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cs.ITcs.CRquant-ph
Local ID: 2606.02323v2
AI Summary: gemma4:e4b
Multidimensional Reconciliation in Continuous-Variable QKD: Review, Coding Schemes, and Open Source Simulation
By Lucien Martial, Alexis Rosio, Eleni Diamanti, Adrien Cassagne, Baptiste Gouraud
Revision History Timeline
v16/1/2026
6/1/2026
“15 pages, 8 figures. Link to the open-source project: https://github.com/aff3ct/HDirac”
v26/2/2026
6/2/2026
“15 pages, 8 figures. Link to the open-source project: https://github.com/aff3ct/HDirac”
★ Version indexed in ExplorerComparing v1 vs v2
Green = Added • Red = Removed
Title Comparison
Multidimensional Reconciliation in Continuous-Variable QKD: Review, Coding Schemes, and Open Source Simulation
Authors Comparison
Removed:Martial LucienRosio AlexisDiamanti EleniCassagne AdrienGouraud Baptiste
Added:Lucien MartialAlexis RosioEleni DiamantiAdrien CassagneBaptiste Gouraud
Unchanged:
v1 Comment
“15 pages, 8 figures. Link to the open-source project: https://github.com/aff3ct/HDirac”
v2 Comment
“15 pages, 8 figures. Link to the open-source project: https://github.com/aff3ct/HDirac”
Abstract Word Diff
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.