basic Science Research Program through a National Research Foundation of Korea (NRF) grant funded by the Ministry of Science, ICT and Future Planning (No. 2010-0018295).


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Physics and Astronomy, Center for Macroscopic Quantum ControlSeoul National UniversitySeoulKorea

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