17 GBd Sub-Photon Level Heterodyne Detection for CV-QKD Enabled by Machine Learning

Max Rückmann; Sebastian Kleis; Christian G. Schaeffer

doi:10.1364/OFC.2020.Th2A.54

Optical Fiber Communication Conference (OFC) 2020
OSA Technical Digest (Optica Publishing Group, 2020),
paper Th2A.54
•https://doi.org/10.1364/OFC.2020.Th2A.54

17 GBd Sub-Photon Level Heterodyne Detection for CV-QKD Enabled by Machine Learning

Max Rückmann, Sebastian Kleis, and Christian G. Schaeffer

Optical Fiber Communication Conference 2020

San Diego, California United States
8–12 March 2020
ISBN: 978-1-943580-71-2

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Poster Session II (Th2A)

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M. Rückmann, S. Kleis, and C. G. Schaeffer, "17 GBd Sub-Photon Level Heterodyne Detection for CV-QKD Enabled by Machine Learning," in Optical Fiber Communication Conference (OFC) 2020, OSA Technical Digest (Optica Publishing Group, 2020), paper Th2A.54.

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Abstract

We experimentally demonstrate heterodyne detection at a SNR of less than −20 dB with machine learning based optimized carrier phase estimation. Successful 17 GBaud BPSK signal demodulation is achieved without the use of pilot signals.

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