Gaussian quadrature inference for continuous-variable quantum key distribution

L. Gyongyosi; S. Imre

doi:10.1117/12.2223482

20 May 2016 Gaussian quadrature inference for continuous-variable quantum key distribution

L. Gyongyosi, S. Imre

Proceedings Volume 9873, Quantum Information and Computation IX; 987305 (2016) https://doi.org/10.1117/12.2223482
Event: SPIE Commercial + Scientific Sensing and Imaging, 2016, Baltimore, MD, United States

Abstract

We propose the Gaussian quadrature inference (GQI) method for multicarrier continuous-variable quantum key distribution (CVQKD). A multicarrier CVQKD protocol utilizes Gaussian subcarrier quantum continuous variables (CV) for information transmission. The GQI framework provides a minimal error estimate of the quadratures of the CV quantum states from the discrete, measured noisy subcarrier variables. GQI utilizes the fundamentals of regularization theory and statistical information processing. We characterize GQI for multicarrier CVQKD, and define a method for the statistical modeling and processing of noisy Gaussian subcarrier quadratures. We demonstrate the results through the adaptive multicarrier quadrature division (AMQD) scheme. We introduce the terms statistical secret key rate and statistical private classical information, which quantities are derived purely by the statistical functions of GQI. We prove the secret key rate formulas for a multiple access multicarrier CVQKD via the AMQD-MQA (multiuser quadrature allocation) scheme. The framework can be established in an arbitrary CVQKD protocol and measurement setting, and are implementable by standard low-complexity statistical functions, which is particularly convenient for an experimental CVQKD scenario.

Citation Download Citation

L. Gyongyosi and S. Imre "Gaussian quadrature inference for continuous-variable quantum key distribution", Proc. SPIE 9873, Quantum Information and Computation IX, 987305 (20 May 2016); https://doi.org/10.1117/12.2223482

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