4.6 Article

Experimental decoy-state Bennett-Brassard 1984 quantum key distribution through a turbulent channel

Journal

PHYSICAL REVIEW A
Volume 103, Issue 3, Pages -

Publisher

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevA.103.032614

Keywords

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Funding

  1. U.S. Office of Naval Research [N00014-15-1-2646]
  2. U.S. Department of Energy (DOE) Office of Cybersecurity Energy Security and Emergency Response (CESER) through the Cybersecurity for Energy Delivery Systems (CEDS) program

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In free-space quantum key distribution (QKD) under turbulent conditions, rejecting received bits below a transmittance threshold can mitigate intensity fluctuations, reducing overall error rate and increasing secure key rate. Through the implementation of the prefixed-threshold real-time selection (P-RTS), higher secure key rates can be achieved for a wide range of atmospheric channel parameters. Additionally, the P-RTS method shows potential for determining an optimal selection threshold even with imperfect knowledge of channel transmittance distribution parameters.
In free-space quantum key distribution (QKD) in turbulent conditions, scattering and beam wandering cause intensity fluctuations which decrease the detected signal-to-noise ratio. This effect can be mitigated by rejecting received bits when the channel's transmittance is below a threshold. Thus, the overall error rate is reduced and the secure key rate increases despite the deletion of bits. In this work, we implement recently proposed selection methods focusing on the prefixed-threshold real-time selection (P-RTS) where a cutoff can be chosen prior to data collection and independently of the transmittance distribution. We perform finite-size decoy-state Bennett-Brassard 1984 QKD in a laboratory setting where we simulate the atmospheric turbulence using an acousto-optical modulator. We show that P-RTS can yield considerably higher secure key rates for a wide range of the atmospheric channel parameters. In addition, we evaluate the performance of the P-RTS method for a realistically finite sample size. We demonstrate that a near-optimal selection threshold can be predetermined even with imperfect knowledge of the channel transmittance distribution parameters.

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