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This paper advances continuous-variable quantum key distribution by introducing multidimensional reconciliation techniques that transform Gaussian channels into virtual binary-input noise models for enhanced error correction. The authors provide an open-source simulation framework, HDirac, which enables the evaluation of high-dimensional constructions and offers practical trade-off analysis between dimensionality, efficiency, and frame error rates. These tools and findings offer immediate value for researchers designing next-generation quantum communication systems operating under low signal-to-noise conditions.
Multidimensional Reconciliation in Continuous-Variable QKD: Review, Coding Schemes, and Open Source Simulation
arXiv:2606.02323v2 Announce Type: replace-cross Abstract: Continuous-variable quantum key distribution (CV-QKD) requires highly efficient reconciliation techniques to operate at low signal-to-noise ratios and long distances. Multidimensional reconciliation addresses this challenge by transforming the physical Gaussian quantum channel into a virtual binary-input additive white Gaussian noise (BIAWGN) channel, enabling the use of modern errorcorrecting codes. In this work, we review the principles of multidimensional reconciliation, with a particular focus on high-dimensional constructions beyond the algebraic dimensions 1, 2, 4, 8. We describe the construction of the virtual channel, discuss practical coding schemes for reverse reconciliation, and analyse their integration with linear error-correcting codes. We also present an opensource simulation framework, HDirac, implementing multidimensional reconciliation for arbitrary dimensions, and use it to evaluate state-of-the-art LDPC codes. The results highlight key trade-offs between dimension, reconciliation efficiency, and frame error rate, providing practical guidance for CV-QKD system design.
Abstract:Continuous-variable quantum key distribution (CV-QKD) requires highly efficient reconciliation techniques to operate at low signal-to-noise ratios and long distances. Multidimensional reconciliation addresses this challenge by transforming the physical Gaussian quantum channel into a virtual binary-input additive white Gaussian noise (BIAWGN) channel, enabling the use of modern errorcorrecting codes. In this work, we review the principles of multidimensional reconciliation, with a particular focus on high-dimensional constructions beyond the algebraic dimensions 1, 2, 4, 8. We describe the construction of the virtual channel, discuss practical coding schemes for reverse reconciliation, and analyse their integration with linear error-correcting codes. We also present an opensource simulation framework, HDirac, implementing multidimensional reconciliation for arbitrary dimensions, and use it to evaluate state-of-the-art LDPC codes. The results highlight key trade-offs between dimension, reconciliation efficiency, and frame error rate, providing practical guidance for CV-QKD system design.
15 pages, 8 figures. Link to the open-source project: this https URL
Information Theory (cs.IT); Cryptography and Security (cs.CR); Quantum Physics (quant-ph)
A.1; E.4; G.3; J.2
arXiv:2606.02323 [cs.IT]
(or arXiv:2606.02323v2 [cs.IT] for this version)
https://doi.org/10.48550/arXiv.2606.02323 Focus to learn more arXiv-issued DOI via DataCite
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Full text under the publisher's open licence · 253 words